Sensor Cloud

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Apr 13, 2009 - Intelligent Systems Center. Nanyang Technological University ... Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the data centers that provide those services. ..... Phone : +65-6514-1005. Email : [email protected]. Contact.
Sensor Cloud : Towards Sensor-Enabled Cloud Services

Dr Lim Hock Beng Intelligent Systems Center Nanyang Technological University 13 Apr 2009 http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Overview Cloud Computing  A Scenario  Concept of Sensor Cloud  Research Challenges  Sensor Cloud Architecture  Key Components  Sensor Data Sources 

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Cloud Computing 



A new buzzword with intricate connections to Grid Computing, Utility Computing, Cluster Computing and Web 2.0 which are well established. Many attempts to define it . . . 

 



Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the data centers that provide those services. An infrastructure in which we won’t compute on local computers, but on centralized facilities operated by third-party compute and storage utilities. A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. A way to increase capacity or add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Broadly, It Looks Like … Code Mobile Computing

Instruments

Economics

Security

Data Storage App Servers Social Networks

Platforms Applications / Services

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On the Architectural Level Applications Environ. Monitoring

Social Networking

Enterprise Computing

Finance

Bioinformatics

Programming Models Management Robust Resource Allocation

Information Management

Dynamic Provisioning

Scheduling

Monitoring

SLA and QoS

Virtualization Live Relocation

Virtual Networks

Virtual Servers

Virtual Services

Virtual Storage

Security & Scalability

Economics of Cloud

Scientific Simulations

Hardware & Platforms System Infrastructures

Operating Systems and Environments

Storage Technologies

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Networks

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Key Features of our Interest     

Immense computational and storage resources that are collocated Very high speed data processing and movement Accessibility over the Internet Service-oriented Architecture Accessibility from virtually any platform and device

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Cloud is Limited – as of now 





The immense power of the Cloud can only be fully exploited if it is seamlessly integrated into our physical lives. That means – providing the real world’s information to the Cloud in real time and getting the Cloud to act and serve us instantly. That is – adding the sensing capability to the Cloud.

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Wireless Sensor Networks (WSNs)  

Seamlessly couples the physical environment with the digital world. Sensor nodes are small, low power, low cost, and provide multiple functionalities 

 

Sensing capability, processing bandwidth, battery power.

power,

memory,

communication

In aggregate, sensor nodes have substantial data acquisition and processing capability. Useful in many application domains – Environment, Healthcare, Education, Defense, Manufacturing, Smart Home, etc.

MICA mote

sensor boards

Telos mote

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Sensor Networks are Limited too     



Very challenging to scale sensor networks to large sizes. Proprietary vendor-specific designs. Difficult for different sensor networks to be interconnected. Operate in separate silos. Sensor data cannot be easily shared by different groups of users. Insufficient computational and storage resources to handle large-scale applications. Used for fixed and specific applications that cannot be easily changed once deployed. Slow adoption of large-scale sensor network applications.

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The Missing Piece Sensor Network

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A Scenario 1:

““Lets Lets go to the Northern Cliffs” Cliffs”

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““Sounds Sounds good. 1: Please take your lunch as you appear hungry. 2: Carry drinking water as water at the Cliffs is contaminated. 3: Use antianti-UV skin cream.” cream.” anti-UV

3: Map to nearest food outlets

4: Take pictures of restaurant and send images

5: Menus of restaurants and recommended food

6: “Your Facebook friends is dining near by Go catch up with her !” !”

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An Insight into the Scenario  

Cell phone records the tourist’s gestures and activates applications such as camera, microphone, etc. The cell phone produces very swift responses in real time after:  

  



Processing geographical data Acquiring tourist’s physiological data from wearable physiological sensors (blood sugar, precipitation, etc) and cross-comparing it with his medical records Speech recognition Image processing of restaurant’s logos and accessing their internet-based profiles Accessing tourist’s social network profiles to find out his friends

Fact : the cell phone cannot perform so much tasks ! http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Need to Integrate Sensors with Cloud 

 



Acquisition of data feeds from numerous body area (blood sugar, heat, perspiration, etc) and wide area (water quality, weather monitoring, etc) sensor networks in real time. Real-time processing of heterogeneous data sources in order to make critical decisions. Automatic formation of workflows and invocation of services on the cloud one after another to carry out complex tasks. Highly swift data processing using the immense processing power of the cloud to provide quick response to the user. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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The Sensor Cloud An infrastructure that allows truly pervasive computation using sensors as interface between physical and cyber worlds, the data-compute clusters as the cyber backbone and the internet as the communication medium.     

It integrates large-scale sensor networks with sensing applications and cloud computing infrastructures. It collects and processes data from various sensor networks. Enables large-scale data sharing and collaborations among users and applications on the cloud. Delivers cloud services via sensor-rich mobile devices. Allows cross-disciplinary applications that span organizational boundaries. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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The Sensor Cloud 

 

 

Enables users to easily collect, access, process, visualize, archive, share and search large amounts of sensor data from different applications. Supports complete sensor data life cycle from data collection to the backend decision support system. Vast amount of sensor data can be processed, analyzed, and stored using computational and storage resources of the cloud. Allows sharing of sensor resources by different users and applications under flexible usage scenarios. Enables sensor devices to handle specialized processing tasks.

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Research Challenges 

Complex Event Processing and Management   



Real-time data feeds from heterogeneous sensors trigger certain events and services. The data can be used by the applications to identify the contexts and the locations and environment where the devices are being used. Find out what other services and data may also be relevant to the current set of data in order to make the correct decisions.

Massive Scale and Real Time Data Processing   

Integration with heterogeneous and massive data sources is a challenge due to the amount of information to be mined and used in real time. If the data includes real-time multimedia content such as streaming video, voice and images, it is a challenge to accurately process the data. It is also challenging to classify such content to trigger relevant services that may assist the user in his current location and scenario.

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Research Challenges 

Large Scale Computing Frameworks  



Multiple sensor data sets used for decision making may or may not be collocated. If these data sets and their corresponding access/search services are geographically distributed, the allocation of computational and storage and data migration become critical challenges.

Harvesting Collective Intelligence  

Heterogeneous and real-time sensor data feeds allow us to improve the decision making by using data and decision level fusion techniques. To maximize the intelligence that can be exploited from massively collocated information in a cloud is a challenge.

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Sensor Cloud Architecture Handheld with Sensors Sensor Network Proxy

SensorSensor-Cloud Proxy User

Traditional Cloud

INTERNET

Satellite Connection Standalone GPS Sensor Network of Sensors with Internet Connectivity http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Key Components 

Sensor-Cloud Proxy  Interface between sensor resources and the cloud fabric.  Manages sensor network connectivity between the sensor resources and the cloud.  Exposes sensor resources as cloud services.  Manages sensor resources via indexing services.  Uses cloud discovery services for resource tracking.  Manages sensing jobs for programmable sensor networks.  Manages data from sensor networks • Data format conversion into standard formats (e.g. XML) • Data cleaning and aggregation to improve data quality • Data transfer to cloud storage

 Sensor-cloud proxy can be virtualized and lives on the cloud !

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Key Components  Sensor Network Proxy  For sensor resources that do not have direct connection to the cloud, this component provides the connection.  The sensor network is still managed from the Sensor-Cloud Interface via Sensor Network Proxy.  The proxy collects data from the sensor network continuously or as and when requested by the cloud services.  Enhances the scalability of the Sensor Cloud.  Provides various services for the underlying sensor resources, e.g. power management, security, availability, QoS.

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Sensor Cloud Prototype  Develop a sensor cloud prototype based on the Open Cirrus cloud computing testbed in Singapore.  Use existing sensor deployments in Asia-Pacific as realtime information sources.

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Sensor Data Sources – The National Weather Study Project 

Large-scale environmental study project in Singapore   



Supported by multiple government agencies (NEA, MOE, etc) Promote awareness about weather patterns, climate change, global warming and the environment among Singapore’s youth. Mini weather stations deployed in schools throughout Singapore.

Goals of the National Weather Sensor Grid (NWSG)     

Connects the mini weather stations deployed in all schools. Collects and aggregates weather data into a Central Data Depository in a continuous, pervasive, and real-time manner. Process, analyze, and store large amounts of weather data using grid resources. Provide geo-centric web interfaces to access the data. Weather data can be accessed and shared by multiple schools, user agencies, and the public. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Sensor Data Sources – Sumatran cGPS Array (SuGAr) 

Earth Observatory of Singapore (EOS) - A new research initiative using sensor-rich infrastructure to provide:   







Efficient monitoring. Early alarming. Decision making for critical events such as earthquakes, volcanic eruptions, tsunamis, etc.

Under EOS, the Sumatran cGPS Array (SuGAr) is a continuous GPS network formed by 29 GPS stations deployed along the Sumatran Plate boundary. It serves as the main GPS data source for The Sumatran Plate Boundary Project, which is a multi-disciplinary effort to understand tectonic processes at a plate boundary. We are developing a sensor grid for collecting data from the GPS stations, and to process, visualize and manage the GPS data. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Sensor Data Sources – Asia-Pacific Environmental Sensor Grid 

 

 

An initiative that aims to encourage the development of technologies for disaster/emergency detection, mitigation, response, and recovery in the Asia-Pacific region. Collect data from environmental sensors deployed in the participating APEC countries to form knowledge base. Hundreds of weather sensors as part of LiveE! (Japan) and NWSG (Singapore) projects have been deployed in Japan, Singapore, Taiwan, China, Thailand, etc. The weather sensors used are heterogeneous and multivendor. We are developing mechanisms for seamless integration and sharing of data and knowledge. http://www.ntu.edu.sg/intellisys http://www.ntu.edu.sg/intellisys

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Questions ?

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Contact We are interested to discuss about the use of cloud computing for real-world applications, and explore opportunities for collaboration. Please contact : Dr Lim Hock Beng Intelligent Systems Centre Nanyang Technological University Phone : +65-6514-1005 Email : [email protected]

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