Proposing an Energy-Aware Routing Protocol by Using Fish Swarm Optimization Algorithm in WSN (Wireless Sensor Networks)

Gorgich, Shiva; Tabatabaei, Shayesteh

doi:10.1007/s11277-021-08312-7

Cited by 29 publications

(11 citation statements)

References 12 publications

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“…Accordingly, the use of a moving sink can solve this problem. The proposed method and AFSRP [ 21 ] in the OPNET simulator simulate and the results show that the proposed method for network features such as improved power consumption, packet loss rate Data, throughput rates, end-to-end latency works better.…”

Section: Discussionmentioning

confidence: 99%

“…In the paper [ 21 ], a new approach to address the problem of energy efficiency in wireless sensor networks is presented by an energy-aware routing protocol using a fish swarm optimization algorithm called AFSRP in these networks, which improves energy consumption. The proposed protocol was simulated with ERA(Energy-aware Routing Algorithm) protocol in OPNET11.5 simulator and the simulation results showed that their proposed protocol performed better than ERA protocol in terms of power consumption, end-to-end latency, media access delay, bandwidth, transmission rate, probability of successful sending to the sink, and the signal to noise ratio.…”

Section: Related Workmentioning

confidence: 99%

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Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink

Tabatabaei¹

2022

PLoS ONE

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Wireless sensor networks (WSNs) include small sensor nodes with battery and processing power and limited memory units then improving power consumption is a major design challenge for any sensor network. In this paper, a new algorithm for routing in the wireless sensor network is proposed using the ultra-innovative algorithm for bacterial Foraging and mobile sink, which leads to energy efficiency. In the proposed method, the number of sensor nodes is determined according to two criteria: the amount of energy on the battery surface and the distance to the sink ahead, which leads to the formation of regular clusters in the network. Nodes adopt a multi-step routing scheme within the network to communicate with the sink. also, the mobile sink is used to balance the load and help consume uniform energy throughout the network. The simulation results show better performance of the proposed method in terms of energy consumption by 17.99%, throughput rate by 30.04%, end-to-end delay by 46.04%, signal-to-noise ratio by 32.81%, delivery rate successfully Data to the sink is 0.80 times higher than the AFSRP (Artificial Fish Swarm Routing Protocol).

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink

Tabatabaei¹

2022

PLoS ONE

Self Cite

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“…To overcome these limitations, in the literature, bio-inspired algorithms are successfully applied to find the optimal cluster head in this protocol. In the literature, the most popular algorithms deployed for it are genetic algorithm (GA) [9], particle swarm optimization (PSO) [10], ant colony optimization [11], fish swarm optimization [12,17], and cuckoo search optimization [13]. Further, to enhance the performance of existing bio-inspired algorithms, hybridization of algorithms is done, such as genetic and fruit fly optimization [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Optimization of APTEEN Protocol in the Wireless Sensor Network Using the Huffman Coding and Artificial Neural Network

Anita

Asthana

2023

Advances in Transdisciplinary Engineering

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Due to APTEEN’s practicality, the routing protocol has become a popular choice. However, there are issues with the network’s unequal energy consumption, the early death of certain nodes, and the channel’s poor effective coverage. In the literature, biologically motivated algorithms have been implemented for optimization of the versatile and edge-sensitive energy potential networks routing protocol. These algorithms are iterative in nature. As a result, in general, choosing the best cluster head takes a lengthy time to execute. To solve these problems, this paper uses Huffman coding and artificial neural networks to optimize the Adaptive Threshold-sensitive Energy Efficient Network (APTEEN) routing protocol. The Huffman coding reduces the data packet size, whereas an artificial neural network searches for the optimal cluster head in the APTEEN routing protocol. The proposed method is simulated in MATLAB and performance evaluation is done based on alive nodes, residual energy, First Node Dead (FND), Head Node Dead (HND), and Last Node Dead (LND). The result shows that the proposed method has higher alive nodes, residual energy, and better FND, HND, and LND nodes than the existing algorithms such as EDS-APTEEN and GA-APTEEN.

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“…Besides, all the data collection and data transmission in WSN is performed through the sensor nodes deployed in the network area. The energy required in the sensor nodes for data transmission and collection is provided by the battery [6]. Hence, the lifespan of the network is mainly dependent on the sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

Secured Data Transmission Using Multi-Objective Trust Based Bat Optimization Algorithm and Enhanced Homomorphic Cryptosystem for WSN

2022

IJIES

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Wireless Sensor Networks (WSNs) have gained huge attention in different areas due to their selfconfigurability, easy maintenance and scalability features. WSN is configured with more nodes to transfer the data inside the network. The sensor networks are usually classified by low bandwidth, limited energy, limited power supplies and small size memory which leads to a very demanding environment to provide security. In recent years, accomplishing the network security objective with low energy utilization is a major issue in WSN. In this paper, twolevel security is proposed to secure data transmission over the WSN. First, the secure clustering and routing operation are performed by using the Multi-Objective Trust-based Bat Optimization Algorithm (MOTBOA). Second, the data security of the network is improved by the Enhanced Homomorphic Cryptosystem (EHC). This paper aims to offer secure communication in WSN. It is achieved by using the EHC method for the operation of encryption and decryption over the data during communication among the nodes. The performance of the proposed MOTBOA-EHC method is evaluated in terms of detection rate, delay, throughput, routing load and Packet Delivery Ratio (PDR). The existing methods namely Trust based Dynamic Source Routing (TDSR), Monarch-Cat Swarm Optimization-based routing protocol and Secured Quality of Service aware Energy Efficient Routing (SQEER) are used to evaluate the performances of the MOTBOA-EHC method. The PDR of the MOTBOA-EHC method is 92% at 100 rounds that are high when compared to the TDSR, MCSO and SQEER.

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Proposing an Energy-Aware Routing Protocol by Using Fish Swarm Optimization Algorithm in WSN (Wireless Sensor Networks)

Cited by 29 publications

References 12 publications

Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink

Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink

Optimization of APTEEN Protocol in the Wireless Sensor Network Using the Huffman Coding and Artificial Neural Network

Secured Data Transmission Using Multi-Objective Trust Based Bat Optimization Algorithm and Enhanced Homomorphic Cryptosystem for WSN

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