QoS based congestion evasion clustering framework of wireless sensor networks

Abstract

Congestion is a significant issue for event-based applications due to the continuous data collection and transmission by the sensors constituting the network. The congestion control technique monitors the process of adjusting the data and intends to manage the network traffic level to the threshold value. The information gathered from an intensive study is required to strengthen the knowledge base for devising a QoS based congestion evasion clustering framework of wireless sensor networks. In this scheme, the cluster heads are optimally determined and dispersed over the network. The data aggregation approach has been applied in a clustered network and set out a crucial paradigm for WSN routing. The proposal employs to mitigate congestion while messages are being forwarded via an alternate route to distribute the traffic and increase the throughput. This technique aims to balance the energy ingestion among the sensor nodes, reduce energy consumption, improve network lifetime, and achieve the quality of services. The result analysis revealed that the proposed scheme recommends 22.5% better throughput, 21% lesser end-to-end delay, 25.5% better delivery ratio, and efficiently relieves congestion while preserving the network's performance for attaining QoS in wireless sensor networks.

Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs

“…PSO-CS uses several paths for delivering data packets and has excellent control over data traffic in the network. Simulation results show that PSO-CS outperforms the existing QoS centric protocols like EE-LEACH [150], EPSO-CEO [151] and OQoSCMRP [152] in terms of throughput, end-to-end delay, packet delivery ratio, network lifetime and energy conservation. Hence, PSO-CS can be used in various delay sensitive applications.…”