Abstract
Wireless Sensor Network consists of a group of independent wireless devices, which is capable of exchanging information with one another without having the knowledge of predefined infrastructure or any centralized node. It functions of WSN depends on the participation of all the nodes in the network. The more nodes involved in the network traffic, the more powerful a WSN acquires. The Quality of Service (QoS) of a routing protocol is constructed successfully only if it knows the bandwidth of a coding host. Nevertheless, it is a challenging issue to identify the coding host and its bandwidth consumption in a WSN. Sending packets from one device to another is done via a chain of intermediate nodes. Detecting routes and forwarding packets consumes local CPU time, memory, network-bandwidth, and energy. We find that the existing, Authenticated Routing for Ad Hoc Network (ARAN) uses Dynamic Source Routing (DSR) Protocol, which has greater performance cost. So we propose a novelty path tracing algorithm using Ad hoc On Demand Distance Vector (AODV) routing protocol for finding the packet droppers in the WSN. The proposed Path Tracing Algorithm (PTA) also detects the Wormhole attack using per hop distance and link frequent appearance count parameters. The performance cost of the proposed method is minimal and outweighed when the security increases. As a result, there is a possibility for a node to delay the packet forwarding and at the same time it utilizes their own resources for data transmission. In the course of broad experimentation we demonstrate that the proposed method detects the Wormhole attacks and reduces the overhead required if the network size increases. Hence it is proved that the QoS is improved when compared to the existing ARAN protocol. The above proposed work is implemented using Network Simulator2 (NS2).
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Tamilarasi, N., Santhi, S.G. (2020). Efficient Resource Utilization to Improve Quality of Service (QoS) Using Path Tracing Algorithm in Wireless Sensor Network. In: Hemanth, D., Shakya, S., Baig, Z. (eds) Intelligent Data Communication Technologies and Internet of Things. ICICI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-030-34080-3_37
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DOI: https://doi.org/10.1007/978-3-030-34080-3_37
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