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Towards Sustainable Portable Computing through Cloud Computing and Cognitive Radios

Towards Sustainable Portable Computing through Cloud Computing and Cognitive Radios. Vinod Namboodiri Wichita State University. Sustainability. The World Wide Fund for Nature, United Nations Environment Programme , and World Conservation Union define sustainability as follows:

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Towards Sustainable Portable Computing through Cloud Computing and Cognitive Radios

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  1. Towards Sustainable Portable Computing through Cloud Computing and Cognitive Radios Vinod Namboodiri Wichita State University

  2. Sustainability • The World Wide Fund for Nature, United Nations Environment Programme, and World Conservation Union define sustainability as follows: • Sustainability is improving the quality of human life while living within the carrying capacity of supporting eco-systems.

  3. Computing Plays a Role • Anywhere from 3-7% of global energy attributed to Information and Communication Technologies (ICT) • That is why we have this workshop!

  4. Sustainability – Portable Devices Energy consumed off the grid Electronic Waste Does not include data center cooling costs Somavat et. al, e-Energy 2010, with updated results

  5. Existing Approaches • Energy-aware schemes to maximize battery lifetime • Energy efficient protocols at various layers of the stack • Cross-layer approaches • Do not necessarily address energy consumed from the grid • Do not address electronic waste problem

  6. Hardware or Software Approach? • New hardware could be more energy-efficient • New hardware = more electronic waste! • Software upgrades through improved protocols, drivers, OS can also lead to energy-efficiency • Minimizes device replacement • Favor software approaches where possible

  7. A Proposed Solution • Rely on Cloud Computing paradigm • portable device executes all applications remotely • more like a thin-client • Example • Game of Chess on Smartphone • Play locally or online

  8. Application executed locally on device hardware Application executed on remote server over a communication network WLAN Access Server(s) • Periodic hardware upgrades needed on device due to limited local resources • Periodic hardware upgrades lead to more waste • Application execution with limited resources could be energy-inefficient for portable devices • Non-Sustainable • Fewer or no hardware upgrades needed on device; needed only on server(s) • Rare hardware updates results in less waste • Application execution on remote, powerful servers could be energy-efficient • More Sustainable Non-Cloud Architecture Cloud Architecture • Communication will be bottleneck • For portable devices, wireless medium will have heavy contention • Cognitive Radio could be the answer, • if found energy-efficient

  9. Cognitive Radios Courtesy Broadband Wireless Networking Lab, Georgia Tech Courtesy Anonymous Source

  10. Why Cognitive Radios? • State-of-the-art solution to wireless spectrum congestion • Can continuously hunt for spectrum that is less congested • Implemented mainly in software; software upgrades can keep optimizing communication energy consumption

  11. Are Cognitive Radios Energy Efficient? • Save Energy • By finding spectrum with • Less contention • Better channel conditions • Waste Energy • Scanning is a • power-intensive process • Delay inducing process

  12. Factors under Study Higher Layer Node distribution, Channel scanning time, Number of nodes, etc. Physical Layer Channel Conditions Merits of Cognition To Energy Consumption - better channel - less contention Demerits to obtaining Cognition - power intensive - time consuming

  13. Cognitive Radio Result Notes: Two radios used; one for scanning one for communication Node conttention only factor differentiating channels Number of Channels Considered = 20. All scanned.

  14. Cloud vs Non-Cloud C1; Google Docs C2: Office Live NC: Microsoft Office with WiFi off

  15. Future Work • Consider many cloud based applications • Understand cloud based network traffic and optimize energy for communication • Consider cloud based application scenarios and impact on energy consumption under the cognitive radio model

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