RFDCAR: Robust failure node detection and dynamic congestion aware routing with network coding technique for wireless sensor network

Abstract

Wireless sensor networks is an attractive concept that is being implemented in all fields of work with diverse applications. Hence it is not a surprise that there are several wireless routing algorithms available and they mainly focus on reducing the consumption of energy in WSN, the direction of the fact that a sensor node point work on batteries. But algorithms do not study on these energy deficient nodes and their collision effects. There are various reasons for node failure that can fall under mechanical or electrical problems, battery depletion, environmental degradation or hostile tampering. But the most common failure of nodes occur due to limited energy availability. Failure caused due to a group of nodes can minimize the network paths. These activities can lead to failures in the subset of acting nodes resulting in a disconnected or no path situation from the network. This algorithm introduces the multipath node disjoint routing by combining local and global procedures for adaptive route. The capable nodes in the network are located using Lyapunoy optimization technique through network coding technique that enhances the operation and lifetime of the entire network. Through weight of the packet and along with the packet receiving ratio the algorithm separates the packets and route them to a different path to the base station thereby improving delivery and optimizing time and energy. Simulations are conducted in a NS3 environment and proved that this algorithm is efficient in performance than the existing methods.

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Correspondence to T. Gobinath.

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Gobinath, T., Tamilarasi, A. RFDCAR: Robust failure node detection and dynamic congestion aware routing with network coding technique for wireless sensor network. Peer-to-Peer Netw. Appl. 13, 2053–2064 (2020). https://doi.org/10.1007/s12083-019-00806-3

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Keywords

  • Congestion
  • Cut detection
  • Encoding
  • Node detection
  • Lyapunoy optimization technique
  • Multipath node disjoint routing
  • Time and energy