TEMSEP: Threshold-Oriented and Energy-Harvesting Enabled Multilevel SEP Protocol for Improving Energy-Efficiency of Heterogeneous WSNs

Abdul-Qawy, Antar Shaddad H.; Nasser, Abdullah B.; Guroob, Abdo H.; Saad, Abdul-Malik H. Y.; Alduais, Nayef Abdulwahab Mohammed; Khatri, Narendra

doi:10.1109/access.2021.3128507

Cited by 12 publications

(7 citation statements)

References 116 publications

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“…Work presented in [27] by (K. Ali et al, 2017) [16] by (Naseer et al, 2020) [8] by (Sajwan et al, 2019) [29] by (Yao et al, 2022) focus on ad hoc deployments of wireless sensor networks in which the number of nodes are assumed to be 100 but the work presented in this study considers a heterogeneous group of nodes twice the size of the current studies and the reason for this is that these techniques mentioned above focus on either the optimized coverage or the routing of data to the control center or data offloading by the un manned aerial vehicles but not all in parallel. The network grid measure 400m 2 . Location of the control center as from Fig 1 is outside the network that can be accessed through the aerial drones.…”

Section: Simmulation and Experimental Resultsmentioning

confidence: 99%

“…Wireless sensor networks are being deployed largely in almost all areas of scientific & industrial domains. Much of this is due to the massive availability of smart devices that are capable of being connected with each other to form a network or IoT based network pointed out by (Fotouhi et al, 2020) and (Abdul-Qawy et al, 2021) respectively respectively in [1,2]. Smart Iot devices are deployed in the region of interest where they gather information and transmit it to the nearby control centers for further processing.…”

Section: Introductionmentioning

confidence: 99%

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Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network

Ahmad,

Ahmed,

Anjum

et al. 2023

PLoS ONE

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Ad-hoc wireless sensor networks face challenges of optimized node deployment for maximizing coverage and efficiently routing data to control centers in post disaster events. These challenges impact the outcome for extending the lifetime of wireless sensor networks. This study presents a uav assisted reactive zone based EHGR (energy efficient hierarchical gateway routing protocol) that is deployed in a situation where the natural calamity has caused communication and infrastructure damage to a major portion of the sensor network. EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) EHGR is tailored to meet two important concerns for a disaster hit wsn ie. optimized deployment and energy efficient routing. The first part of EGHR focuses on maximized coverage during node deployments. Maximized coverage is an important aspect to be considered during the event of disaster since most of the nodes loose coverage and are detached from the wireless sensor network. The first part of EHGR uses state of the art game theory approach to build a model that maximizes the coverage of nodes during the deployment phase from all participating entities i.e. nodes and uavs. Rather than fixing the cluster head as is the case in traditional cluster-based approaches EHGR uses the energy centroid nodes. Energy centroid nodes evolve on the basis of aggregated energy of the zone. This approach is superior to simply electing cluster head nodes on the basis of some probability function. The nodes that fail to achieve any successful outcome from the game theory matching model fail to get any association. These nodes will use multi hop d2d relay approach to reach the energy centroid nodes. Gateway relay nodes used with the game theory approach during the deployment of the uav assisted wsn improves the overall coverage by 25% against traditional leach based hierarchical approaches. Once the optimum deployment phase is completed the routing phase is initiated. Aggregated data is sent by the energy centroid nodes from the ECN nodes to the servicing micro controller enabled un manned aerial vehicles. The routing process places partial burden of zone formation and data transmission to the control center for each phase on the servicing uavs. Energy centroid nodes engage only in the data aggregation process and transmission of data to servicing uav. Servicing-uavs reduce energy dissipated of the entire zone which result in gradual decrease of energy for the zone thus increasing the network lifetime. Node deployment phase and the routing phase of EHGR utilize the computations provide by the mirco controller enabled unmanned aerial vehicles such that the computationally intensive calculations are offloaded to the servicing uav. Experiment results indicate an increase in the first dead node report, half dead node report, and last dead node report. Network lifetime is extended to approximately 1800 rounds which is an increase by ratio of 100% against the traditional leach approach and increase by 50% percent against the latest approaches as highlighted in the literature.

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Section: Simmulation and Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network

Ahmad,

Ahmed,

Anjum

et al. 2023

PLoS ONE

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“…Abdul‐Qawy et al 18 proposed threshold‐oriented and energy‐harvesting enabled multi‐level stable selection protocol (TEMSEP) for WSN networks. Energy‐harvesting relay nodes, sensor nodes, and hierarchical clustering are used in TEMSEP to perform a certain task.…”

Section: Related Workmentioning

confidence: 99%

CE2RV: Commissioned energy‐efficient virtualization for large‐scale heterogeneous wireless sensor networks

Babu

Ramesh

Kannan

et al. 2023

Int J Communication

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Summary The Internet of Things (IoT) comprises sensor networks, intelligent things, devices, and humans for heterogeneous services and applications. Energy constraints in conventional wireless networks impact IoT performance resulting in service failures. For reducing the adverse impact of energy, this article introduces a commissioned energy‐efficient resource virtualization (CE2RV) scheme. This proposed scheme classifies the sensor nodes as fast and slow‐depleting for identifying service failures. The fast‐depleting nodes are discontinued from the service replications, and the remaining energy high‐node‐connected resources are identified. Such resources are virtualized for thwarting the existing energy failures over various services. The node classifications are performed using a tree‐learning algorithm. The classifications are performed for node replacement and service virtualization under different energy depletion rates. This is required for preventing sensor network disconnections between the users and service providers. The classification is required for overcoming multiple virtualizations between common nodes across different service providers. The proposed scheme's performance is analyzed using the metrics of service disconnections, energy utilization, energy efficiency, and service delay.

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“…They are exploiting more battery energy than the remaining nodes because of handling more sensed data in the network. The hotspot problem, control packet overhead, and inefficient cluster formation are the major constraints to affect the overall performance of the IWSN [12][13][14]. Henceforth, an effective clustering algorithm is necessitated to manage these problems.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Energy-Efficient Auto Clustering Framework for Improving Quality of Service in IoT-enabled WSN Applications

S.P

PRASANTH³

2022

Preprint

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In today’s world, emerging Internet of Things (IoT) technology have the most potential to extend the influence of the internet through IoT-enabled devices in futuristic fields such as smart healthcare, commercial, and industrial applications. Wireless Sensor Network (WSN) is utilized for sensing and communication processes over IoT-based applications. However, the battery energy of the sensor nodes is restricted in IoT-enabled WSN (IWSN) owing to its irreplaceable ability. Most of the existing clustering schemes lagged to mitigate the control packet overhead problem since it consumes extra energy for data computation, gathering, and forwarding tasks at any environmental conditions. In this paper, a novel Energy-Efficient Auto Clustering (EEAC) framework has been proposed to develop the effective IWSN model with enhanced quality of service. The EEAC framework comprises three phases such as zone formation, node classification, and auto clustering phases. The objective of the first phase is to significantly form the different zones by alleviating the hotspot problem. Subsequently, the fuzzy logic algorithm is employed in the second phase to classify the nodes as Master, Sub-Master, and member nodes. Finally, the third phase of the proposed framework will accomplish the auto clustering mechanism based on hop information received from the reported packet. The performance results evident that the proposed EEAC framework obtains a lesser energy consumption of 0.01J during dense network and the network lifetime is prolonged up to 48% when compared with existing state-of-the-art clustering models.

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TEMSEP: Threshold-Oriented and Energy-Harvesting Enabled Multilevel SEP Protocol for Improving Energy-Efficiency of Heterogeneous WSNs

Cited by 12 publications

References 116 publications

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network

CE2RV: Commissioned energy‐efficient virtualization for large‐scale heterogeneous wireless sensor networks

Implementation of Energy-Efficient Auto Clustering Framework for Improving Quality of Service in IoT-enabled WSN Applications

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