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[ pdf ] Energy and Utility Optimization in Wireless Networks with Random Access

Energy and Utility Optimization in Wireless Networks with Random Access Download
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Topic under  Wireless Connectivity
Source: ee.sharif.edu 
File size: 301 kb
File type: pdf
Last download on: Sun May 14, 2017 02:23:17 PM
Short Desciption:
In this paper an ad-hoc network is considered where there is no infrastructure and intermediate nodes send packets toward their destinations. It is common in such networks to use random access since random access algorithms are inherently distributed given that nodes themselves decide when to access the channel [1]. The main characteristic of random access is independent transmission of nodes.

Summary:
Abstract— Energy consumption should be minimized in wireless networks since nodes are supplied with limited energy batteries. Energy minimization increases the time that networks’ nodes work properly without recharging or substituting batteries. Another criterion for network performance is data transmission at the proper rates which is usually quantified by means of network utility function. There exists an inherent tradeoff between these criteria and enhancing one of them can deteriorate the other one. In this paper we consider both Network Utility Maximization (NUM) and energy minimization in a bicriterion optimization problem. The problem is formulated in Random Access (RA) which is the most practical Medium Access Control (MAC) for ad-hoc networks. First, we optimize performance of MAC and define utility as a monotonically increasing function of link throughputs. We investigate the optimal tradeoff between energy and utility in this part. In the second part, we define utility as a function of end to end rates and optimize MAC and transport layers simultaneously. We calculate optimal persistence probabilities and end to end rates. Finally, by means of duality theorem we decompose the problem into smaller subproblems, which are solved at nodes and network layers separately. This decomposition avoids central unit and sustains benefits of layering. Keywords- Energy-utility tradeoff; persistence probability, random access; convex optimization; distributed algorithm.
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