Volume 16, Number 6
Fuzzy-based Clustering of Wireless Sensor Networks for Multiple Mobile Agent Itinerary Planning
Authors
Nidhi Kashyap1, Shuchita Upadhyaya1, Monika Poriye1 and Sachin Lalar2, 1Kurukshetra University, India, Gurugram University Gurugram, India
Abstract
Mobile agent (MA) technology exhibits remarkable efficiency
when integrated into Wireless Sensor Networks (WSNs) for information processing tasks. MAs reduce network
overhead by executing processing code locally on nodes and selectively
transmitting significant data to designated remote sensor nodes, thereby enhancing data fusion and
acquisition while minimizing energy depletion. However, in large-scale networks, relying on a single MA
leads to significant delays,
necessitating the use of multiple MAs to operate asynchronously and minimize latency. The challenge lies in
effectively grouping nodes to ensure MAs reach their intended destinations.
To address this challenge, this paper introduces a novel approach, the Adaptive FCM Clustering
Algorithm (AFCM), a fuzzy-based clustering algorithm designed for addressing network partitioning challenges
in Multiple Mobile
Agent Itinerary Planning (MIP). A systematic analysis of the existing literature examines various MIP
algorithms, emphasizing their strengths and uncovering potential research gaps. AFCM is specifically
developed to create disjoint
and load-balanced partitions tailored for multi-mobile agent itinerary planning. A Methodical analysis with
three traditional clustering algorithms is conducted. The correctness of the Adaptive Fuzzy C-Means (AFCM)
algorithm is
demonstrated through a detailed manual application on a wireless network comprising 15 nodes
Keywords
Clustering, Itinerary planning, Mobile agent, Routing, Wireless sensor networks.