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Algorithms and protocols towards energy-efficiency in wireless networks
Abstract
A plethora of wireless technologies promise ubiquitous communication in the future. A major impediment to this vision is limited energy supply from batteries in these devices. Energy supply has far reaching implications on user experience as well as practicality of many envisaged applications. The energy consumed for radio communication in these devices is a major factor in the operating lifetimes of these devices. This calls for design of network protocols and algorithms that reduce energy consumption due to the wireless interface. In this dissertation we look at three emerging application scenarios of wireless networks and present our solutions to make radio communication energy-efficient in these scenarios. We first look at the scenario of VoIP calls over wireless LANs where we propose an algorithm to reduce energy wasted in the idle mode of the wireless interface. We show that, in spite of the interactive, real-time nature of voice, energy consumption during calls can be reduced by close to 80% in most instances. Next, we consider the scenario of tag anti-collision protocols for radio frequency identification (RFID) systems and propose three protocols that reduce energy consumption due to packet collisions. We demonstrate that all three protocols provide 40-70% energy savings both at the reader and tags (if they are active tags). Finally, we consider topology control algorithms for wireless mesh networks that derive transmit power levels that prove to be energy-efficient. We propose a non-uniform model of gain for nodes using switched-beam directional antennas and develop algorithms for this model introducing antenna orientation as a parameter in topology construction. Through our evaluations, we demonstrate that 20-40% power level reductions are possible by our approach.
Subject Area
Electrical engineering|Computer science
Recommended Citation
Namboodiri, Vinod, "Algorithms and protocols towards energy-efficiency in wireless networks" (2008). Doctoral Dissertations Available from Proquest. AAI3337020.
https://scholarworks.umass.edu/dissertations/AAI3337020