Energy efficient chaotic whale optimization technique for data gathering in wireless sensor network

Abstract

A Wireless Sensor Network includes the distributed sensor nodes using limited energy, to monitor the physical environments and forward to the sink node. Energy is the major resource in WSN for increasing the network lifetime. Several works have been done in this field but the energy efficient data gathering is still not improved. In order to amend the data gathering with minimal energy consumption, an efficient technique called chaotic whale metaheuristic energy optimized data gathering (CWMEODG) is introduced. The mathematical model called Chaotic tent map is applied to the parameters used in the CWMEODG technique for finding the global optimum solution and fast convergence rate. Simulation of the proposed CWMEODG technique is performed with different parameters such as energy consumption, data packet delivery ratio, data packet loss ratio and delay with deference to dedicated quantity of sensor nodes and number of packets. The consequences discussion shows that the CWMEODG technique progresses the data gathering and network lifetime with minimum delay as well as packet loss than the state-of-the-art methods.

A new optimal strategy for energy minimization in wireless sensor networks

“…The distance 𝑑 𝑖 between sensor 𝑠 𝑖 and the BS can be calculated using their coordinates (𝑥 𝑖 − 𝑦 𝑖 ) and (𝑥 𝑏 − 𝑦 𝑏 ) respectively, based on the Euclidean distance as in (3),…”

“…Recently, optimal resource management in wireless sensor networks (WSNs) has gained significant importance and is considered a fertile domain for numerous research studies [1], [2]. To support multiple applications simultaneously over a single physical WSN architecture, it is crucial to design and utilize WSNs in an optimal manner, considering their limited computing, memory, and battery power [3], [4]. In this context, ubiquitous sensor networks, which incorporate WSN technologies and internet of things (IoT) paradigms, are rapidly advancing to sense unpredictable environments and provide support to remote clients [5]- [7].…”

Energy‑harvesting and energy aware routing algorithm for heterogeneous energy WSNs

“…The research community has proposed many routing algorithms to cope with these challenges, where cluster topology is one of these proposals and is considered as the most used because of its efficiency in terms of energy consumption [15]- [17]. Based on research in this area, the hierarchical routing technique is more efficient in terms of minimizing energy consumption and prolonging the life of the network [18].…”