Assessing the efficacy of a novel adaptive fuzzy c-means (AFCM) based clustering algorithm for mobile agent itinerary planning in wireless sensor networks using validity indices

Abstract

Wireless Sensor Networks (WSN) are composed of small sensor nodes that either transmit their sensed data to the sink node directly or transmit it to its respective cluster head, which then transmits it to the sink node. However, this consumes a lot of network bandwidth and energy from the constrained sensor nodes. To address these constraints, Mobile Agents (MA) paradigm can be used in WSNs, which may lead to better energy and bandwidth conservation. When a single mobile agent is insufficient to complete a task, multiple mobile agents can be deployed to perform in parallel and reduce network latency. The set of sensor nodes and their sequence that MAs must migrate to complete a task is called an itinerary. The planning of the itinerary is the most prominent and significant issue related to the MA-based system, including the determination of an appropriate number of MAs to be dispatched, determining the set of sensor nodes and their sequence to be visited by MAs. This paper proposes a fuzzy-based algorithm to partition Wireless Sensor Networks into a set of sensor nodes, called domains, for enhancing the efficiency of the WSN in terms of its prolonged operation. Experimental evaluations are conducted to compare the proposed algorithm with benchmarked algorithms. The paper suggests that the proposed algorithm's integration with MA-based systems can enhance their performance and prolong the WSN's lifetime.