A Multi-level Effective Wireless Sensor Networks (WSNs) with Residue Number Systems and Intelligent Multi-Agent Technologies

Abstract

ABSTRACT

Wireless Sensor Networks (WSNs) consist of numerous sensor nodes spread across a targeted area, complemented by one or more base stations that monitor environmental and physical conditions. The primary challenges faced by WSNs include ensuring their energy efficiency, speed, and reliability. These networks operate on a limited energy reserve, complicating the process of energy replenishment. Additionally, the critical nature of the data collected from the environment demands that WSNs operate swiftly, reliably, and maintain functionality even in the event of component failures. Hence, designing WSNs to be reliable, energy-efficient, and fault-tolerant is crucial for enhancing their lifespan and overall performance. To address these challenges, the integration of the Residue Number System (RNS) and intelligent multi-agent technologies has been pursued to create WSNs that excel in fault tolerance, energy efficiency, speed, and reliability. Techniques such as the Chinese Remainder Theorem (CRT)-based packet division and the Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm have been developed to reduce energy consumption significantly. Additionally, the implementation of a High Spread REverse Converter (HISPREC) based on Mixed Radix Conversion for the moduli set {2ⁿ⁺¹-1, 2ⁿ, 2ⁿ-1} facilitates the swift conversion of collected residues back into the original message by the Cluster Head (CH). Moreover, the adoption of intelligent multi-agent technology enables the WSN to monitor and control its operation dynamically, ensuring continuous operation even in the presence of faults and efficiently isolating any nodes compromised by power depletion. This design approach results in a multi-layered, efficient WSN framework that leverages the strengths of RNS and intelligent multi-agent technologies. This strategy is among the pioneering efforts to incorporate these technologies into real-time WSN applications, representing a significant advancement in the design and functionality of WSNs.