alexa A Power - Balancing Approach for Coverage Time Optimiz
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article

A Power - Balancing Approach for Coverage Time Optimization in Clustered Networks

S.Thirunavukkarasu1 Dr.K.P.Kaliyamurthie2
  1. Assistant Professor, Dept of IT, Bharath University, Chennai-600073, India
  2. Professor&Head, Dept of IT, Bharath University, Chennai-600073, India
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Abstract

The rapid transition to nano scale ICs has led to the integration of high performance processors and high speed, digital wireless communication circuits. For a large WSN (Wireless Sensor Network), sensors are often hierarchically organized into clusters, each having its own cluster head (CH). Within a cluster, sensors transmit data to their CH, which in turn forwards the data to the sink, either directly or through a multi hop path through other intermediate CHs. The coverage time of the network is defined as the time until one of the CHs runs out of battery, resulting in an incomplete coverage of the sensing region. The maximization of the coverage time for a clustered wireless sensor network by optimal balancing of power consumption among cluster heads (CHs). Clustering significantly reduces the energy consumption of individual sensors, but it also increases the communication burden on CHs. To investigate this tradeoff, the analytical model incorporates both the intra and the inter cluster traffic. Using a Rayleigh fading channel model for inter-cluster communications, we provide optimal power allocation strategies that guarantee (in a probabilistic sense) an upper bound on the end-to-end (inter-CH) path reliability. Our allocation strategies account for the interaction between routing and clustering by considering the impacts of intra- and intercluster traffic at each CH. Two mechanisms are proposed for achieving balanced power consumption: the routingaware optimal cluster planning and the clustering-aware optimal random relay. For both mechanisms, the problem is formulated as a signomial optimization, which can be efficiently solved using generalized geometric programming.

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