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2014 SERVICES/BigData Congress

CLOUD/ICWS/SCC/MS

ADVANCE PROGRAM2014 21st International Conference on Web Services (ICWS)

http://icws.org

2014 11thInternational Conference on Services Computing (SCC)http://conferences.computer.org/scc

2014 7thInternational Conference on Cloud Computing (CLOUD)

http://thecloudcomputing.org2014 3rdInternational Congress on Big Data (BigData Congress)

http://www.ieeebigdata.org

2014 3rdInternational Conference on Mobile Services (MS)http://www.themobileservices.org

2014 10thWorld Congress on Services (SERVICES)http://http://www.servicescongress.org

June 27-July 2, 2014Hilton Anchorage

500 West Third Avenue, AnchorageAlaska, 99501, USA

Tel: +1 907-272-7411Twitter: @servicesconfs Topic: SERVICES2014


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IEEE 2014 SERVICES/CLOUD/ICWS/SCC/BigData Congress/MS Anchorage, AK, USA

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CONFERENCE LEADERSHIP TEAM

General ChairsICWS 2014 SCC 2014

Jeffrey Tsai, Asia University, TaiwanMichael Goul, Arizona State University, USA

I-Ling Yen, University of Texas at Dallas, USA

CLOUD 2014 MS 2014Alan Sussman, University of Maryland, USA

Liana L. Fong, IBM T.J. Watson Research Center, USAMichael Melliar-Smith, University of California - Santa

Barbara, USA

BigData Congress 2014 SERVICES 2014Paul Hofmann, Saffron Technology, USAMing-Chien Shan, SAP Research, USAWu Chou, Huawei IT Lab, Huawei, USA

Stephen S. Yau, Arizona State University, USAEphraim Feig, Chair, IEEE TC-SVC

Program ChairsICWS 2014 SCC 2014

David De Roure, Oxford University, UKBhavani Thuraisingham, University of Texas, Dallas,

USAJia Zhang, Carnegie Mellon University Silicon Valley,

USA (Vice Chair)

Elena Ferrari, University of Insubria, ItalyRavindran Kaliappa, City University of New York, USA

Patrick C.K. Hung, University of Ontario institute ofTechnology, Canada (Vice Chair)

CLOUD 2014 MS 2014

Carl Kesselman, University of Southern California, USARong Chang, IBM T.J. Watson Research Center, USA

Nimish Radia, Ericsson, USAYan Wang, Macquarie University, Australia

BigData Congress 2014Peter Chen, Carnegie Mellon University & Louisana State University, USA

Hemant Jain, University of WisconsinMilwaukee, USA

Steering CommitteeCarl K. Chang, Iowa State University, USA

Ephraim Feig, IEEE TC-SVC, USAHemant Jain, University of Wisconsin at Milwaukee, USA

Frank Leymann, University of Stuttgart, GermanyCalton Pu, Georgia Tech, USA

Jeffrey Tsai, University of Illinois at Chicago, USALiang-Jie Zhang (Chair), Kingdee International Software Group CO., Ltd, China


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Table of Contents

Conference Leadership Team ................................................... ...................................................................2Program Overview ............................. .......................... .................................................................................. ..... 3

June 27, 2014 (Friday) ..................................................................... .............................................. ... 3June 28, 2014 (Saturday) ........ .................... ................................ .................................................. ... 4June 29, 2014 (Sunday) .................................. .... ............................. .............. ............................... .. .. 5June 30, 2014 (Monday) .......................................... ...................... ................................................. .. . 6July 1, 2014 (Tuesday) .................................. ..................... ................................... ............... 7July 2, 2014 (Wednesday)............................................... ....................................................... .............. 8

CLOUD/ICWS/SCC/BigDataCongress/MS/SERVICES 2014 Keynotes............. .. ............................ .... ..... 10CLOUD/ICWS/SCC/BigDataCongress/MS/SERVICES 2014 Plenary Panels ........ ..................................... 13CLOUD/ICWS/SCC/BigDataCongress/MS/SERVICES 2014 Tutorials ................. ..................................... 20

2014 IEEE 21stInternational Conference on Web Services (ICWS 2014) ................................................... 24

Research Track ................................................................................................................................... 25Applications and Industry Track .......................................................................................... .... 26Work-in-Progress Track .................... ............................................................................ .... 29

2014 IEEE 7thInternational Conference on Cloud Computing (CLOUD 2014) ...................................... 31Research Track ................................................................................. ................................................. 31Applications and Industry Track ............................................... .......................................... .... 34Work-in-Progress Track .................... ........................... ................................................ .... 38

2014 IEEE 3rdInternational Conference on Mobile Services (MS 2014)......... ............... ........... 41Research Track ................................................................................................................................... 41Applications and Industry Track .................................... .... 41Work-in-Progress Track .................... ................................................................................... .... 42

2014 IEEE 11thInternational Conference on Services Computing (SCC 2014) .. ............................. ........... 43Research Track ................................................................................................................................... 43Applications and Industry Track .................................... .... 45Work-in-Progress Track .................... ................................................................................... .... 50

2014 IEEE 3rdInternational Congress on Big Data (BigData Congress 2014) . ............... ........... 51Research Track ................................................................................................................................... 51Applications and Industry Track .................................... .... 54Work-in-Progress Track .................... ................................................................................... .... 57

2014 IEEE 10thWorld Congress on Services (SERVICES 2014) ................ .................................................... 59Applications and Industry Track 59Workshops ....................................................................... ...................... ............................................ 59

Journal Support ............................................................... ............................................................. 66Conference Room Floor Plan ............................................................... ............................................................. 67


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IEEE 2014

ICWS/SCC/CLOUD/BigDataCongress/MS/SERVICES Keynote Sessions

Keynote 1: Clouds, Crowds and Provenance (Susan Davidson, University

of Pennsylvania, USA)(SERVICES2014-7002)(06/28 Saturday, 9:50-12:00; Alaska Ballroom)

Abstract:Harnessing the crowd to collect and/or analyze massive amounts of data (crowdsourcing) has becomeincreasingly popular. Examples in our culture include Wikipedia, social tagging systems for images, trafficinformation aggregators like Waze, citizen science applications such as Galaxy Zoo, and hotel and movieratings like TripAdvisor and IMDb. Cloud platforms are also increasingly being explored for hostingcrowdsourcing systems, and for exposing the crowd as a service. In this talk, I give an overview of the

challenges inherent in providing declarative, database-style platforms for supporting crowdsourcing. I thendiscuss how to go one step further and enable users to posed general questions to mine the crowd and to receiveconcise, relevant answers that represent frequent significant data patterns. Finally, I discuss the importance ofcapturing provenance for crowdsourcing applications, and the inherent challenges due to the massive size ofdata and complex analytics.

About the Speaker: Susan B. Davidson is the Weiss Professor of Computer andinformation Science (CIS) at the University of Pennsylvania (Penn). She received herB.A. degree in Mathematics from Cornell University in 1978, her Ph.D. degree inElectrical Engineering and Computer Science from Princeton University in 1982, andjoined Penn in 1982. Dr. Davidson was a founding co-Director of the Penn Center forBioinformatics as well as the regional Greater Philadelphia Bioinformatics Alliance,served as the Deputy Dean of the School of Engineering and Applied Science, is the

founding Faculty Director of Advancing Women in Engineering at Penn, and recentlystepped down as Chair of CIS. She is an ACM Fellow, a Fulbright scholar, and serveson the Board of Directors of the Computing Research Association and the ExecutiveCommittee of the Computing Community Constorium. Dr. Davidson's research

interests include database systems, database integration, distributed systems, bioinformatics, scientific workflowsystems, provenance, and crowd data-sourcing.

Keynote 2: On Mining Big Data (Philip S. Yu, University of Illinois atChicago, USA)(SERVICES2014-7003)

(06/29 Sunday, 9:45-11:00; Alaska Ballroom)

Abstract: The problem of big data has become increasingly important in recent years. On the one hand, the bigdata is an asset that potentially can offer tremendous value or reward to the data owner. On the other hand, itposes tremendous challenges to mine the value out of the big data. The very nature of the big data poseschallenges not only due to its volume, and velocity of being generated, but also its variety. Here variety means

the data can be collected from various sources with have different formats. One of themost critical big data applications is mining social networks. As social networksbecome increasingly popular, not only the scale of the networks grows rapidly, but alsothe complexity of the networks increases over time. In this talk, we will discuss thesebig data issues and approaches to address them using social networks as an example.

About the Speaker: Dr. Philip S. Yu is a Distinguished Professor and the WexlerChair in Information Technology at the Department of Computer Science, University ofIllinois at Chicago. Before joining UIC, he was at the IBM Watson Research Center,where he built a world-renowned data mining and database department. He is a Fellow


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of ACM and IEEE. Dr. Yu has been making tremendous, and globally recognized contributions to the principlesof mining big data. He is the recipient of IEEE Computer Societys 2013 Technical Achievement Award forpioneering and fundamentally innovative contributions to the scalable indexing, querying, searching, mining

and anonymization of big data. Dr. Yu has published more than 800 papers in refereed journals andconferences, cited by more than 52,000 times with an H-index of 109. He holds or has applied for more than300 US patents.

Dr. Yu is the Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data. He is on the steeringcommittee of the IEEE Conference on Data Mining and ACM Conference on Information and KnowledgeManagement, and was a member of the IEEE Data Engineering steering committee. He was the Editor-in-Chiefof IEEE Transactions on Knowledge and Data Engineering (2001-2004). He received a Research ContributionsAward from IEEE Intl. Conference on Data Mining (ICDM) in 2003, the ICDM 2013 10-year Highest-ImpactPaper Award, and the EDBT Test of Time Award (2014). Dr. Yu received his PhD from Stanford University.

Keynote 3: Predictive Analytics Governance in Business: A New Services

Computing Frontier (Michael Goul, Arizona State University, USA)(SERVICES2014-7004)(06/29 Sunday, 14:30-15:45; Alaska Ballroom)

Abstract:The proliferation of deployed predictive analytics - all across business service landscapes - will serve tochallenge earlier conceptualizations of services computing and business process management/integration. Forexample, monitoring for predictive model decay in embedded Internet of things software services represents anew governance challenge and opportunity. Big data acquisition and integration for purposes of testing forpredictive model decay will require new insights for SOA platforms. To address this new frontier for servicescomputing, we will generalize a business perspective to the deployment of predictive analytics, discussstrategies for predictive analytics governance and demonstrate the pitfalls of failing to implement appropriategovernance mechanisms. Reconciling data scientists current predictive analytics discoverymethodologies withwhat it takes to deployanalytics into modern IT service systems represents a new corporate balancing act. The

hand-offs between data scientists and services computing developers need to be examined in light of newcompliance realities that impact the services lifecycle. Abstracting from current best practices in companieslike UBS, eHarmony, Linked-in, eBay, American Express and others provides a fresh perspective to predictiveanalytics governance. Challenges to be faced are ripe for research innovations by the services computing

community.

About the Speaker: Michael Goul is Professor and Chair of the Department of InformationSystems, W.P. Carey School of Business, Arizona State University. His research bridges servicescomputing and analytics. He was Co-PI on grants from Intel and American Express at the intersectionof these areas, and he recently authored a case on eBays approach to experimentation that relies on amulti-tenant, self-service data warehouse infrastructure. His work in services computing led to a one-year appointment as a Distinguished University Scholar at the Clinton School of Public Service. Goul isalso on the research faculty of the W.P. Carey Schools Center for Services Leadership.

Keynote 4: Toward a Science of Security (and Governance) in ServiceSystems (Munindar Singh, North Carolina State University, USA)

(SERVICES2014-7005)(06/30 Monday, 9:45-11:00; Alaska Ballroom)

Abstract: Despite sustained research effort in security, current security practice conveys a decidedly ad hocflavor --- find a bug; patch it; find the next bug; and so on. This methodology is sometimes termed"engineering", using the term in the narrow sense of developing solutions to specific problems. The past fewyears have seen a growing push to develop a Science of Security (SoS), viewed as a systematic body ofknowledge with strong theoretical and empirical underpinnings that inform the engineering of secureinformation systems.


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I introduce SoS, briefly describing its key elements. I then motivate some of the foundational challenges of SoSfrom the standpoint of systems of autonomous participants, such as cross-organizational service systems. Idescribe how security is an element of the governance of such systems. I introduce an approach for governancebased on a new formulation of norms and accountability, showing how it addresses the challenges of securitypertaining to secure collaboration and would facilitate the development of flexible and secure cross-organizational service engagements.

About the Speaker: Dr. Munindar P. Singh is a professor in the Department ofComputer Science at North Carolina State University. Munindar's research interestsinclude service-oriented computing, security, and social computing. He addresses thechallenges of trust, norms, requirements modeling, service ecosystems, and businessprocesses and protocols in large-scale open environments.

Munindar is the editor-in-chief of ACM Transactions on Internet Technology. From1999 to 2002, he was the editor-in-chief of IEEE Internet Computing. His currenteditorial service includes IEEE Internet Computing, Journal of Autonomous Agents and

Multiagent Systems, IEEE Transactions on Services Computing, ACM Transactions onIntelligent Systems and Technology, the Journal of Artificial Intelligence Research, and the Journal of TrustManagement. Munindar served on the founding board of directors of IFAAMAS, the International Foundationfor Autonomous Agents and MultiAgent Systems.

Munindar is a Fellow of the IEEE. His research has been recognized with awards and sponsorship by(alphabetically) Army Research Lab, Army Research Office, Cisco Systems, Consortium for Ocean Leadership,DARPA, Ericsson, IBM, Intel, National Science Foundation, National Security Agency, and Xerox. Nineteenstudents have received PhD degrees and 27 students MS degrees under Munindar's direction.

Keynote 5: Modern Service industry in China: Crossover, Convergence,

and Complex Services (Zhaohui Wu, Zhejiang University, China)(SERVICES2014-7006)

(07/01 Tuesday, 9:45-11:00; Alaska Ballroom)

Abstract: Modern Service industry is not only becoming a leading and pillar industry for economicdevelopment, but also an important indicator of measuring the degree of production socialization and marketeconomic development. As a matter of course, Service Oriented Computing, as the academic foundation ofModern Service industry, attracts lots of attention in the last decade. However, the big data and the developmentof emerging computing paradigms such as Cloud Computing, internet-Of-Things, and Mobile internet havemade Service Oriented Computing more and more complex. in this talk, we will give the concept and overviewof the development trend of Modern Service industry in the world, especially the development of ModernService industry in China. Moreover, we give the concept and the definition of complex service, which has thecharacteristics of 3C, i.e., convergence, and complex. Further, a technique architecture for complex servicecomputing is provided and some case studies of complex services are provided.

About the Speaker: Dr. Zhaohui Wuis a Qiushi Professor of Zhejiang University and the director of theinstitute of Computer System and Engineering. He is the committee chair of National

S&T innovation Plan on Modern Service industry (MSCI) and the DistinguishedYoung Scholar of China National Science Foundation (NSFC). He is the director of

MOEs Research Center of intelligence Science and Technique and the head of MOEsR&D Center of High-Performance Embedded Computing. He is the Standing Memberand a fellow of the China Computer Federation (CCF). His research interests includeService Computing and intelligent systems. Dr. Wu has authored 9 books, more than

200 refereed papers and over 100 invention patents, as well as 2 national S&T progressprize II. He is the founding editor-in-chief of Elseviers Big Data Research Journal, the

associated editor of Chinese Journal of information on Traditional Chinese Medicineand the founder of three International conferences (ICESS, CPSCom and MSCI).


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IEEE 2014

ICWS/SCC/CLOUD/BigDataCongress/MS/SERVICES Plenary Panel Sessions

Plenary Panel 1: The Next Computing Platform and Cloud Computing

Standards (SERVICES2014-7007)(06/28 Saturday, 16:45-18:00; Alaska Ballroom)

Moderator:Stephen L. Diamond, Chair, IEEE Cloud Computing Initiative, General Manager, IndustryStandards Office and Global Standards Officer, EMC

Panelists:Joe Weinman, Chair of the IEEE Intercloud Testbed executive committeeJoel J. Fleck II, Senior Standards Architect, HP

John Messina, Senior Member of the Cloud Computing Project, NIST

Abstract:In only a few years, cloud computing has disrupted computing, impacting everything from governments,supercomputers, service providers, enterprise data centers, small businesses, to individual consumers. Enabledby the cloud, big data analytics has disrupted enterprises by giving managers unprecedented insight into theirbusiness. This next platform of computing, building on cloud computing, big data, mobile, social networking,the Internet of Things, and cyber-physical systems, will compose an infrastructure encompassing billions ofusers, millions of applications, exabytes of data creation per day, and ultimately hundreds of billions ofconnected things. In parallel many standards organizations are engaged in the development of cloud computingstandards. This panel will examine elements of the cloud standards landscape and discuss directions and gaps.In addition, we will provide an update on the next phase of the IEEE Cloud Computing Initiative.

About the Moderator:

Stephen L. Diamond is Global Standards Officer and General Manager of the Industry StandardsOffice at EMC Corporation. He chairs the IEEE Cloud Computing Initiative and the IEEE CloudComputing Standards Committee. Steve has 30 years of senior management experience insemiconductors, software, systems, and standards. Prior to EMC, he was Director of IntercloudComputing at Cisco, where he built what was at the time the largest AWS-compatible cloud outside ofAmazon. Before that he was Vice President of Marketing at Equator Technologies, a digital signal

processing semiconductor startup. Steve has authored more than 20 technical publications. He was the2003 President of IEEE Computer Society and twice served on the IEEE Board of Directors. Steve wasawarded the IEEE Richard E. Merwin Medal in 2014 and the IEEE Third Millennium Medal in 2000.

About the Panelists:Joe Weinman is currently the chair of the IEEE Intercloud Testbed executive committee, as well asthe author of Cloudonomics: The Business Value of Cloud Computing (Wiley, 2012), and theforthcoming Digital Disciplines, which focuses on the intersection of IT and business strategy. He is aformer executive with Bell Labs, AT&T, HP, and Telx, and has been awarded 20 U.S. and

International patents in areas including pseudoternary line coding, Monte Carlo simulation, distributedstorage architectures, wireless and IP networks, and homomorphic encryption. He has a B.S. inComputer Science from Cornell University, an M.S. in Computer Science from the University ofWisconsin-Madison, and has completed executive education at the International Institute forManagement Development in Lausanne, Switzerland.

Joel J. Fleck IIs primary research and standards focus is adaptive management of distributed systemsand policy based management. Prior to joining Hewlett-Packard, he spent 16 years at Bell Laboratoriesand Bell Communications Research researching distributed management systems, multimedia networksand automated test systems to validate digital communications systems, and at Stochos, Inc. as asoftware architect and designer. Joel is a frequent speaker at conferences, has published numerous

papers on the subject of distributed architectures, model-driven architectures and management ofdistributed architectures and serves on the editorial board of several major journals relating to policy-


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based and next generation management. Joel serves on the Board of Directors and in lead executive positions for a numberof International standards bodies. Joel graduated from the University of Michigan with a MS in Industrial and OperationsEngineering and the University of Vermont with a BS in Computer Science. He is Distinguished Fellow of theTeleManagement Forum.

John Messina is a senior member of the Cloud Computing (CC) Project at the National Institute ofStandards and Technology (NIST). He holds a M.S. in Computer Science and B.S. in Physics and has

been working at NIST as computer scientist since 1998. He has a distinguished record of scientificaccomplishments, such as publications and industry presentations, and has received several awards,including NISTs Edward Bennett Rosa Award and the US Department of Commerces Bronze Medal.Having spent the last few years helping developing data dictionaries and data exchange standards for theUS Electronics Industry, he has been co-leading the NIST CC Reference Architecture working group. His

particular focus has been on leading efforts to create Cloud Computing Ontologies and varioustaxonomies.

Plenary Panel 2: Real-Time Big Data (SERVICES2014-7008)(06/29 Sunday, 16:00-17:15; Alaska Ballroom)

Moderator:Tony Shan, Chief TechnologistPanelists:

Eddie Satterly, CTO of CSC BD&AHemant Jain, Roger L. Fitzsimonds Distinguished Scholar and Professor of Information Technology

Management, University of Wisconsin-MilwaukeeJrg Bienert, CTO of ParStreamSrini Srinivasan, Co-founder and VP of Aerospike

Abstract:Real-time big data represents a convergence of science, engineering, and technology disciplines to collect,transform, store, process, analyze, and search big data in real time. Analytical processes that used to run longhours or days are now reduced by an order of magnitude to fractions of seconds. Traditional analytics areusually a process for generating reports from structured data retrieved from a traditional data warehouse. Real-

time big data takes it to the next level to drive business values by generating insights or recommendations fromdifferent sources of structured, semi-structured, and unstructured data in real time.

The trend is towards faster, intelligent, highly automated, cost-effective, and high-quality processing of data thatproduces insights quickly and offer specific recommendations in the right context, resulting in greater sales andhigher profits. Despite recent progress in the high-performance systems like trading and online advertisements,there are still a number of issues, barriers, pitfalls, and challenges in this maturing space. The industry gurus andfield practitioners on this panel will share their perspectives, experience and advice with forward-thinking viewsand practical forecasts.

About the Moderator: Tony Shanis a renowned thought leader and innovative visionary with decadesof field experience and guru-level expertise on cutting-edge enterprise computing technologies. He hasdirected and advised the pragmatic lifecycle design of large-scale award-winning distributed systems ondiverse platforms in Fortune 500 companies and public sector organizations like IBM, Apple, Cisco andBank of America. He is a regular speaker and organizer in preeminent conferences, a book author, aneditor/editorial advisory board member of IT research journals, and a founder of several user groups andforums.

About the Panelists:

Eddie Satterly has served in a variety of roles including developer, engineer, architect and CTOover his 25 year career. He spent the early part of his career working with globalTelecommunications companies leveraging big data before the term existed. His current role is CTOof CSC Big Data & Analytics where he is helping customers to adopt BD&A solutions and driveinternal advancement through R&D and constant review of available OSS options. More recently heheld the title of Chief Evangelist for Splunk where he drove the Big Data strategy that led toshipping of Hunk and was the public face in the community. Before that he was able to revolutionize


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the way a leading online travel agency delivers their core web applications using a combination of highly scalable andflexible, best in breed data tools. He also currently serves as a member of the Apache Cassandra MVP board and on theadvisory boards of 3 startups. Eddie has done guest lectures at Universities and presents at several conferences andsymposiums yearly.

Hemant Jain is serving as interim director of Biomedical and Health Informatics Research Institute. Hespecializes in information system agility through web services, service oriented architecture, component

based development, real time enterprises and health care informatics. He is on the Executive AdvisoryBoard of IEEE Transactions on Services Computing and is Associate Editor of Journal of AIS.Additionally, Hemant serves on the editorial board of a number of other highly regarded Journals. Hereceived his Ph. D. in information system for Lehigh University, an M. Tech form IIT Kharagpur and B. E.from University of Indore India.

Jrg Bienert is Co-Founder of ParStream, the fastest real-time database for Big Data Analytics (columnar-store, SQL, in-Memory, shared nothing architecture). Before ParStream he founded Empulse, an ITconsultancy and was COO and Head of Turnaround Team at Framfab, an internet agency. As Manager ofStrategic Consulting Business for Telcos at Accenture Germany, he met Michael Hummel. Jrg Bienert

began his career as Head of International IT Project Management at Gerling Insurance. He holds degrees in

computer science and electrical engineering.

Srini Srinivasan has over 20 years of experience designing, developing and operating webscale infrastructures and holds over a dozen patents in database, internet, mobile and distributedsystem technologies. His career includes high-profile technical and executive managementroles at IBM, Liberate and Yahoo!. Srini has degrees in Computer Science from IIT Madras(B.Tech) and the University of Wisconsin-Madison (M.S. and Ph.D).

Plenary Panel 3: Services Computing: Time for the Seventh Inning Stretch(SERVICES2014-7009)

(06/30 Monday, 12:00-13:15; Alaska Ballroom)

Moderator:I-Ling Yen, University of Texas at Dallas, USAPanelists:

Michael Goul, Arizona State University, USALing Liu, Georgia Tech., USABhavani Thuraisingham, University of Texas at Dallas, USALiang-Jie (LJ) Zhang, Kingdee International Software Group Company Limited, China

Abstract:The IEEE Transactions on Services Computing is currently in its seventh year of existence. In the modernsports pastime of baseball, fans usually arise from the hard benches somewhere in the middle of the seventhinning to walk about, extend their arms and legs, and enjoy a moment to relax from the intensity of the game.Akin to a seventh inning stretch, in this panel, services computing leaders will provide their perspectives on the

first seven years of the Transactions, they will evaluate how far weve progressed in the field, and they willcatalyze your thoughts about what the next seven years might bring.

In 2008s Vol. 1, No. 1, Transactions Editor-in-Chief Liang-Jie (LJ) Zhang explained that the servicescomputing discipline addresses a research domain significantly different than what is addressed in similardisciplines such as Internet and networking, software development, databases and multimedia. He explainedthat the technology foundation is different, and the research target is to modernize the traditional software andservices industry while concomitantly creating new generation software and services. Is this still true today?LJ further discussed the status of the services computing body of knowledge with first-level concepts includingSOA, Web services, service lifecycles, bridging business and IT architectures, etc. Second- and third-levelbody of knowledge fine-grained research areas provide ample opportunities for advanced insight. Are these stillthe most important research opportunities?


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Our panelists will examine how far we come from Vol. 1, No. 1 of the Transactions. They will elaborate someof todays most challenging and promising research directions. Example questions that will be debated amongpanelists include the following: Where is service computing today and where is it going to be in the next 7 years

as a general field? What roles can and should the IEEE TSC play? What interesting research problems andchallenges do we face in service computing? The panelists are from multi-disciplinary areas in academia andindustry, including business management, computer science and information technology as well as applicationdomain scientists and engineers.

About the Moderator:I-Ling is a Professor in the Computer Science Department at the University of Texas, Dallas. Shereceived her BS degree from Tsing-Hua University, Taiwan, and her MS and PhD degrees fromthe University of Houston. Her research interests include service-oriented computing, cloudcomputing, and high assurance systems. Dr. Yen has served as program chair and general chairfor many conferences. Currently she is on the editorial boards of IEEE Transactions on ServiceComputing, Journal on Knowledge and Information Systems, and the International Journal on

Artificial Intelligence Tools.

About the Panelists:

Michael Goul is Professor and Chair of the Department of Information Systems, W.P. Carey School ofBusiness, Arizona State University. His research bridges services computing and analytics. He was Co-PIon grants from Intel and American Express at the intersection of these areas, and he recently authored a caseon eBays approach to experimentation that relies on a multi-tenant, self-service data warehouseinfrastructure. His work in services computing led to a one-year appointment as a Distinguished UniversityScholar at the Clinton School of Public Service. Goul is also on the research faculty of the W.P. CareySchools Center for Services Leadership.

Ling Liuis a Professor in the College of Computing at Georgia Institute of Technology. There she directsthe Distributed Data Intensive Systems Lab, working on systems performance, availability, security and

privacy in data intensive systems, ranging from service oriented computing and architectures, big datasystems and technology, cloud computing, social computing, mobile services, to Internet systems and

services. Professor Liu has published over 300 international journal and conference articles, and herresearch group has produced a number of open source software systems. She is a recipient of the IEEEComputer Society Technical Achievement Award in 2012, an Outstanding Doctoral Thesis Advisor award

from Georgia Institute of Technology and numerous best paper awards, including ICDCS, WWW, ICWS, IEEE Cloud. Inaddition to services as General chair and PC Chair of numerous IEEE and ACM conferences, Professor Liu has served onthe editorial boards of many international journals. Currently Professor Liu is the Editor in Chief of the IEEE Transactionson Service Computing and a member of the steering committee of IEEE International Conference on Data Engineering(ICDE). Professor Liu's current research is primarily sponsored by NSF, IBM and Intel.

Bhavani Thuraisingham is the Louis A. Beecherl, Jr. DistinguishedProfessor in the Erik Jonsson School ofEngineering and Computer Science at the University of Texas, Dallas (UTD) and the executive director ofUTDs Cyber Security Research and Education Institute. Her current research is on integrating cybersecurity, cloud computing and big data analytics. Prior to joining UTD she worked at the MITRECorporation for 16 years including a three year stint as a Program Director at the NSF. She initiated theData and Applications Security program at NSF and was part of the Cyber Trust theme. Prior to MITRE,

she worked for the commercial industry for six years. She is the recipient of numerous awards including the IEEE CS 1997Technical Achievement Award, the ACM SIGSAC 2010 Outstanding Contributions Award, and a 2013 IBM FacultyAward. She is a Fellow of the IEEE, the AAAS and the British Computer Society. She has published mover than 100 journalarticles, more than 200 conference papers and 12 books and has delivered more than 100 keynote and invited addresses.

Liang-Jie (LJ) Zhang is Senior Vice President, Chief Scientist & Director of Research at KingdeeInternational Software Group Company Limited. Prior to joining Kingdee, he was a Research StaffMember and Program Manager at IBM Thomas J. Watson Research Center. Dr. Zhang has publishedmore than 160 technical papers in journals, book chapters, and conference proceedings. He has 50 granted

patents. He chaired the IEEE Computer Society's Technical Committee on Services Computing from 2003to 2011. He also chaired the Services Computing Professional Interest Community at IBM Research from2004 to 2006. Dr. Zhang has served as the Editor-in-Chief of the International Journal of Web Services


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Research since 2003 and was the founding Editor-in-Chief of IEEE Transactions on Services Computing. He was elected asan IEEE Fellow in 2011, and in the same year won the Technical Achievement Award "for pioneering contributions toApplication Design Techniques in Services Computing" from IEEE Computer Society.

Plenary Panel 4: Mobile Services: Trends and Challenges (SERVICES2014-7010)(06/30 Monday, 16:00-17:30; Alaska Ballroom)

Moderator:Steve Yau, Arizona State University, USA

Panelists:Rong Chang, IBM Research Center, USA and ChinaMin Luo, Huawei, USAMichael Melliar-Smith, University of California Santa Barbara, USANimish Radia, Ericsson, USA

Abstract:Innovation in services computing technologies is being driven by the need for high-value business services,

frequently involving the users, their environments, and their academic, commercial and industrial activities.Some important trends in this global metamorphosis are the mobile cloud, wearable technology and the Internetof Things.

Market research data on the impact of the changes include, for example, 15 billion devices of more than 200types will be communicating over the Internet by 2015, and the Internet of Things will reach $4.5 trillion by2020. Mobile services have broadened rapidly from information sharing to the management and optimizationof cyber-physical activities. They not only enable just-in-time information distribution among human users andsmart devices, but they also provide big data analytics and location-based services. On the other hand, as weincreasingly trust and use these mobile services, we have to find effective approaches to mitigate potentialdamages of service failures through fault tolerance mechanisms. The boundaries between automation andcontrol pervade our daily lives. Do we want decisions to be made and actions to be taken automatically withoutour being aware of them, or do we want to have explicit knowledge and control over them? If it is the former,we need to avoid the effect of being a big brother. How do we do that, while achieving commercial benefits?

If it is the latter, we have a "last foot" problem. How can we improve the human interface and our interactionswith the technology?

Based on market research data and ongoing research and development, this panel will provide variousviewpoints addressing major technical challenges in the area of mobile services that must be resolved in a user-friendly and cost-effective manner.

About the Moderator:Stephen S. Yau is a Professor of Computer Science and Engineering and the Director of the InformationAssurance Center at Arizona State University. He served as the chair of the Department of Computer Scienceand Engineering at ASU and was previously on the faculties of Northwestern University, Evanston, Illinoisand University of Florida. He received the M.S. and Ph.D. degrees from the University of Illinois, Urbana,and the B.S. degree from National Taiwan University, all in electrical engineering. Yau served as the

president of the IEEE Computer Society and on the Boards of Directors of the IEEE and the ComputingResearch Association. He also served as the editor-in-chief of IEEE Computer, and general chairs or co-chairs of a numberof major international conferences, including this IEEE World Congress on Services. He received the Tsutomu Kanai Awardand Richard E. Merwin Award of the IEEE Computer Society, the IEEE Centennial Award, and Third Millennium Medal,and the Outstanding Contributions Award of the Chinese Computer Federation. Yau is a Life Fellow of the IEEE and aFellow of the AAAS. His current research interests include cloud and service-based systems, cyber security, trustworthycomputing, software engineering, mobile ad-hoc networks and ubiquitous computing.

About the Panelists:Rong N. Chang is a senior researcher at IBM Research leading a cross-organization team advancing thetechnologies for IoT-enabled industry cloud services. He received his Ph.D. degree in Computer Science andEngineering from the University of Michigan, Ann Arbor and his B.S. degree in Computer Engineering withhonors from the National Chiao Tung University, Taiwan. Before joining IBM, he was with BellCommunications Research. At IBM, his research encompasses the areas of cloud computing, ITinfrastructure, and business service and process management. Chang is the editor-in-chief of the


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International Journal of Cloud Computing and an associate editor of the IEEE Transactions on Services Computing and theInternational Journal of Services Computing. He holds more than 20 patents, and has published more than 40 refereedtechnical papers. Chang is Administrator of the 2014 Sino-American Technology and Engineering Conference. He is anACM Distinguished Member, an IEEE Senior Member.

Min Luois currently the Head and Chief Architect of the Advanced Networking at Huaweis Shannon (IT)Lab, leading the research and development in Software Defined Networking (SDN) and other futurenetworking initiatives. He served as Chief/Executive Architect for IBM SWGs Stretegy and Technology,Global Business Solution Center, Industry Solutions, and Center of Excellence for Enterprise Architectureand SOA for more than 11 years. He also worked as Senior Operations Research Analyst, Senior Managerand Director of Transportation Network Planning and Technologies for Conrail and Norfolk Southern Corp.

for 7 Years. His expertise is in next generation SDN, enterprise architecture and information systems, whole life cyclesoftware application and product development, business intelligence, business process optimization, Model/business-drivenarchitecture and development (MDA-D), and component/object-oriented technologies. He obtained his Ph.D. in ElectricalEngineering from Georgia Institute of Technology in 1992. He was awarded the Distinguished Lead/Chief Architect fromthe Open Group in 2007.

Michael Melliar-Smith is a Professor in the Department of Electrical and Computer Engineering at theUniversity of California, Santa Barbara. His research interests span the fields of distributed systems andapplications, network architectures and protocols, and fault tolerance. He has authored or coauthoredmore than 290 publications in computer science and engineering, and he holds 12 patents. At UC SantaBarbara, he has served as PI for numerous funded research projects from DARPA, AFOSR, NSF, UCMicro and UC Discovery. Previously, he worked at SRI International in Menlo Park, and at the

University of Newcastle upon Tyne and GEC Computers in England. As Senior Computer Scientist and Program Director atSRI, he worked on the SIFT computer for aircraft flight control and the EHDM system for formal specification andverification. At GEC Computers, he was the Principal Designer of the GEC 4080, which won the Queens Award forInnovation. At the University of Newcastle upon Tyne, he invented the definitions of fault, error and failure, as well as therecovery block method for fault tolerance. Professor Melliar-Smith has served as Technical Chair and General Chair of theIEEE International Conference on Mobile Services in 2013 and 2014, respectively. He received the Ph.D. in ComputerScience from the University of Cambridge, England.

Nimish Radia has more than 20 years of experience in the IT, mobile, telecom and finance industry witha strong combination of technology expertise and business acumen. Dr. Radia has proven leadership in

transforming technology into multi-million dollar profitable vertical and horizontal solutions. Currently,he is Director of Research and Innovation leading Ericsson's efforts in Silicon Valley for next generationservices and software in areas such as big data, social computing, and contextual user-centered solutionsfor networked society challenges, such as healthcare, public safety, media, and smart energy. Before

joining Ericsson, he was Advanced Technology Executive at Sun for US Communications, Media, and Entertainment Sales.In that role, he led a cross-company R&D team that was accountable for creating revenue-generating solutions. Prior to Sun,he was a Senior Member of the IBM Research and Advanced Software Technology Group driving R&D projects withcustomers globally. Dr. Radia holds 8 patents and more than 15 invention disclosures and industry publications.

Plenary Panel 5: Enablement for Cloud Computing (SERVICES2014-7011)(07/01 Tuesday, 12:00-13:15; Alaska Ballroom)

Moderator:Lorraine Herger, IBM Research, USA

Panelists:Wu Chou, Huawei Shannon IT Lab, USACarl Kesselman, University of Southern California, USAMarco Netto, IBM Research, BrazilAlan Sussman, University of Maryland, USA

Abstract:Cloud computing is now more than an emerging platform but rather is a maturing platform for delivering ITservices and for hosting solutions. Enablement for cloud computing consists of many technologies of manylayers and many dimensions, including the development environment for born-in-cloud applications, migrationtools for existing applications, elastic provisioning of cloud services, funding and charge-back models, andstandardization efforts.


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IEEE 2014

ICWS/SCC/CLOUD/BigDataCongress/MS/SERVICES Tutorials

Tutorial 1: Play with Streams: Real-time Data Processing Architecture(SERVICES2014-7013)Tianjian Chen, Architecture R&D Team, Baidu inc., China

(06/27 Friday, 9:45-14:00; Aleutian)

Abstract:The stream processing architecture is a popular component of todays big data architecture. It cansharply reduce the data process latency and enable many applications that depend on high capacity online ornear-line computation. in this tutorial, we present the methodology of how to design and implement a streamprocessing system from scratch. The key design point of the stream processing architecture will be illustratedbased on the lessons that we learn from several real world projects during the past 3 years. The architectureevolution of a massive stream computing platform will be a valuable reference to similar projects.

The reference design that we provided in this tutorial addresses issues of scalability, availability, manageabilityand programmability on different layers. Its layered design enables the system developer to quickly modify anylayer according to the demand of applications and generate minimal side effects. in the case studies, we willpresent some interesting applications of real-time stream processing, including a web crawler, an onlinemachine learning system and a hybrid application with Hadoop Map Reduce.

About the Speaker: Tianjian Chen is a senior architect in the basic technology department at Baiduincorporation, a leading internet company in China. He is the chief architect of the Baidus recommenderengine, which serves half billion Chinese users. Tianjian and his R&D team focus on large scale datainfrastructures and have particular interest in the cost efficiency and the connectivity challenges of cloudcomputing systems.

Tutorial 2: Countries and Cities through the Prism of Big Data of Digital FootprintsCreated By Human Activity (SERVICES2014-7014)

Stanislav Sobolevsky, MIT, USA(06/27 Friday, 9:45-14:00; Alaska)

Abstract: The past few decades saw a technological revolution that resulted in the broad penetration of digitaltechnologies in everyday life. More and more aspects of human activity now leave digital traces behind them,thus increasing production of big data related to human mobility, interactions or other types of behavior such asshopping. Various datasets from the last 5-7 years - landline and cell phone call records, public transportationrecords, vehicle GPS traces, bank card transactions, digital social media (Twitter, Flickr, Foursquare) arenow available for research purposes, creating tremendous opportunities for new solutions to well-knownresearch and operational problems in different fields including human geography, urban planning, economics as

well as other areas of social science. To present days, those fields are largely relying on different sources ofcensus data and surveys. Considered as a whole, the above new big data sources and their applicationtechniques could be summarized as a novel concept of the digital census. Opposed to traditional survey-basedone, it possesses substantial potential advantages such as lower cost, instant availability, objectiveness andaccuracy.

In this tutorial, we present modern techniques for the application of said digital census. They allow a betterunderstanding of present countries and cities as well as the design of innovative concepts for the future ones.We focus on important applications such as regional delineation, city definition, human country- and city-scalemobility modeling, transportation optimization, and certain aspects of urban sustainability. Examples of datavisualization tools, as means to explore data potential, are also considered. Together with the advances, newmethodologies and further potential of the approach, we focus on the challenges, biases and limitations typicallyintroduced by big data of human activity, pointing out to ways of addressing them.


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About the Speaker: Dr. Stanislav Sobolevsky leads the Network and Society area in the SENSEable CityLaboratory at Massachusetts Institute of Technology since 2012, working on studying laws and regularities ofhuman behavior in urban context through big data analysis. Holds Ph.D. (since 1999) and Doctor of Science(habilitation in C.I.S. countries academy; since 2008) degrees in Mathematics. Previously Dr. Sobolevsky was a

Professor and Director of the Institute of Lifelong Education at Belarusian State University. He authored a monograph,several textbooks and book chapters and over 50 peer-reviewed papers in pure and applied mathematics as well as big dataanalysis. Dr. Sobolevskys current research interests cover network science, big data analysis, modeling of complex systemsas well as the theory of differential equations.

Tutorial 3: NoSQL Data Stores in Internet-scale Computing (SERVICES2014-7015)Wei Tan, IBM T.J. Watson Research Center, USA

(06/27 Friday, 14:10-17:30; Aleutian)

Abstract: NoSQL (Not Only SQL) as a collective name of data stores that neither use relational model norexpose SQL interfaces, emerges recently and gains much popularity in supporting Internet-scale applications.These stores provide simple operations compared to those offered by relational databases, but prevail in flexibleschema, elasticity, and fine-grained control on consistency. Examples of NoSQL include Dynamo, BigTable,Cassandra, HBase and MongoDB. This tutorial introduces NoSQL in a why-what-how approach. Why: we firstinvestigate the motivations of having NoSQL: flexible schema, scale-out capability on commodity hardware,fine-grained control on consistency/availability, and exploration of new hardware. What: we then survey manyNoSQL stores including those developed by software companies and open-source offerings. How: afterward,we make a deep dive into the key aspects enabling NoSQL stores to achieve their mission. These aspectsinclude data model (key/value, document, graph, tabular, etc), storage model (tree, sequence file, etc), datapartition (hash, range, hybrid, etc), consistency/availability, exploration of advanced hardware and workloadmanagement. Especially, throughout the tutorial we will use existing NoSQL stores as examples to illustratehow NoSQL technologies address the issues that are not solved by relational databases.

About the Speaker:Dr. Wei Tan is a research staff member in IBM T. J. Watson Research Center, YorktownHeights, NY, USA. From 2008 to 2010 he was a researcher at Computation Institute, University of Chicago andArgonne National Laboratory, USA. At that time he was the technical lead of the caBIG workflow system. Hisresearch interests include NoSQL, big data, cloud computing, service-oriented architecture, business andscientific workflows, and Petri nets. He has published over 50 journal and conference papers, and a monograph

Business and Scientific Workflows: A Web Service-Oriented Approach (272 pages, Wiley- IEEE Press). He is anassociate editor of IEEE Transactions on Automation Science and Engineering. He has served in program committee ofmany conferences and co-chaired several workshops. He received the Best Paper Award from IEEE InternationalConference on Services Computing (2011), Pacesetter Award from Argonne National Laboratory (2010), and caBIGTeamwork Award from the National Institute of Health (2008). He is member of ACM and senior member of IEEE.

Tutorial 4: Big Data Science: Fundamental, Techniques, and Challenges (SERVICES2014-7016)

Incheon Paik, Neil Y. YenUniversity of Aizu, Japan

(06/27 Friday, 14:10-17:30; Alaska)

Abstract: Recently, there have been very large and complex data sets from nature, sensors, social networks,enterprises increasingly based on high speed computers and networks together. Big data is the term for acollection of the data sets that it becomes difficult to process using on-hand database management tools ortraditional data processing applications. Data science is a novel term that is often used interchangeably withcompetitive intelligence or business analytics, and it seeks to use all available and relevant data to effectivelytell a story that can be easily understood by non-practitioners. Data science based on the big data is expected toprovide very potent prediction and analysis for information and knowledge of various fields of researches andbusinesses from the new data set. This tutorial is to give fundamental techniques for big data processing andsome view point to accomplish a business target. Business modeling and data science process on big data,statistical analysis, emerging data mining techniques, and how to use the technologies to achieve the businessgoal will be introduced by and large.

About the speakers: Dr. Incheon Paik received the M.E. and Ph.D. degrees in Electronics Engineering from Korea


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University in 1987 and 1992, respectively. During 1993-2000, he worked as a senior associate professor inSoonchunhyang University, Korea. From 1996 to 1998, he was a visiting researcher of State Key Laboratory,Beihang University, Beijing, China. Also he leaded the Electronic Commerce S/W Research Center (now,ITRC) funded by the Ministry of Information & Communication during 1999-2001. Now he is an associate

professor in the University of Aizu, Japan. Research interests include Semantic Web, Web Services and TheirComposition, Web Data Mining, Awareness Computing, Security for e-Business, Agents on Semantic Web,

and Big Data Science. He served several conferences as a program chair and program committee member for numerousInternational conferences. He serves as an editor of journals of JIPS and IEICE. He is a member of IEEE, IEICE and IPSJ.

Dr. Neil Y. Yen is an Associate Professor at the University of Aizu, Japan. Dr. Yen received doctorates in Human Sciences(major in Human Informatics) at Waseda University, Japan, and in Engineering (major in Computer Science) at TamkangUniversity, Taiwan in March and June 2012 respectively. His doctor degree at Waseda University was funded by the JSPS(Japan Society for the Promotion of Science) under RONPAKU program. In academic research career, Dr. Yen has been

engaged in the interdisciplinary realms of research, and his research interests are now primarily in the scope ofbig data science, computational intelligence, and human-centered computing. His recent publications can befound on over 60 refereed journals/conferences/books, including 5 on ACM/IEEE Transactions and over 15

journals indexed by SCI/SCIE. Dr. Yen has actively involved himself in the International activities, includingeditorial works in journals and books, society services in academic conferences sponsored by IEEE/ACM, etc.,and devoted himself to discover advanced and interesting research directions. He is now a member of IEEE

(CS, SMCS, CIS), ACM (SIGCHI, SIGKDD, SIGMM), IPSJ, and IEICE.

Tutorial 5: Big Data Proficiency (SERVICES2014-7017)Tony Shan, USA

(06/27 Friday, 9:45-14:00; Denali)

Abstract: According to McKinsey and Co., a shortage of 50-60% of qualified Big Data resources is predictedfor companies trying to locate the required expertise within the U.S. The resource deficit is certainly a bigproblem hindering the Big Data adoption and advancement. But the bigger problem is what new skills areneeded, what difference exists, and how the gap can be quickly closed in the new era.

This tutorial presents the Big Data Proficiency, with a focus on the drivers, concept, values, means, buildout andevolution of Big Data competency. We start with why the current state of the art and the imperatives for new

skillsets in the Big Data space. Then we define the concept of Big Data competency as the core abilitiesrequired in the implementations of Big Data initiatives. Further, we specify various roles that have differentresponsibilities in the Big Data project management. The desired skillsets are formulated for all these new andexpanded roles. Afterwards, we map the roles to the end-to-end Big Data lifecycle model to illustrate the keytasks and deliverables they are accountable for. Subsequently, we prescribe a few patterns to hire, train, andretool resources to build a solid Big Data CoE, followed by 4 organizational models for effective governance.Moreover, we walk through a methodical framework for Big Data solutioning in a detailed step-by-step guide toBig Data problem solving, coupled with the core architecture aptitude. In addition, the growth ladders andlearning paths are discussed as well, along with the best practices and lessons learned from the real-world in BigData engagements.

About the Speaker: Tony Shan is a renowned thought leader and innovative visionary with decades offield experience and guru-level expertise on cutting-edge enterprise computing technologies. He has directedand advised the pragmatic lifecycle design of large-scale award-winning distributed systems on diverse

platforms in Fortune 500 companies and public sector organizations like IBM, Apple, Cisco and Bank ofAmerica. He is a regular speaker and organizer in preeminent conferences, a book author, an editor/editorialadvisory board member of IT research journals, and a founder of several user groups and forums.

Tutorial 6: Big Data Analytic Opportunities and Challenges (SERVICES2014-7018)Anup Kumer, University of Louisville, USA

(07/01 Tuesday, 13:30-17:00; Katmai)

Abstract: In todays world data is generated by network sensors, Big Data is changing the way we store thedata, analyze the data and build knowledge from the analysis. The tutorial will include practical applications,appropriate tools and technology to leverage Big Data Analytics. It will also discuss Hadoop landscape for BigData processing. Big Data application in healthcare systems both in terms of patient care and cost will be


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addressed. A framework of how Big Data Analytics can arm healthcare players and providers with practicalknowledge to make better decisions will also be discussed.

High Level Tutorial Outline:

Introduction to Big Data and Big Data Analytics Storage structures for Big data Potential for Big data analytics Hadoop spectrum and MapReduce framework Tools for Big data analytics Delivering Big data analytics benefits Big data analytics for Healthcare Challenges for Big Data Analytics What to expect going forward

About the Speaker: Anup Kumar ([email protected]) is currently a Professor of CECS Department at theUniversity of Louisville. He is also the Director of Mobile Information Network and Distributed Systems

(MINDS) Lab. He has given tutorials in the past at many IEEE International conferences and at SCC-2005/2006. His research interests include web services, wireless networks, distributed system modelling, andsimulation. He has co-edited a book titled, Handbook of Mobile Systems: Applications and Services

published by CRC press in 2012. He is an Associate Editor of Internal Journal of Web Services Research. Hewas an Associate Editor of IEEE Transactions on Services Computing from 2008-2012. He was Associate Editor ofInternational Society of Computers and Their Application Journal from 2004-2008 and of International Journal ofEngineering Design and Automation from 1995-1998. He was a member of IEEE Distinguished Visitor Program (2006-2008). He was the Chair of IEEE Computer Society Technical committee on Simulation (TCSIM) (2004-2007). He has

published and presented over 200 papers. He has served on many conference program and organizing committees such asCyberC-2013-2009, IEEE ISCC 2007, IEEE ICSW-2006, IEEE MASS-2005, IEEE SCC-2005, IEEE ICWS-2005, CIT-2005, IEEE MASCOTS, ADCOM 97 and 98. He has also edited special issues in IEEE Internet Magazine, and InternationalJournal on Computers and Operations Research.


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2014 IEEE Twenty First International

Conference on Web Services (ICWS 2014)

Research TrackResearch Session 1 Service Selection (06/28 Saturday, 8:30-9:30; Dillingham)Session Chair: Stephen Reiff-Marganiec, University of Leicester, UKPartial Selection: An Efficient Approach for Qos-Aware Web Service Composition (ICWS2014-1001)

Ying Chen, Jiwei Huang, Chuang Lin(Tsinghua University, China)Pruning Based Service Selection Approach under Qos and Temporal Constraints (ICWS2014-1002)

Ikbel Guidara, Nawal Guermouche, Tarak Chaari, Said Tazi, Mohamed Jmaiel (Univ de Toulouse, France; Universityof Sfax, Tunisia)Personalized Decision Making for Qos-Based Service Selection (ICWS2014-1003)

Muhammad Suleman Saleem, Chen Ding, Xumin Liu, Chi-Hung Chi (Ryerson University; Rochester institute of

Technology, USA)

Research Session 2 Service Recommendation (06/28 Saturday, 13:00-14:00; Dillingham)Session Chair: Mohamed Quafafou, Domaine Universitaire de Saint-Jrme, FranceTime-Aware Service Recommendation for Mashup Creation in an Evolving Service Ecosystem (ICWS2014-1004)

Yang Zhong, Yushun Fan, Keman Huang, Wei Tan, Jia Zhang (Tsinghua University, China; IBM T.J. Watson ResearchCenter, USA; Carnegie Mellon University, USAA Time-Aware and Data Sparsity Tolerant Approach for Web Service Recommendation (ICWS2014-1005)

Yan Hu, Qimin Peng, Xiaohui Hu (Chinese Academy of Sciences, China)A Graph-Based Data Model for API Ecosystem insights(ICWS2014-1006)

Erik Wittern, Jim Laredo, Maja Vukovic, Vinod Muthusamy, Aleksander Slominski(IBM T.J. Watson Research Center,USA)

Research Session 3 Service Quality Control(06/28 Saturday, 14:10-15:10; Dillingham)

Session Chair: Stephen Crago, University of Southern California, USAVerifying Multiagent-Based Web Service Compositions Regulated By Commitment Protocols (ICWS2014-1007)

Warda El Kholy, Mohamed El Menshawy, Jamal Bentahar, Hongyang Qu, Rachida Dssouli (Concordia University,Canada)Quality of Experience: What End-Users Say about Web Services? (ICWS2014-1008)

Bipin Upadhyaya, Ying Zou, Iman Keivanloo, Joanna Ng(Queen's University, Canada)Inferring Data Contract for Web-Based API (ICWS2014-1009)

Chushu Gao, Jun Wei, Hua Zhong, Tao Huang (Chinese Academy of Sciences, China)

Research Session 4 Context-Aware Service Selection (06/28 Saturday, 15:30-16:30; Dillingham)Session Chair: Yushun Fan, Tsinghua University, ChinaAutomatic Propagation of User Inputs in Service Composition for End-Users (ICWS2014-1010)

Shaohua Wang, Bipin Upadhyaya, Ying Zou, Iman Keivanloo, Joanna Ng, Tinny Ng(Queen's Univerisity; IBM Canada

CAS Research, Canada)Context-Aware Cloud Service Selection Based On Comparison and Aggregation of User Subjective Assessmentand Objective Performance Assessment (ICWS2014-1011)

Lie Qu, Yan Wang, Mehmet A. Orgun, Ling Liu, Athman Bouguettaya (Macquarie University, Australia; Georgia Tech;RMIT University, USA)Context Aware Filtering and Visualization of Web Service Clusters (ICWS2014-1012)

Banage Thenna Gedara Samantha Kumara, Incheon Paik, Hiroki Ohashi, Yuichi Yaguchi, Wuhui Chen (University ofAizu, Japan)

Research Session 5 Novel Service Applications (06/29 Sunday, 8:30-9:30; Dillingham)Session Chair: Brian Blake, University of Miami, USALandslide Detection Service Based on Composition of Physical and Social information Services(ICWS2014-1013)


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Aibek Musaev, De Wang, Chien-An Cho, Calton Pu (Georgia institute of Technology, USA)A Web Service for Scholarly Big Data information Extraction(ICWS2014-1014)

Kyle Williams, Lichi Li, Madian Khabsa, Jian Wu, Patrick C. Shih, C. Lee Giles(Penn State University, USA)Virtual Location-Based Services: Merging the Physical and Virtual World (ICWS2014-1015)

Christian Von Der Weth, Vinod Hegde, Manfred Hauswirth (National University of Ireland, Galway)

Research Session 6 Service Trust (06/29 Sunday, 12:00-13:00; Dillingham)Session Chair: Stephen S. Yau, Arizona State University, USAAn Efficient Multiple Trust Paths Finding Algorithm for Trustworthy Service Provider Selection in Real-TimeOnline Social Network Environments (ICWS2014-1016)

Guanfeng Liu, An Liu, Yan Wang, Lei Li (Soochow University; Macquarie University, Australia; HeFei University ofTechnology, China)A Model-Driven Approach for REST Compliant Services (ICWS2014-1017)

Florian Haupt, Dimka Karastoyanova, Frank Leymann, Benjamin Schroth (University of Stuttgart, Germany)Secure Web Service Composition with Untrusted Broker(ICWS2014-1018)

Barbara Carminati, Elena Ferrari, Ngoc Hong Tran (University of insubria at Como, Italy)

Research Session 7 Service Prediction (06/29 Sunday, 13:15-14:15; Dillingham)Session Chair: Xiaoqing (Frank) Liu, Missouri University of Science and Technology, USAIncorporating Invocation Time in Predicting Web Service QoS via Triadic Factorization(ICWS2014-1019)

Wancai Zhang, Hailong Sun, Xudong Liu, Xiaohui Guo (Beihang University, China)Leveraging Formal Concept Analysis with Topic Correlation for Service Clustering and Discovery(ICWS2014-1020)

Mustapha AZNAG, Mohamed QUAFAFOU, Zahi JARIR (Aix-Marseille University, France)Modelling and Predicting the Data Availability in Decentralized Online Social Networks (ICWS2014-1021)

Songling Fu, Ligang He, Xiangke Liao, Chenlin Huang, Kenli Li, Cheng Chang, Bo Gao (University of Warwick, UK;Hunan University, China)

Research Session 8 Service Provisioning (06/30 Monday, 8:30-9:30; Dillingham)Session Chair: Jianwei Yin, Zhejiang University, ChinaDelay-Aware Cost Optimization for Dynamic Resource Provisioning in Hybrid Clouds(ICWS2014-1022)

Song Li, Yangfan Zhou, Lei Jiao, Xinya Yan, Xin Wang, Michael R. Lyu (Fudan University, China; The ChineseUniversity of Hong Kong, China; University of Gttingen, Germany)Impacts of Pheromone Modification Strategies in Ant Colony for Data-intensive Service Provision(ICWS2014-1023)

Lijuan Wang, Jun Shen, Junzhou Luo (University of Wollongong, Australia; Southeast University, China)Learning Efficient Compositions for QoS-Aware Service Provisioning(ICWS2014-1024)

Ahmed Moustafa, Minjie Zhang (University of Wollongong, Australia)

Research Session 9 Workflows (06/30 Monday, 13:30-14:30; Dillingham)Session Chair: Dariusz Krl, AGH University of Science and Technology, PolandUnraveling and Learning Workflow Models From interleaved Event Logs(ICWS2014-1025)

Xumin Liu (Rochester institute of Technology, USA)Service Evolution Patterns(ICWS2014-1026)

Shuying Wang, Wilson Akio Higashino, Michael Hayes, Miriam Akemi Manabe Capretz (Western University, USA)SCKY: A Method for Reusing Service Process Fragments(ICWS2014-1027)

Rong Yang, Bing Li, Jian Wang, Lulu He, Xiaohui Cui (Wuhan University, China)

Research Session 10 Service Efficiency (06/30 Monday, 14:45-15:45; Dillingham)Session Chair: Abdelmounaam Rezgui, New Mexico Tech, USAWire-Speed Differential SOAP Encoding(ICWS2014-1028)

Kanak Agarwal (IBM, USA)Web Service Orchestration Topic Mining(ICWS2014-1029)

Victor W. Chu, Raymond K. Wong, Chi-Hung Chi, Patrick C.K. Hung (University of New South Wales, Australia;CSIRO, Australia; University of Ontario, Canada)Is XML-Based Test Case Prioritization for Validating WS-BPEL Evolution Effective in Both Average andAdverse Scenarios? (ICWS2014-1030)

Changjiang Jia, Lijun Mei, W.K. Chan, Y.T. Yu, T.H. Tse (City University of Hong Kong, China)


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Applications & Industry TrackApplications & Industry Session 1 IoT Services (06/28 Saturday, 8:30-9:30; Katmai)Session Chair: Xiaofei Xu, Harbin Institute of Technology, ChinaSpatio-Temporal Composition of Sensor Cloud Services (ICWS2014-1031)

Azadeh Ghari Neiat, Athman Bouguettaya, Timos Sellis, Zhen Ye (RMIT University, USA)TSaaaS: Time Series analytics as a service on IoT(ICWS2014-1032)

Xiaomin Xu, Sheng Huang, Yaoliang Chen, Kevin Browny, Inge Halilovicy, Wei Lu (IBM China Research Laboratory)SDN Northbound REST API with Efficient Caches(ICWS2014-1033)

Wei Zhou, Li Li, Wu Chou (Huawei, China)

Applications & Industry Session 2 Time-Aware Services Recommendation (06/28 Saturday, 13:00-14:00; Katmai)

Session Chair: Ruichong Zhang, Beihang University, ChinaTime-Aware Collaborative Filtering for QoS-Based Service Recommendation(ICWS2014-1034)

Chengyuan Yu, Huang LinpengShanghai Jiao Tong University, ChinaTime-aware Web Service Recommendations Using Implicit Feedback(ICWS2014-1035)

Gang Tian, Jian Wang, Keqing He, Patrick C.K. Hung, Chengai Sun (Wuhan University, China)Web Service Recommendation Based on Watchlist via Temporal and Tag Preference Fusion(ICWS2014-1036)

Xiuwei Zhang, Keqing He, Jian Wang, Chong Wang, Gang Tian, Jianxiao Liu (Wuhan University, China)

Applications & Industry Session 3 Services Recommendation (06/28 Saturday, 14:10-15:10; Katmai)Session Chair: Hamid R. Motahari Nezhad, IBM Almaden Research Center, USAA Novel Approach for API Recommendation in Mashup Development(ICWS2014-1037)

Chune Li, Richong Zhang, Jinpeng Huai, Hailong Sun (Beihang University, China)Location-based Hierarchical Matrix Factorization for Web Service Recommendation(ICWS2014-1038)

Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu (University of Hong Kong, China)Combining Global and Local Trust for Service Recommendation(ICWS2014-1039)

Mingdong Tang, Yu Xu, Jianxun Liu, Zibin Zheng, Xiaoqing (Frank) Liu (Hunan University; University of Hong Kong,China; Missouri University, USA)

Applications & Industry Session 4 Cloud-based Service Selection and Composition (06/28Saturday, 15:30-16:30; Katmai)

Session Chair: Michael Rung-Tsong Lyu, Chinese University of Hong Kong, ChinaA Hybrid Fuzzy Framework for Cloud Service Selection(ICWS2014-1040)

Le Sun, Hai Dong, Farookh Khadeer Hussain, Omar Khadeer Hussain, Jiangang Ma, Yanchun Zhang (VictoriaUniversity, Australia; RMIT University, Australia)Service Composition Pattern Generation for Cloud Migration: a Graph Similarity Analysis Approach(ICWS2014-1041)

Zhitao Wan, Fan Jing Meng, Jing Min Xu, Ping Wang (IBM Research; Peking University, China)Exploring Cloud Service Brokering from an interface Perspective(ICWS2014-1042)

Yucong Duan, Nanjangud C. Narendra, Wencai Du, Yongzhi Wang, Nianjun Zhou(Florida international University,USA; Hainan University, CHina; IBM T.J. Watson Research Center, USA)

Applications & Industry Session 5 Cloud Service QoS (06/29 Sunday, 8:30-9:30; Katmai)Session Chair: Karen Lu, Gemalto, USACutting Your Cloud Computing Cost for Deadline-Constrained Batch Jobs(ICWS2014-1043)

Min Yao, Peng Zhang, Yin Li, Jie Hu, Chuang Lin, Xiang-Yang Li (Tsinghua university, China)A Trust Evaluation Method for Cloud Service with Fluctuant QoS and Flexible SLA(ICWS2014-1044)

Lianyong Qi, Wanchun Dou, Jiancheng Ni, Xiaona Xia, Chunmei Ma, Jinfeng Liu (Nanjing University, China)Modeling Accountable Cloud Services(ICWS2014-1045)

Jun Zou, Yan Wang, Mehmet A. Orgun (Macquarie University, Australia)

Applications & Industry Session 6 Services Optimization (06/29 Sunday, 12:00-13:00; Katmai)Session Chair: Xuanzhe Liu, Peking University, China


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Towards Heuristic Optimization of Complex Service-based Workflows for Stochastic QoS Attributes(ICWS2014-1046)

Dieter Schuller, Melanie Siebenhaar, Ronny Hans, Olga Wenge, Ralf Steinmetz, Stefan Schulte (TechnischeUniversitt Darmstadt; Vienna University of Technology)Flexible Execution of Adaptable Composed Services (ICWS2014-1047)

Carlos Kamienski, Ernani Azevedo, Ramide Dantas, Djamel Sadok, Brje Ohlman (Federal University of ABC(UFABC) Brazil)Collaborative Web Service QoS Prediction on Unbalanced Data Distribution(ICWS2014-1048)

Wei Xiong, Bing Li, Lulu He, Mingming Chen, Jun Chen (Wuhan University, China)

Applications & Industry Session 7 Data-Oriented Services (06/29 Sunday, 13:15-14:15; Katmai)Session Chair: Varghese S. Jacob, University of Texas at Dallas, USAData Mining from NoSQL Document-Append Style Storages(ICWS2014-1049)

Richard K. Lomotey, Ralph Deters (University of Saskatchewan, Canada)Effectiveness Assessment of Solid-State Drive used in Big Data Services(ICWS2014-1050)

Wei Tan, Liana Fong, Yanbin Liu (IBM Watson Research Center, USA)Runtime Enforcement of Data-centric Properties for Concurrent Service-based Application(ICWS2014-1051)

Guoquan Wu, Jun Wei, Hua Zhong, Tao Huang (Chinese Academy of Sciences)

Applications & Industry Session 8 Service Verification (06/30 Monday, 8:30-9:30; Katmai)Session Chair: Xumin Liu, Rochester Institute of Technology, USAITWS: An Extensible Tool for interoperability Testing of Web Services (ICWS2014-1052)

Ivano Alessandro Elia, Nuno Laranjeiro, Marco Vieira (University of Coimbra)Web Services and Performance: for eBay Item Visibility Framework(ICWS2014-1053)

James Shen (eBay inc., USA)Measuring Credit of Web Service(ICWS2014-1054)

Bin Xu, Jiaxiang Ge, Tonglee Chung (Tsinghua University, China)

Applications & Industry Session 9 Services Composition 1(06/30 Monday, 13:30-14:30; Katmai)Session Chair: Frank Siqueira, Federal University of Santa Catarina, BrazilCategorial Link: REST Service Composition Based on Category Theory(ICWS2014-1055)

Li Li, Wu Chou (Huawei, China)Domain-aware Service Recommendation for Service Composition(ICWS2014-1056)

Bofei Xia, Yushun Fan, Cheng Wu, Keman Huang, Wei Tan, Jia Zhang, Bing Bai (Tsinghua University)Adaptive and Dynamic Service Composition via Multi-agent reinforcement learning(ICWS2014-1057)

Hongbing Wang, Qin Wu,Xin Chen,Qi Yu, Zibin Zheng, Athman Bouguettaya(The Chinese University of Hong Kong;Rochester institute of Technology, USA)

Applications & Industry Session 10 Services Composition 2 (06/30 Monday, 14:45-15:45; Katmai)Session Chair: Carlos Kamienski, Federal University of ABC, BrazilMagEl: A Magneto-Electric Effect-inspired Approach for Web Service Composition(ICWS2014-1058)

Tanveer Ahmed, Michael Mrissa, Abhishek Srivastava (Indian Institute of Technology Indore; Universite Lyon 1,France)Improved Genetic Algorithm based Approach for QoS Aware Web Service Composition (ICWS2014-1059)

A. Erdinc Yilmaz, Pinar Karagoz (METU Computer Eng. Dept.; Middle East Technical Universityturkey)Developing a Meta-Model to Support End-User Service Composition (ICWS2014-1060)

Feifei Hang, Liping Zhao (The University of Manchester)

Applications & Industry Session 11 Services Composition 3 (07/01 Tuesday, 8:30-9:30; Katmai)Sessoin Chair: Nuno Laranjeiro, University of Coimbra, PortugalTowards Flexibility in Transactional Service Compositions(ICWS2014-1061)

Stefanie Rinderle-Ma, Paul Grefen (University of ViennaAustria; Eindhoven University of Technology)A Context-based Autonomous Construction Approach for Procedural Mashups(ICWS2014-1062)

Wei He, Qingzhong Li, Lizhen Cui, Ting Li (Shandong University, China)Discovering Diversity Corrections for incompatible Web Services (ICWS2014-1063)

Shuai Gong, Jinhua Xiong, Zhiyong Liu, Manfred Wojciechowski (Chinese Academy of Sciences; University of AppliedSciences Dusseldorf)


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Applications & Industry Session 12 Services Discovery (06/27 Friday, 14:10-15:10; Denali)Session Chair: Yan Wang, Macquarie University, AustraliaS-ABC A Service-Oriented Artificial Bee Colony Algorithm for Global Optimal Services Selection in

Concurrent Requests Environment(ICWS2014-1064)Zhizhong, liu Liu, Xiaofei XU (Harbin institute of Technology, China)Correlation-Supported Composite Service Reselection(ICWS2014-1065)

Yuesong Zhang, Bin Zhang, Changsheng Zhang (Northeastern University, China)Towards Effectively Identifying RESTful Web Services(ICWS2014-1066)

Yao Zhao, Li Dong, Rongheng Lin, Danfeng Yan, Jun Li (Beijing University of Posts and Telecom, China)

Applications & Industry Session 13 Services Policy (06/27 Friday, 15:20-16:20; Denali)Session Chair: Richong Zhang, Beihang University, ChinaLow-Latency Service Data Aggregation using Policy Obligations(ICWS2014-1067)

Stephan Reiff-Marganiec, Marcel Tilly, Helge Janicke (University of Leicester, England; EMIC Germany; DeMontfort University)Policy Conflict Detection in Composite Web Services with RBAC(ICWS2014-1068)

Danfeng Yan, Junlin Huang, Yuan Tian, Yao Zhao, Fangchun Yang (Beijing University of Posts and

Telecommunications, China)Rule-based web service validation (ICWS2014-1069)

Mikls Klmn (Univesity of Szeged)

Applications & Industry Session 14 QoS-aware Services Selection (06/27 Friday, 16:30-17:30; Denali)Session Chair: Hailong, Sun, Beihang University, ChinaQoS Uncertainty Filtering for Fast and Reliable Web Service Selection(ICWS2014-1070)

Lei Sun, Shangguang Wang, Jinglin Li, Qibo Sun, Fangchun Yang (Beijing University of Posts andTelecommunicationsChina)Energy Efficient Dynamic Service Selection for Large-Scale Web Service Systems(ICWS2014-1071)

Ying Chen, Jiwei Huang, Xudong Xiang, Chuang Lin (Tsinghua University, China)Quality Failure Prediction for the Self Healing of Service-oriented System of Systems(ICWS2014-1072)

Hongbing Wang, Cheng Wan (SouthEast University, China)

Applications & Industry Session 15 Services Prediction (07/02 Wednesday, 8:30-9:30; Katmai)Session Chair: Mikio Aoyama, Nanzan University, JapanPerformance Functions for QoS Prediction in Web Service Composites (ICWS2014-1073)

Florian Volk, Johanna Sokoli, Max Mhlhuser (Technische Universitt Darmstadt/CASED)A Novel Online Reliability Prediction Approach for Service-Oriented Systems(ICWS2014-1074)

Hongbing Wang, Lei Wang, Qi Yu, Zibin Zheng (Southeast University China; Rochester institute of Technology,USA; The Chinese University of Hong Kong)Parameter Tuning for ABC-based Service Composition with End-to-End QoS Constraints (ICWS2014-1075)

Ruilin Liu, Zhongjie Wang, Xiaofei Xu (Harbin institute of Technology, China)

Applications & Industry Session 16 Services Tooling (07/02 Wednesday, 9:45-10:45; Katmai)Session Chair: James Shen, eBay, USAA Resource-Oriented Services Platform for Managing Software Supply Chains and its Experience

(ICWS2014-1076)Mikio Aoyama, Kazuo Yabuta, Tsutomu Kamimura, Souichi inomata, Toshiya Chiba, Takashi Niwa, Koji Sakata(Nanzan University, Japan)PEESOS: A Web Tool for Planning and Execution of Experiments in Service Oriented Systems(ICWS2014-1077)

Luiz Henrique Nunes, Luis Hideo Vasconcelos Nakamura, Bruno Tardiole Kuehne, Edvard Martins de Oliveira,Rafael Mira de Oliveira Libardi, Lucas Junqueira Adami, Julio Cezar Estrella, Stephan Reiff-MarganiecA Novel Web Service Directory Framework for Mobile Environments(ICWS2014-1078)

Rohit Verma, Abhishek Srivastava (University of Leicester, UK)

Applications & Industry Session 17 Services Annotation (07/02 Wednesday, 11:00-12:00; Katmai)Session Chair: Nianjun Zhou (Joe), IBM T.J. Watson Research Center, USAAnnotating Web Service Sections with Combined Classification(ICWS2014-1079)

Georgia M. Kapitsaki (University of Cyprus)


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A Framework for Semantic Description of RESTful Web APIs(ICWS2014-1080)Ivan Luiz Salvadori, Frank Siqueira (Federal University of Santa Catarina)

Ranking Web Services with Limited and Noisy information(ICWS2014-1081)Jiwei Huang, Ying Chen, Chuang Lin, Junliang Chen (Tsinghua University; Beijing University of Posts and

Telecommunications, China)

Applications & Industry Session 18 Services Innovation (07/02 Wednesday, 13:00-14:00; Katmai)Session Chair: Georgia Kapitsaki, University of CyprusUtilizing Web services Networks for Web service innovation(ICWS2014-1082)

Shahab Mokarizadeh, Peep Kungas, Mihhail Matskin (Royal institute of Technology (KTH); University of Tartu,Estonia; KTH)Hoop: Offloading HTTP(S) POSTs from User Devices onto Residential Gateways(ICWS2014-1083)

Kvin Huguenin, Erwan Le Merrer, Nicolas Le Scouarnec, Gilles Straub (EPFL, Switzerland;Technicolor, France)A Context-Aware Intentional Service Prediction Mechanism in PIS(ICWS2014-1084)

Salma najar, Manuele Kirsch-pinheiro, Carine Souveyet (Universit Paris 1 Panthon-Sorbonne)Application Configuration Repository for Adaptive Service-based Systems: Overcoming Challenges in anEvolutionary Online Advertising Environment (ICWS2014-1085)

Marcos E. B. Broinizi, Danilo Mutti, Joao Eduardo Ferreira (University of Sao Paulo, Brazil)

Work-in-Progress TrackWork-in-Progress Session 1 Services Selection and Composition(06/27 Friday, 9:45-10:45; Katmai)Session Chair: Shiyong Lu, Wayne State University, USADynamic Web Service Composition with QoS Clustering(ICWS2014-1086)

Ajaya Kumar Tripathy, Manas Ranjan Patra, Mohiuddin Ali Khan, Huda Fatima, Pravati Swain (Utkal University,India)Fast Selection of Web Services with QoS using a Distributed Parallel Semantic Approach(ICWS2014-1087)

Luis H. V. Nakamura, Pedro F. do Prado, Rafael Mira de O. Libardi, Luiz H. Nunes, Julio C. Estrella, Regina H.C. Santana, Marcos J. Santana, Stephan Reiff-Marganiec (University of Sao Paulo; University of Leicester)A Utility-Aware Runtime Conflict Resolver for Composite Web services(ICWS2014-1088)

Xiao Ning, Jiuyun Xu, Nan Xu, Di Li, Stephan Reiff-Marganiec (University of Leicester, UK)Trustworthy Service Composition in Service-oriented Mobile Social Networks(ICWS2014-1089)Tao Zhang, Jianfeng Ma, Ning Xi, Ximeng Liu, Zhiquan Liu, Jinbo Xiong (Xidian University, China; Fujian Normal

University, China )Automatic mining data-aware Web services properties(ICWS2014-1090)

Guoquan Wu, Jun Wei (Chinese Academy of Sciences; Chinese Academy of Sciences, China)Supporting End-User Service Composition with Automatically Generated Composite Service Descriptions(ICWS2014-1091)

Feifei Hang, Liping Zhao (The University of Manchester, UK)

Work-in-Progress Session 2 Services Management (06/27 Friday, 11:00-12:00; Katmai)Session Chair: Yucong Duan, Hainan University, ChinaComponent-based information service platform for heating industry(ICWS2014-1092)

Guangchang Hu, Budan Wu, Bo Cheng, Junliang Chen (Beijing University of Posts and Telecommunications,

China)RESTful Web Service Mining: Simple Algorithm Supporting Resource-Oriented Systems(ICWS2014-1093)Andrzej Stroinski, Dariusz Dwornikowski, Jerzy Brzezinski (Poznan University of Technology)

Revisiting the Evolution of Web Service Systems: The Amazon EC2 Case Study(ICWS2014-1094)Marios Fokaefs (University of Alberta, Canada)

Services Adaptation Based o

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