Customer Driven SLA in

Cloud Based Systems

Dr Mydhili K. Nair

Associate Professor,

Dept. of ISE, MSRIT

Balaji Soundararajan

Manager, Software QA

McAfee Software (India) Pvt. Ltd.

Varun M Deshpande

Software QA Engineer,

McAfee Software (India) Pvt. Ltd.

&

PhD Student,

Dept. of CSE, Jain University

1

ICECIT 2013

Agenda Background

Problem Domain

Literature Survey

Design and Analysis

Results

Conclusion and Future Scope

Bibliography

2

ICECIT 2013

Background Gartner says..

The total public cloud services market size in 2011 was $91.4 billion, and it will

grow to $206.6 billion in 2016.

Gartner expects the highest regional growth rates in emerging markets of

Asia/Pacific regions

ResearchOnChina.com writes..

Barely 14% of Chinese companies have adopted virtualization as compared to that

of 74% in the U.S.

The cloud computing market of China is poised to demonstrate a robust growth of

77.5% CAGR during 2010-15

China’s cloud computing market stands to capitalize upon the untapped potential in

47 million domestic SMB’s.

3

ICECIT 2013

Background contd..

Service Delivery

Requirements

Customer Service Provider

Cloud Service Model – Customer requests for service. Service provider provides the same

But each customer is different. They have different needs.

4

ICECIT 2013

Problem Domain

Enterprise Customers

Highest Availability

Lowest Downtime

24/7 Technical Support

Quickest Resolution Time

Cost is not an Issue

SMB Customers

High Availability

Low Downtime

On Demand Technical Support

Quick Resolution Time

Cost should be within Budget

Start-up and Individual Developers

High Availability during Spikes

Scheduled Downtime is fine

Technical Support after Issue reported

Resolution Time depends on Issue

Cost is a Concern

Each Class of Customer has their own concerns

5

ICECIT 2013

Problem Domain Contd..

0

2000

4000

6000

8000

10000

12000

Number of Hits

Number of Hits

Sample Request Variation

for Start-up Application

Requirements

On an average, I need to support

2000 hits per day

Only in specific weeks, I need to

support 10000+ hits

I need highest Quality of Service

(QoS) during these 2 weeks. I

am ready to pay more.

Other 6 weeks, I can do with

moderate QoS. I want to pay

less during this time.

Start-up Customer

Similarly, SMB / Enterprise

Customers may also have

similar constraints

6

ICECIT 2013

Literature Survey

Rajkumar Buyya et al. [4] highlighted the point -With growing demand of delivering services to a large number of users, cloud service providers need to offer differentiated services to users and meet their quality expectations.

Few of the approaches which they discussed to realize of this research vision consist of following:

Support for customer driven service management based on customer profiles and QoS requirements

Incorporation of autonomic resource management models that effectively self-manage changes in service requirements to satisfy both new service demands and existing service obligations

Leverage VM technology to dynamically assign resource shares according to service requirements

They envisioned the need for a deeper investigation in SLA-oriented resource allocation strategies that encompass customer driven service management.

7

ICECIT 2013

Literature Survey Contd..

Siddesh G.M. and Srinivasa K.G. in their work[5], have concentrated

on resource management problem in heterogeneous workload

environments which is the key challenge faced by cloud service

providers. They focus on dynamic resource allocation with risk analysis

by meeting SLA.

The discussed framework aims in designing, dynamic capacity

forecasting with risk analysis on clouds in scheduling the resources with

the following features:

Dynamic Resource Provision

Heterogeneous Work loads

Advanced Reservation

Dynamic capacity forecasting with risk analysis

SLA based resource scheduling/ rescheduling

Experimental results suggest that dynamic resource management is

preferable while compared to traditional static configuration.

8

ICECIT 2013

Literature Survey Contd..

Zhen Xiao et al. In their work[6], attempt to study the problem: How can

a cloud service provider best multiplex its virtual resources onto physical

hardware.

Studies have shown that many of existing data centers are often

underutilized due to over provisioning for the peak demand. This cloud

model is expected to make such practice unnecessary by offering

automatic scale up and down in response to the load variation.

They discuss a design of an automated resource management system

that achieves a good balance between the two goals. Some of their

contributions are

Developed a resource allocation system that can avoid overload the system

effectively while minimizing total number of servers used.

Reduce uneven utilization of servers. Improve overall utilization of servers.

Design load prediction algorithm that can capture future resource usages of

applications accurately

9

ICECIT 2013

Design and Analysis

Profiles inbuilt in the Cloud Architecture

10

Customer of cloud service

should be able to choose

different QoS profiles at

different times during the

contract.

There are other

quantitative parameters

like hard disk space, RAM

size, network bandwidth

etc, which can also be

choose as a function of

time.

Cloud service provider is

required to setup cloud

profiles which are

maintained at different

levels of quality of service.

Number of different types

of profiles may not be

fixed.

ICECIT 2013

Design and Analysis..

Cloud Profiles are maintained at different QoS

11

ICECIT 2013

Design and Analysis..

Dynamic Resource Management Work Flow Diagram

12

ICECIT 2013

Design and Analysis..

User Flow Model

13

ICECIT 2013

Simulation and Testing..

Assumed pricing values

for Simulation

Sample Requirements input

for Simulation

Parameter Requirements

Bandwidth (GB) 50

Machine

Architecture

x86

Number of VMs 2

HDD Space (GB) 100

DB Space (GB) 3

RAM (GB) 4

14

ICECIT 2013

Results Customer Class Request

Week 1 Week 2 Week 3 Week 4

Enterprise Best Better Best Best

SMB Better Better Best Better

Start-up / Individual

Developer

Good Best Good Good

Sample Profile Requirements

input for Simulation

Simulation

Results

Even if number of Start-up and SMB

customers increase by 1000, revenue

would increase by Rs 37.3 Lakh per

Month (4 Week)

Start-up customer would be saving

20% of their expenditure

SMB customer would be saving 13%

of their expenditure

15

0

500

1000

1500

2000

2500

Start-up SMB Enterprise

Actual Cost

Savings

ICECIT 2013

Novel QoS based Cloud System using dynamic

resource management and cloud profiling strategies

Cloud Services would be $200+ Billion industry with majority of demand coming

from developing regions

Customers can judiciously decide upon their custom

needs and avail the service which they intend to use

By providing flexibility of choosing the resources, it

would attract more customers to adopt cloud computing increasing market capital.

Customer Driven SLA in Cloud Based Systems

Conclusion 16

Benefits of Current Work

ICECIT 2013

Future Scope

Customer driven SLA is need of the hour in cloud computing

and further investigation is necessary

Work towards standardization of the cloud profiles.

Although Cloud Services are proprietary, it would be important to

have some standard template for maintaining and publishing various

cloud profiles which can be provided by the cloud service provider.

Gather real world data of cloud subscribers and run simulations

on the data in order to test and improve proposed system.

Analyze security implications of developing such a system like

VM migration issues, information security etc.

17

ICECIT 2013

Bibliography

Daryl C. Plummer, Thomas J. Bittman, Tom Austin, David W. Cearley and David Mitchell Smith, “Cloud Computing: Defining and Describing an EmergingPhenomenon,” Gartner Research- ID G00156220, June 2008

Barrie Sosinsky, “Cloud Computing Bible,” Published by John Wiley & Sons, 2011

Stefano Ferretti, Vittorio Ghini, Fabio Panzieri, Michele Pellegrini and Elisa Turrini, “QoS-aware Clouds,” IEEE 3rd International Conference on Cloud Computing, 2010

Rajkumar Buyya, Saurabh Kumar Garg and Rodrigo N. Calheiros, “SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture and Solutions,” International Conference on Cloud and Service Computing, 2011

Siddesh G.M and Srinivasa K.G, “SLA- Driven Dynamic Resource Allocation on Clouds,” ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security

Zhen Xiao, Weijia Song, and Qi Chen, “Dynamic Resource Allocation using Virtual Machines for Cloud Computing Environment”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, June 2013

18

ICECIT 2013

Thank You

For Your Time

19

ICECIT 2013