Routing Algorithm for Energy Efficiency Optimizing of Wireless Sensor Networks based on Genetic Algorithms

• Published in: Wireless personal communications Vol. 133; no. 3; pp. 1829 - 1856
• Main Authors: de Azevedo Albuquerque, Kaíque Rhuan, de Medeiros, Rafael Pereira, Duarte, Rafael Moura, Villanueva, Juan Moises Mauricio, de Macêdo, Euler Cássio Tavares
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-12-2023; Springer Nature B.V
• Subjects: Communications Engineering; Computer Communication Networks; Energy consumption; Engineering; Genetic algorithms; Internet of Things; Multiple objective analysis; Network latency; Networks; Nodes; Residential areas; Residual energy; Routing (telecommunications); Sensors; Signal,Image and Speech Processing; Standard deviation; Wireless sensor networks; Wirelles sensor network; Routing algorithm; Optimize energy efficiency; Energy balancing; Genetic algorithm
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-023-10849-8

With the popularization of wireless sensor networks (WSN) and the concept of IoT (Internet-of-things), several applications have emerged in the industrial, scientific and engineering sectors. However, energy consumption is a challenge, because the demands for improvement in transmission rates and latency limitations. In particular, increasing the lifetime of wireless sensor networks has been a common goal in recent research. A viable alternative to solve this problem consists in reducing the data traffic defined by the routing protocol, which optimizes the number of messages that travel through the network. These protocols can also be optimized using evolutive algorithms, such as genetic algorithms. In the present work, is proposed a routing algorithm for WSN based on genetic algorithms, with the purpose of minimizing the total distance from the sensor node to the sink, which would allow optimized use of energy by sensor nodes and extend the lifetime of the WSN. The proposed algorithm includes a form of chromosome coding that had not yet been used in the context of routing and a new multi-objective fitness function. Performance analyzes were carried out establishing exhaustive search (ES) and opportunistic routing (OR) algorithms as comparison references and considering two scenarios: an open field and the other in a closed residential area. Proposed algorithm revealed superior performance when compared to reference algorithms. In open space and in the residential scenario, the lifetime provided by the proposed algorithm was 7320 and transmissions greater than that provided by OR. It was also observed that, with the increase in the number of transmissions, the standard deviation of the nodes’ residual energy is smaller when GAEA-RP is applied, which means the predictability of the energy consumed by them. After
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transmissions, it was 0.105 J for GAEA-RP versus 0.188 J for OR in the first scenario. In the second scenario, in addition to the smaller standard deviation of the residual energy, the proposed algorithm provides an average energy very close to that obtained with OR, which indicates the possibility of its application in environments with more obstacles. Concisely, the work introduces a new way of performing routing in WSN with average residual energy similar to OR, but with a slightly larger lifespan and greater residual energy uniformity between nodes.