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An Efficient Energy Aware Semigraph-Based Total Edge Domination Routing Algorithm in Wireless Sensor Networks - 2021

Research Area:  Wireless Sensor Networks


Wireless sensor networks (WSNs) are group of spatially distributed atomic sensors which are deployed widely in unattended environments. Each sensor node is capable of monitoring environmental parameters like temperature, pressure, humidity, vibration etc. And WSNs has wide range of applications starting from home automation to military surveillance. However, one of the noticeable issues in WSNs is its efficient energy usage because sensor nodes are battery powered, which cannot be replaced or recharged once deployed in target area. Since communication module consumes most of the node power, energy efficient topology construction and routing algorithm design plays the vital role for energy conservation. For energy efficient optimized topology construction selected nodes are being chosen to construct a virtual backbone. One of the principle practices followed for virtual backbone construction for optimized topology is Dominating Set (DS) of graph theory. However, generating a virtual backbone by DS or Connected Dominating Set (CDS) is NP-hard problem because of larger network size. To overcome this issue, in this paper an energy aware Total Edge Domination based semigraph model (TEDS) is proposed. The performance ratio of proposed TEDS algorithm is measured as (3+𝑙𝑛Δ+1Δ)|𝑜𝑝𝑡|, where |opt| represents size of the network constructed using proposed model. The time complexity of the proposed model is measured as O(m) and message complexity O(𝑚𝑛+𝑚Δ), where Δ is the maximum edge degree of the network. In addition, the performance of the network is simulated using the NS-2 simulator, and the performance metrics were studied.

Author(s) Name:  T. Suriya Praba,S. Saravanan,T. Sethukarasi

Journal name:  Wireless Personal Communications

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s11277-020-07982-z

Volume Information:  volume 117, pages 2423–2439 (2021)