A survey on sensor cloud architecture, applications, and approaches
Sensor Cloud
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Transcript of Sensor Cloud
Sensor CloudPresented By
Debjyoti GhoshM.Tech 3rd Semester
Dept. of Computer Science & EngineeringUniversity of Calcutta16-01-2017
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Contents
Introduction
Wireless Sensor Network
Cloud Computing
Why Sensor Cloud?
General Architecture
Detailed Architecture
Pros and Cons
Application Scenario
Conclusion
References
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Introduction What is sensor cloud?
Integrated version of Wireless Sensor Networks and Cloud Computing.
Powerful and scalable high-performance computing and massive storage infrastructure
Analysis of the processed information to extract events of interest.
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Wireless Sensor Network
A wireless sensor network (WSN) consists of spatially distributed autonomous
sensors to monitor physical or environmental conditions .
Monitors temperature, sound, pressure, etc.
Used in healthcare, military, critical infrastructure monitoring, environment
monitoring, and manufacturing.
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Cloud Computing
Provides shared computer processing resources and data to computers
and other devices on demand.
Infrastructure as a service(IaaS)
Software as a service(SaaS)
Platform as a service(PaaS)
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Why Sensor Cloud?
Sensors are limited in energy, processing power, memory, and
communication bandwidth.
WSNs have been designed to support a specific application service in
mind.
Sensor data used for specific applications cannot be easily shared among
different groups of users.
Cloud computing platform dynamically provisions, configures, and
reconfigures the servers when needed by users.
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Sensor Cloud Service Life-Cycle Model
Preparing IT resources and
sensor devices
Preparing service
templates to create service
instances
Users requesting the service instances
Utilising the service
instances
Unregistering/Deleting the
service instances
Unregidteringthe service template or
physical services
User interface via web crawler
MonitoringAutomated
provisioning of DataControlling
Virtual sensor groups
Physical Sensors 1
Physical Sensors 2
Physical Sensors 3
Preparing the IT
resources (processors,
storage, disk, memory
etc.)
Preparing the physical
sensor devices
Preparing the service
templates
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Layered Structure of Sensor Cloud
1. User and application
layers
2. Sensor-Cloud and
virtualization layers,
3. Template creation
and tangible sensors
layers16-01-2017
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Design Considerations
Virtualization
Each virtual sensor is created from one or more physical sensors which is dependent on the user application area.
A virtual sensor group is created from one or more virtual sensors.
Users can create virtual sensor groups and freely use the virtual sensors included the groups as if they owned sensors.
Users can activate or inactivate their virtual sensors, check their status, and set the frequency of data collection from them.
Standardization & Automation
Each physical sensor provides its own functions for control and data collection.
Standard like Sensor Model Language/SML mechanism enables users to access sensors without concern for the differences among the physical sensors.
Sensor-Cloud infrastructure translates the standard functions for the virtual sensors into specific functions for the different kinds of physical sensors.
Automation (in terms of response of data), improves the service delivery time and reduces the cost.
Sensor-Cloud infrastructure is an on demand service delivery and supports the full lifecycle of service delivery from the registration of physical sensors through creating templates, requesting of virtual sensors, provisioning, starting and finishing to use virtual sensors, and deleting the physical sensors.
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Design Considerations
Monitoring
The users can check the status and the availability of the virtual sensors by the monitoring mechanism of Sensor-Cloud infrastructure.
Grouping
There are many kinds of physical sensors, each application does not have to use all of them.
Each application uses some types of sensors or when the sensors which match certain constrains (such as a location).
Sensor-Cloud infrastructure can provide virtual sensors as virtual sensor groups. Users can control each virtual sensor and virtual sensor groups.
For example, a user can set the access control and the frequency of data collection
for virtual sensor groups. Sensor-Cloud infrastructure prepares typical virtual sensor
groups and users can create new virtual sensor groups by selecting virtual sensors.
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Entities Involved Sensor Owner:
Owns has physical sensors which are deployed over the area of interest.
One of the possible advantages for sensor owner could be rental fees for using thephysical sensors. The fees reflects the actual usage of the physical sensors.
A sensor owner registers the physical sensors with their properties to Sensor-Cloudinfrastructure. The owner deletes the registration of them when s/he quits sharing them.
Sensor-Cloud Administrator:
The actor who manages the Sensor-Cloud Infrastructure service.
Manages the IT resources for the virtual sensors, monitoring, and the user interfaces.
Prepares the templates for the virtual sensors and for some typical virtual sensor groups.
End User:
An actor with one or more applications or services that use the sensor data.
Requests the use of virtual sensors or virtual sensor groups that satisfy the requirements fromthe templates.
These templates are easily configurable, sharable, and removable and easily can becreated.
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Components in Architecture Portal server:
When a user logs into the portal from a Web browser, the user’s role (end user, sensor owner or Sensor-Cloud administrator) determinates the available operations.
Shows the end users the menus for logging in, logging out, requesting for provisioning or destroying virtual sensor groups, monitoring their virtual sensors, controlling them, creating templates of virtual sensor groups and checking their usage-related charges.
Gives sensor owners the menus for logging in, logging out, registering or deleting physical sensors, and checking the usage-related rental fees. One of the menus or Sensor-Cloud administrators is for creating, modifying, and deleting the templates for virtual sensors or virtual sensor groups.
Provisioning Server:
Provisioning server provisions the virtual sensor groups for the requests from the portal server.
It contains a workflow engine and predefined workflows. It executes the workflows in the proper order.
First, it checks and reserves the IT resource pool when it receives a request for provisioning. It retrieves the templates of virtual sensors and virtual sensor groups,
Then provisions the virtual sensor groups including virtual sensors on the existing or a new virtual server.
After provisioning, the provisioning server updates the definitions of the virtual sensor groups. The virtual servers are provisioned with the agents for monitoring.
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Components in Architecture
Virtual Sensor Group:
A virtual sensor group is automatically provisioned on a virtual server by the provisioning server.
Each virtual sensor group is owned by end user and has one or more virtual sensors. The end user can control the virtual sensors.
For example, they can activate or inactivate their virtual sensors, set the frequency of data collection from them, and check their status. The virtual sensor groups are controlled directly or form a Web browser.
Monitoring Server:
The monitoring server receives the data about virtual sensors from the agents in the virtual servers and the servers.
It stores the received data in a database.
The monitoring information for the virtual sensors is available using a Web browser. The Sensor-Cloud administrators are also able to monitor the status of the servers.
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Component Flow 1) Login: A end user logs in the portal on a Web browser.
2) Select the templates of virutal sensor group: The portal asks the database thelist of the templates of virual sensors and virtual sensor groups. A end user selectsthe required templates from the list.
3) Request the virutal sensor group: A end user requests the virtual sensor groupsby selecting the templates on the portal. The portal calls the provisioning serverwith the input parameters (such as the template IDs, the virtual group names, anduser ID).
4) Reserve IT resource: The provisioning server first try to reserve the IT resource forthe virtual sensor groups. If there is no spare resource on the existing virtual servers,it automatically provisions a new virtual server with a monitoring agent, andreserves the IT resource.
5) Get the templates and Provision: The provisioning server gets the templates ofthe virtual sensor group and the virtual sensors from the repository. It provisions thevirtual sensor groups on the selected virtual server.
6) Notify the completion: The provisioning server notifies the end user of thecompletion of provisioning the requested virtual sensor group by e-mail. It alsoadds the new records to the definition of the virtual sensor groups.
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Pros
Analysis
Scalability
Collaboration
Visualization
Free Provisioning of Increased Data storage and Processing Power
Dynamic Provisioning of Services
Automation
Flexibility
Quick Response Time
Resource Optimization
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Cons
Implementation Cost & Maintenance
Overload of creating the Template or Virtual Sensor Group
A continuous data connectivity is needed between end users and Sensor-
Cloud server.
Sensor-Cloud infrastructure is vulnerable and more prone to sophisticated
distributed intrusion attacks like DDOS (distribute denial of service) and XSS
(cross-site scripting).
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Application Scenario
A. Transport Monitoring
Transport monitoring system includes basic management systems like traffic signal control,navigation, automatic number plate recognition, toll collection, emergency vehiclenotification, dynamic traffic light etc.
C. Military Use
Sensor networks are used in the military for Monitoring friendly forces, equipment andammunition, Battlefield surveillance, Reconnaissance of opposing forces, Targeting, Battledamage assessment and Nuclear, biological and chemical attack detectionreconnaissance etc.
C. Weather Forecasting
Weather forecasting is the application to predict the state of the atmosphere for a futuretime and a given location. Weather monitoring and forecasting system typically includes-Data collection, Data assimilation, Numerical weather prediction and Forecastpresentation.
D. Health Care
Sensor networks are also widely used in health care area. In some modern hospital sensornetworks are constructed to monitor patient physiological data, to control the drugadministration track and monitor patients and doctors and inside a hospital.
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Conclusion
The communication among sensor nodes using Internet is a challenging task since sensor nodes contain limited band width, memory and small size batteries.
The issues of storage capacity may be overcome by widely used cloud computing technique.
The Sensor-Cloud architecture enables the sensor data to be categorized, stored, and processed in such a way that it becomes cost-effective, timely available, and easily accessible.
Integrating the existing sensors with cloud will enable an open, extensible, scalable, interoperable, and easy to use, reconstructible network of sensors for numerous applications.
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References
[1] “Sensor-Cloud,” [Online]. Available: http://sensorcloud.com/system-overview.
[2] Atif Alamri, Wasai Shadab Ansari, Mohammad Mehedi Hassan, M. Shamim Hossain, Abdulhameed Alelaiwi, M. Anwar Hossain, “A Survey on Sensor-Cloud: Architecture, Applications, and Approaches,” International Journal of Distributed Sensor Networks, 2013.
[3] “Wireless sensor network - Wikipedia, the free encyclopedia,” [Online]. Available: http://en.wikipedia.org/wiki/Wireless_sensor_network.
[4] S. K. Dash, J. P. Sahoo, S. Mohapatra, and S. P. Pati,, “Sensor-cloud: assimilation of wireless sensor network and the cloud,” Advances in Computer Science and Information Technology Networks and Communications, Spinger, vol. 84, pp. 455-464, 2012.
[5] M. Yuriyama and T. Kushida, “Sensor-cloud infrastructure physical sensor management with virtualized sensors on cloud computing,” Proceedings of the IEEE 13th International Conference on Network-Based Information Systems (NBiS ’10), pp. 1-8, September 2010.
[6] Dash, S.K., Mohapatra, S., Pattanaik, P.K.: A Survey on Applications of Sensor Network using Cloud Computing. International Journal of Computer Science and Emerging Technologies 2(4), 50–55 (2010)
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