Wireless Sensor Networks (WSNs) is one of the most important types of networks in the world where sensors collect information within a specific area and send the data to a central point called the Base Station (BS). Many researchers have attempted to develop or improve the performance of WSNs by trying to mitigate the limitations and challenges facing WSNs. The most important challenge is to reduce energy consumption in a limited battery power supply of sensor nodes. Energy is consumed by sensor nodes in WSNs to perform three significant functions namely data sensing, transmitting and relaying. Various energy-saving routing protocols have been proposed to solve this problem to maintain the lifetime of the network for longer periods. In this paper, we propose an optimal routing protocol using multi-objective cultural algorithm for wireless sensor networks (ORPMCA). The simulation results showed that the ORPMCA protocol extends the lifetime of the WSN compared to other protocols by 15%. تفاصيل المقالة

Recently, wireless sensor networks (WSNs) have been used increasingly in military and civilian fields, especially for target tracking and environmental monitoring purposes. The main obstacle in the way of broader use of WSNs is the limited charge of sensors used in these networks. Research has shown that the power consumption of these sensors can be reduced through the sensible use of routing protocols and multi-hop communications. While cluster-based multi-hop protocols have shown to be very effective in reducing power consumption of sensors, they tend to suffer from power balance and data conflict problems. This paper applied the multi-objective whale optimization algorithm to develop a cluster-based routing protocol for WSNs. For improving the time division multiple access cycle, a bottom-up continuous time slot allocation scheme was used with the purpose of preventing data collision in multi-hop communications, as well as maximizing the sleep period of all idle nodes, including the cluster heads. Simulations performed in MATLAB demonstrated the ability of the developed protocol in prolonging the network lifespan by almost 100% by balancing the power consumption of its sensors. تفاصيل المقالة

Wireless sensor networks have become extensively applied in various fields with their advance. They may be formed freely and simply in many areas with no infrastructure. Also, they gather information about environmental phenomena for decent efficiency and event analysis and send it to base stations. The absence of infrastructure in such networks, on the other hand, limits the sources; therefore, the nodes are powered by a battery with inadequate energy. As a result, preserving energy in such networks is a critical task. Clustering the nodes and picking the cluster head based on the available transmission factors is an intriguing way for reducing energy consumption in these networks, as the average energy consumption of the nodes is lowered and the network lifespan is increased. By combining the multi-objective grasshopper optimization algorithm and the harmony search, this study provides a novel optimization strategy for wireless sensor network clustering. The cluster head is chosen using the multi-objective grasshopper optimization algorithm, and information is communicated between the cluster head's nodes and the sink node using nearly optimum routing based on the harmony search. The simulation outcomes indicate that when the functionality of the multi-objective grasshopper optimization algorithm and the harmony search are taken into account, the suggested technique outperforms the previous methods in terms of data delivery rate, energy consumption, efficiency, and information packet transmission. تفاصيل المقالة