Routing and Congestion Control in Wireless Sensor Networks using the Ant Colony Optimization algorithm and the Tabu search algorithm

Seyed Salar Sefati, Roya Zareh Farkhady
2023 · doi:10.21203/rs.3.rs-2453157/v1
preprint OA: closed CC-BY-4.0
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Abstract

Wireless sensor networks (WSN) are a new generation of networks that consist of a enormous number of sensor nodes. These nodes are usually inexpensive and have the ability to communicate wirelessly, compute, and sensing. The main purpose of these networks is to collect information about the environment. These networks' function is that the nodes collect the information, and then this data is sent to the base station. Therefore, data transfer, routing, congestion control are important and challenging issues in this network type. Various protocols have been proposed in this field, considering energy utilization and increasing the network's lifetime are important problems. Our goal in this study is to consider the energy consumption and increase the network lifetime and some of the Quality of Service (QoS) parameters, such as increasing the number of alive nodes and throughput. In this paper, we use an Ant Colony Optimization (ACO) algorithm to try the routing send data from a source node to the Cluster Head (CH). Then the routing analysis performed with the Tabu search (TS) algorithm is to found the route that has congestion. If the path has more than a 70% threshold, the path putting up on the congestion route, and the ACO algorithm must find the new path to send data from source to CH. In this research, the proposed method's performance with the Adaptive Cuckoo Search Based Optimal Rate Adjustment (ACSRO) algorithm, Fuzzy based Cross-layer mechanism using Oppositional Artificial Bee Colony (FCOABC) algorithm, and the Flock-based Congestion Control (Flock-CC) algorithm in the same data set has been investigated in the NS3 simulator.

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License: CC-BY-4.0