Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling

Sinde, Ramadhani; Begum, Feroza; Njau, Karoli N.; Kaijage, Shubi

doi:10.3390/s20051540

Cited by 59 publications

(31 citation statements)

References 44 publications

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“…A comparison has been made without using the Tabu Node Selection. Furthermore, we compared the performance of our proposed approach with the E2S-DL algorithm (Sinde et al, 2020). The E2S-DL uses cyclic phases to reduce network delay and increase network lifetime using a clustering and routing phases.…”

Section: Experiments and Discussionmentioning

confidence: 99%

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A dynamic heuristic for WSNs routing

Tounsi

2021

Cogent Engineering

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One of the most important issues in the wireless sensor networks (WSNs) is nodes energy. The routing protocols as well as nodes management are considered as the key elements to improve a network's lifetime. In this research, we have suggested a dynamic heuristic for new nodes selection that manages efficiently the active nodes using a Tabu Node Selection coupled with minimum spanning tree routing protocol (TNS). Minimizing the total energy consumption in WSN, is not enough alone, since some nodes drain their energy faster than others, and may cause network failure. To balance the energy consumption, our strategy is to identify nodes with high-energy depletion and balance data routing on their neighbours. This approach performs nodes energy balancing, by creating lists of Tabu nodes (periodically inactive nodes). Such a scheme will prevent the most used nodes, such as nodes close to the base station to see their energy drain. The nodes in the Tabu lists will dynamically be active according to the energy level of nodes surrounding them. Our new dynamic heuristic has proven to outperform other nodes management approach which does not use Tabu search. The experiments show that Tabu list combined with Minimum Spanning Tree routing protocol extend drastically the network lifetime by balancing optimally the nodes energy.

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Section: Experiments and Discussionmentioning

confidence: 99%

“…The suggested process augments the delay of packet data, which inclines to loss data. In (Sinde et al, 2020) the authors used reinforcement learning to an Energy-Efficient Scheduling using the Deep Reinforcement Learning named E2S-DRL. The suggested algorithm is meant to reduce network delay and increase network lifetime.…”

Section: Related Workmentioning

confidence: 99%

A dynamic heuristic for WSNs routing

Tounsi

2021

Cogent Engineering

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“…Reference [3] introduces the standard clustering algorithm LEACH wherein the authors R. Sinde et al (2020) uses a randomized way of selecting cluster head and also supports the data fusion or aggregation within the cluster. Here the operation during each round of data transfer is divided into two phases namely the set-up phase and the data transfer phase.…”

Section: Related Workmentioning

confidence: 99%

“…Since these nodes are not easily humanly accessible, we have to be very particular about the energy utility in these nodes as its not possible to replace or recharge the batteries in them. Hence, many algorithms have adopted a clustering approach [2][3][4][5][6][7][8][9][10][11] with the cluster heads choosing a single hop data transfer mechanism to the sink. This mechanism is effective in case of small network area.…”

Section: Introductionmentioning

confidence: 99%

Spatial Correlation Based Clustering with Node Energy Based Multi-Hop Routing Scheme for Wireless Sensor Networks

Sreedharan

Pete

2021

Teh. glas. (Online)

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Major points of concern in implementing a wireless sensor network (WSN) are the network lifetime and energy utility within any delay tolerant network. Both these parameters define the success of the sensor network. The higher the expectancy of network Lifetime, the higher is the probability of acceptance of the network. Similarly, better the energy utilization in the network, better are the chances of success and implementation of the sensor network. Clustering is one such scheme adopted in WSN towards harnessing the best of above specified parameters for the network implemented. Most popular clustering techniques are the variants of LEACH protocol that facilitate cluster formation based on the proximity of an individual node to other nodes in the sensor network. These protocols are based on a single hop structure from the selected cluster heads in the network. This paper embarks on a multi-hop clustering algorithm that takes into consideration the spatial correlation between the nodes to form clusters and implements a highly energy efficient routing scheme which selects the multi-hop path in the network in a dynamic fashion.

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“…Meanwhile, there are some projects like NDAPSO 117 that presented energy‐aware and clustered node architecture by using a modern cluster head competition mechanism. Moreover, to adjust the area partition line, the PSO algorithm is used to computes fitness function and better network performance 118,119 . However, the clustered approaches suffer from scattering and aggregating processes which add more complexity and overhead to the WSN network.…”

Section: Service Discovery and Cluster‐based Routing Protocolsmentioning

confidence: 99%

Service redundancy and cluster‐based routing protocols for wireless sensor and mobile ad hoc networks: A survey

Yagoub

Rodrigues

Khalifa

et al. 2020

Int J Communication

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SummaryService discovery (SD) is the cornerstone of wireless and mobile systems. The discovery of effective service is the key to achieve a higher level of ubiquity, which ensures the availability of services to users and applications significantly, and the high use of services. The research in this field is limited, with a few SD protocols available for specific purposes specified in the 6LoWPAN region. This paper discusses the various issues and challenges facing the design and selection of the appropriate service discovery and cluster‐based mechanism. Moreover, attention has been drawn to the cross‐layer solution by discussing different clustering techniques used to solve the redundancy problems. Furthermore, the service discovery protocols and cluster‐based routing protocols are critically investigated considering the redundancy problem, methods, mechanisms, and architectures by categorizing them into different categories, comparing them with fundamental parameters in the WSNs and MANETs environments. In addition, a modern form is proposed to show the life cycle of the service discovery process, and a new figure has been designed to clarify to the researchers various of the open issues related to the service discovery and cluster‐based routing protocols, corresponding objectives and the techniques of solving problems. Through the discussion of the scientific papers under survey, important results and valuable recommendations were reached. The survey is concluded with a summary, open research issues, outlook, and directions for future research on the topic.

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Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling

Cited by 59 publications

References 44 publications

A dynamic heuristic for WSNs routing

A dynamic heuristic for WSNs routing

Spatial Correlation Based Clustering with Node Energy Based Multi-Hop Routing Scheme for Wireless Sensor Networks

Service redundancy and cluster‐based routing protocols for wireless sensor and mobile ad hoc networks: A survey

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