QoS provisioning-based routing protocols using multiple data sink in IoT-based WSN

Verma, Sandeep; Sood, Neetu; Sharma, Ajay K.

doi:10.1142/s0217732319502353

Cited by 41 publications

(21 citation statements)

References 57 publications

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“…SEECP 28 adopted multihop communication which at the end made them suffering from hot-spot problem. 29 Further, various researchers have proposed CH selection based on metaheuristic approaches. Saemi et al 30 focused on partitioning clustering algorithms (PCA).…”

Section: A Brief Survey On Existing Ch Selection Methodsmentioning

confidence: 99%

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A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

Manchanda

Sharma

2020

Int J Communication

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Summary Wireless sensor network (WSN) suffers from the energy‐limited sensor nodes which consume energy heavily depending upon the magnitude of data which is transmitted or received by the nodes in the network. In this paper, our primary aim is to reduce the quantity of data transmitted to the data‐collecting sink, which helps in the energy preservation and eventually leads to network longevity. To address this concern, in this paper, we propose a novel framework for energy‐efficient compressive data gathering (NFECG) for heterogeneous WSN. NFECG works in four following phases; in the first phase, the cluster head (CH) selection is performed by considering remaining energy, “distance within the nodes and the sink,” and node density; in second phase, sleep scheduling is done among the cluster member nodes; further, in third phase, the compression of the aggregated data is performed at the CH level, and equivalent compressed sparse signals are generated which are transmitted to sink. In the last phase, at the sink, decompression is applied to retrieve the original signals. The simulation of NFECG is performed using MATLAB under two cases of different network area and number of nodes. We examine its performance for various performance metrics and also inspect for its scalable characteristics. The results show that for one of the two cases, it improves stability period and network lifetime by 52.59% and 46.09%, respectively, as compared to energy‐adjusted high‐level data total tree (EHDT) protocol, and also for the other case of network configuration, it acquires supreme performance.

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Section: A Brief Survey On Existing Ch Selection Methodsmentioning

confidence: 99%

“…However, it is discerned that TEDRP still suffers from the hot‐spot problem due to the relaying of data traffic to the sink. SEECP 28 adopted multihop communication which at the end made them suffering from hot‐spot problem 29 …”

Section: Related Workmentioning

confidence: 99%

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

Manchanda

Sharma

2020

Int J Communication

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“…The authors in [29] used the GA-based optimization for the heterogeneous network. Quality of Service (QoS) were handled to improve the network performance with the use of multiple data sinks in the network [30].…”

Section: Ch Selection Using Heterogeneous Algorithmsmentioning

confidence: 99%

Particle swarm optimization based energy efficient clustering and sink mobility in heterogeneous wireless sensor network

2020

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In a WSN, sensor node plays a significant role. Working of sensor node depends upon its battery's life. Replacements of batteries are found infeasible once they are deployed in a remote or unattended area. Plethora of research had been conducted to address this challenge, but they suffer one or the other way. In this paper, a particle swarm optimization (PSO) algorithm integrated with an energy efficient clustering and sink mobility ((PSO-ECSM) is proposed to deal with both cluster head selection problem and sink mobility problem. Extensive computer simulations are conducted to determine the performance of the PSO-ECSM. Five factors such as residual energy, distance, node degree, average energy and energy consumption rate (ECR) are considered for CH selection. An optimum value of these factors is determined through PSO-ECSM algorithm. Further, PSO-ECSM addresses the concern of relaying the data traffic in a multi-hop network by introducing sink mobility. PSO-ECSM's performances are tested against the state-of-the-art algorithms considering five performance metrics (stability period, network, longevity, number of dead nodes against rounds, throughput and network's remaining energy). Statistical tests are conducted to determine the significance of the performance. Simulation results show that the PSO-ECSM improves stability period, half node dead, network lifetime and throughput vis-à-vis ICRPSO by 24.8%, 31.7%, 9.8 %, and 12.2%, respectively.

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“…However, the energy depletion increased due to the systematic rotation of the relay nodes and increased the consequently depleted energy. A novel routing architecture designed for harsh environment monitoring was proposed by Verma [ 48 ]. The objective of this work was to prolong the lifespan by addressing the hotspot problem in the network.…”

Section: Related Workmentioning

confidence: 99%

CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things

Sankar¹,

Ramasubbareddy

Luhach

et al. 2020

Sensors

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Energy conservation is one of the most critical challenges in the Internet of Things (IoT). IoT devices are incredibly resource-constrained and possess miniature power sources, small memory, and limited processing ability. Clustering is a popular method to avoid duplicate data transfer from the participant node to the destination. The selection of the cluster head (CH) plays a crucial role in gathering and aggregating the data from the cluster members and forwarding the data to the sink node. The inefficient CH selection causes packet failures during the data transfer and early battery depletion nearer to the sink. This paper proposes a cluster tree-based routing protocol (CT-RPL) to increase the life span of the network and avoid the data traffic among the network nodes. The CT-RPL involves three processes, namely cluster formation, cluster head selection, and route establishment. The cluster is formed based on the Euclidean distance. The CH selection is accomplished using a game theoretic approach. Finally, the route is established using the metrics residual energy ratio (RER), queue utilization (QU), and expected transmission count (ETX). The simulation is carried out by using a COOJA simulator. The efficiency of a CT-RPL is compared with the Routing Protocol for Low Power and Lossy Networks (RPL) and energy-efficient heterogeneous ring clustering routing (E2HRC-RPL), which reduces the traffic load and decreases the packet loss ratio. Thus, the CT-RPL enhances the lifetime of the network by 30–40% and the packet delivery ratio by 5–10%.

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QoS provisioning-based routing protocols using multiple data sink in IoT-based WSN

Cited by 41 publications

References 57 publications

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

Particle swarm optimization based energy efficient clustering and sink mobility in heterogeneous wireless sensor network

CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things

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