Successors of PEGASIS protocol: A comprehensive survey

Khedr, Ahmed M.; Aziz, Ahmed; Osamy, Walid

doi:10.1016/j.cosrev.2021.100368

Cited by 35 publications

(13 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This section provides a brief background information on the focus of our survey. WSN consists of hundreds and thousands of nodes and these nodes have the potential to communicate with each other or to the Base Station (BS) ( Al-Karaki & Kamal, 2004 ; Raj, Khedr & Aghbari, 2020 ; Osamy, El-Sawy & Khedr, 2020 ; Khedr, 2015a ; Khedr, Aziz & Osamy, 2021 ). Routing refers to the path that is followed by these nodes to communicate the data to its destination and it is important to have a routing strategy for convenient communication among nodes.…”

Section: Background Informationmentioning

confidence: 99%

A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks

Osamy

Khedr

Salim

et al. 2022

PeerJ Computer Science

Self Cite

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) are becoming increasingly important, providing pervasive real-time applications that have been used to enhance smart environments in various fields such as smart cities, manufacturing, and the Internet of Things (IoT). This survey reviews and analyzes the research trends related to the utilized Artificial Intelligence (AI) methods for WSN and the potential enhancement of WSNs using these methods. We highlight the routing challenge in WSN and present a comprehensive discussion on the recent studies that utilized various AI methods in addressing the routing challenge to meet specific objectives of WSN, during the span of 2010 to 2020. This would guide the reader towards an understanding of up-to-date applications of AI methods with respect to routing challenge in WSN. In addition, a general evaluation is provided along with a comparison of utilized AI methods in WSNs, which guides the reader in identifying the most appropriate AI methods that can be utilized for solving the routing challenge. Finally, we conclude the paper by stating the open research issues and new directions for future research.

show abstract

Section: Background Informationmentioning

confidence: 99%

A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks

Osamy

Khedr

Salim

et al. 2022

PeerJ Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…In PEGASIS, every node communicates solely with its nearby neighbor and transmits to the BS in turn, hence decreasing the amount of energy consumed per round [34]. The chain is created using the greedy method and the leader of chain is responsible of transmitting the data to BS, where every network node changes its task as the leader permitting a better even distribution of energy load among WSN nodes and thus the energy consumption for each round is balanced [35]. In PEGASIS, the sensor nodes are randomly located, and each of them is capable of data sensing, wireless communication, data fusion and positioning.…”

Section: Pegasis Protocolmentioning

confidence: 99%

Improvement of Cluster Head Selection in LEACH for Reducing Energy Consumption in Wireless Sensor Networks

ALRUBAYE

Myderrizi

2022

IJET

View full text Add to dashboard Cite

“…During the process of inter-cluster multi-hop transmission, constructing the least energy-consuming path from cluster heads to base station becomes the core. Inspired by PEGASIS protocol, other algorithms introduce the idea of chaining [22] [23] to construct chain structure within or among clusters to save energy consumed by nodes. Some experts consider some factors which affecting network energy consumption from the perspective of system heterogeneous [16] [24] [28] or nonuniform clustering [6] [14] [19] [20] [25].…”

Section: Introductionmentioning

confidence: 99%

WSN Clustering Routing Algorithm Combining Sine Cosine Algorithm and Lévy Mutation

Xiaoling

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Directed against the disadvantages of relatively short life-cycle and unbalanced energy utilization among nodes in WSN, a clustering routing algorithm combining sine cosine algorithm and Lé vy mutation is developed. During the cluster head election stage, the amount of cluster heads is dynamically calculated according to the surviving nodes for keeping it at a reasonable value; taking full account of the current energy of nodes, only nodes with high energy can be candidate cluster heads; the fitness function is constructed according to inter-cluster distance, so that the distribution structure within the cluster are relatively uniform; the Sine Cosine Algorithm with improved step size search factor is used for cluster head election, and Lé vy mutation is introduced to realize the variation of population. The group of individuals with the lowest fitness function value is used as final election scheme for current round. In the data transmission phase, for the sake of avoiding long-distance transmission, the relay node is designed to forward data. The proposed algorithm effectively extends network life-cycle and well equilibriums the load of network nodes.

show abstract

Successors of PEGASIS protocol: A comprehensive survey

Cited by 35 publications

References 47 publications

A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks

A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks

Improvement of Cluster Head Selection in LEACH for Reducing Energy Consumption in Wireless Sensor Networks

WSN Clustering Routing Algorithm Combining Sine Cosine Algorithm and Lévy Mutation

Contact Info

Product

Resources

About