Towards Sustainability in Portable Computing through Cloud Computing and Cognitive Radios

It is imperative to consider the concept of sustainable portable computing as the role of such devices increases our lives. With the emergence of the cloud computing paradigm, there will be an increased reliance on wireless communication from portable computing devices to more powerful centralized servers. This paradigm shift to `thin-clients' presents an opportunity to make portable computing more sustainable by shifting more functionality to centralized servers. Reduced functionality needed on these devices could mean a slower rate of hardware replacement. This could significantly cut the electronic waste that is currently attributed to the frequent replacements of these devices. One of the challenges in such a paradigm shift to thin portable clients through reduced local computation would be the additional burden imposed on the wireless communication technologies used. Wireless communication technologies must be improved to handle the additional burden that will be imposed. Any proposed wireless technology must also be energy-efficient to maximize the operating life time of these battery operated, energy-constrained devices. Software approaches to achieve energy-efficient operation are preferable as they reduce the dumping of existing hardware due to upgrades or replacements, and help reduce electronic waste. This paper discusses these challenges and describes one way to move forward towards sustainable portable computing by considering application scenarios based on cloud computing and communication through software-defined cognitive radios.

[1]  Minoru Mizuno,et al.  Energy saving potential of office equipment power management , 2004 .

[2]  Miao Ma,et al.  Joint Spectrum Sharing and Fair Routing in Cognitive Radio Networks , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[3]  Kwang-Cheng Chen,et al.  Carrier Sensing Based Multiple Access Protocols for Cognitive Radio Networks , 2008, 2008 IEEE International Conference on Communications.

[4]  Limin Xiao,et al.  Optimization of Detection Time for Channel Efficiency in Cognitive Radio Systems , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[5]  Ian F. Akyildiz,et al.  Cognitive Wireless Mesh Networks with Dynamic Spectrum Access , 2008, IEEE Journal on Selected Areas in Communications.

[6]  Kang G. Shin,et al.  Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks , 2008, IEEE Transactions on Mobile Computing.

[7]  Amir Ghasemi,et al.  Optimization of Spectrum Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.

[8]  Yunnan Wu,et al.  Allocating dynamic time-spectrum blocks in cognitive radio networks , 2007, MobiHoc '07.

[9]  Galit Zadok,et al.  The Green Switch: Designing for Sustainability in Mobile Computing , 2010, SustainIT.

[10]  Kaushik R. Chowdhury,et al.  A survey on MAC protocols for cognitive radio networks , 2009, Ad Hoc Networks.

[11]  Yiwei Thomas Hou,et al.  A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[12]  Vinod Namboodiri Are cognitive radios energy efficient? A study of the Wireless LAN scenario , 2009, 2009 IEEE 28th International Performance Computing and Communications Conference.

[13]  Hyoil Kim Adaptive MAC-layer Sensing of Spectrum Availability in Cognitive Radio Networks , 2006 .

[14]  Ben Y. Zhao,et al.  Utilization and fairness in spectrum assignment for opportunistic spectrum access , 2006, Mob. Networks Appl..

[15]  Vijay Raghunathan,et al.  Experience with a low power wireless mobile computing platform , 2004, Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758).

[16]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[17]  Haitao Zheng,et al.  Stable and Efficient Spectrum Access in Next Generation Dynamic Spectrum Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[18]  Richard E. Brown,et al.  After-hours power status of office equipment in the USA , 2005 .

[19]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[20]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[21]  Philip Ross,et al.  Cloud Computing's Killer App: Gaming , 2009, IEEE Spectrum.

[22]  Shraddha Jadhav,et al.  Accounting for the energy consumption of personal computing including portable devices , 2010, e-Energy.

[23]  Ian F. Akyildiz,et al.  Optimal spectrum sensing framework for cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[24]  Ravi Prakash,et al.  MAC-layer scheduling in cognitive radio based multi-hop wireless networks , 2006, 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks(WoWMoM'06).

[25]  Ling Luo,et al.  Analysis of Search Schemes in Cognitive Radio , 2007, 2007 2nd IEEE Workshop on Networking Technologies for Software Define Radio Networks.

[26]  Qi Zhang,et al.  Cognitive radio MAC protocol for WLAN , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[27]  William H. Tranter,et al.  Minimizing Energy Consumption Using Cognitive Radio , 2008, 2008 IEEE International Performance, Computing and Communications Conference.

[28]  Vibhore Vardhan,et al.  Power Consumption Breakdown on a Modern Laptop , 2004, PACS.

[29]  G. Fettweis,et al.  ICT ENERGY CONSUMPTION – TRENDS AND CHALLENGES , 2008 .

[30]  Hanif D. Sherali,et al.  Spectrum Sharing for Multi-Hop Networking with Cognitive Radios , 2008, IEEE Journal on Selected Areas in Communications.

[31]  Srinivasan Seshan,et al.  Self-management in chaotic wireless deployments , 2005, MobiCom '05.