Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Hwang, I‐Shyan

doi:10.3390/s17122945

Cited by 12 publications

(6 citation statements)

References 40 publications

(148 reference statements)

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“…Furthermore, since life span concerns ordinarily constrain the design of LLNs, a prevalent approach toward expanding network longevity is by utilizing duty cycling (Türkogulları et al, 2010). In duty-cycled networks, nodes enter sleep state frequently to conserve energy, and intermittently wake up to check for action (Sahoo, Thakkar, Hwang, et al, 2017). High redundancy in network deployment is necessary to achieve this goal; only then is it possible to identify small subsets of active nodes at a time and put the major part of nodes into a sleeping state and thus saving energy (Table 1: Requirement 3).…”

Section: Balance the Monitoring Role Among Nodesmentioning

confidence: 99%

Optimal proactive monitor placement & scheduling for IoT networks

Mostafa

Molnar

Saleh

et al. 2022

Journal of the Operational Research Society

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This work is fulfilled in the context of the optimized monitoring of Internet of Things (IoT) networks. IoT networks are faulty; Things are resource-constrained in terms of energy and computational capabilities; they are also connected via lossy links. For IoT systems performing a critical mission, it is crucial to ensure connectivity, availability, and network reliability, which requires proactive network monitoring. The idea is to oversee the network state and functioning of the nodes and links; to ensure the early detection of faults and decrease node unreachability times. It is imperative to minimize the resulting monitoring energy consumption to allow the IoT network to perform its functions. Furthermore, to realize the integration of the monitoring mechanism with IoT services, this latter should work in tandem with the IoT standardized protocols, especially the IPv6 for Low-power Wireless Personal Area Networks (6LoWPAN) and the Routing Protocol for Low-power and lossy networks (RPL). In this paper, an optimized, proactive, passive, centralized monitoring system is proposed for IoT networks. The proposition ensures the optimal placement of monitoring nodes (monitors). Leveraging the graph built by RPL for routing (the DODAG), minimal sets of monitors are optimally placed to cover a given domain. The monitoring activity is optimally scheduled between several subsets of nodes to prolong longevity while minimizing the energy consumption for monitoring, communication, and state transitions. Our proposition provides the exact solution to the defined monitoring placement and scheduling problem via a Binary Integer Program. The model serves as a benchmark for the performance evaluation of contemporary models. Experimentation is designed using network instances of different topology. Results demonstrate the proposed model's effectiveness in realizing full monitoring coverage with minimum energy consumption and communication overhead and a balanced distributed monitoring role.

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Section: Balance the Monitoring Role Among Nodesmentioning

confidence: 99%

Optimal proactive monitor placement & scheduling for IoT networks

Mostafa

Molnar

Saleh

et al. 2022

Journal of the Operational Research Society

View full text Add to dashboard Cite

show abstract

“…Finally, the authors used the algorithm auxiliary information provided by the coverage edge nodes to move the nodes to the best candidate location. In [25], to reduce the cost of the K-coverage sleep-scheduling algorithm and ensure effective monitoring by the nodes, the prescheduling-based K-coverage group scheduling (PSKGS) and self-organized K-coverage scheduling (SKS) algorithm were proposed. Finally, the authors concluded that the PSKGS algorithm improves the monitoring quality and network lifetime through simulation experiments, while the SKS algorithm reduces the computational and communication costs of the nodes.…”

Section: Related Workmentioning

confidence: 99%

Target Detection Coverage Algorithm Based on 3D-Voronoi Partition for Three-Dimensional Wireless Sensor Networks

Dang

Shao

Hao

2019

Mobile Information Systems

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The detection of target events is an important research area in the field of wireless sensor networks (WSNs). In recent years, many researchers have discussed the problem of WSN target coverage in a two-dimensional (2D) coordinate system. However, the target detection problem in a 3D coordinate system has not been investigated extensively, and it is difficult to improve the network coverage ratio while ensuring reliable performance of WSN. In addition, sensor nodes that are initially deployed randomly cannot achieve accurate target coverage in practice. Moreover, it is necessary to consider the energy consumption factor owing to the limited energy of the sensor node itself. Hence, with the objective of addressing the target event coverage problem of WSNs in 3D space applications, this paper proposes a target detection coverage algorithm based on 3D-Voronoi partitioning for WSNs (3D-VPCA) in order to ensure reliable performance of the entire network. First, we extend Voronoi division based on the 2D plane, which allows 3D-Voronoi partitioning of sensor nodes in 3D regions. Then, it is optimized according to the 3D-Voronoi neighbouring node partitioning characteristics and combined with the improved algorithm. Next, we set the priority coverage mechanism and introduce the correlation force between the target point and the sensor node in the algorithm, so that the sensor node can move to the target position for accurate coverage. Finally, we carry out related simulation experiments to evaluate the performance and accuracy of the proposed algorithm. The results show that the proposed algorithm can effectively improve the coverage performance of the network while ensuring a high overall coverage ratio.

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“…However, the authors only optimised the angle of the sensor and did not solve the mobility problem in the directional sensor. In [23], the authors propose prescheduling-based k-coverage group scheduling (PSKGS) and self-organised k-coverage scheduling (SKS) algorithms to reduce the cost of the algorithm and ensure the effective monitoring of node quality. The experimental results show that PSKGS improves monitoring quality and the SKS algorithm reduces the node's computation and communication costs.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

2019

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In directional sensor networks research, target event detection is currently an active research area, with applications in underwater target monitoring, forest fire warnings, border areas, and other important activities. Previous studies have often discussed target coverage in two-dimensional sensor networks, but these studies cannot be extensively applied to three-dimensional networks. Additionally, most of the previous target coverage detection models are based on a circular or omnidirectional sensing model. More importantly, if the directional sensor network does not design a better coverage algorithm in the coverage-monitoring process, its nodes’ energy consumption will increase and the network lifetime will be significantly shortened. With the objective of addressing three-dimensional target coverage in applications, this study proposes a dynamic adjustment optimisation algorithm for three-dimensional directional sensor networks based on a spherical sector coverage model, which improves the lifetime and coverage ratio of the network. First, we redefine the directional nodes’ sensing model and use the three-dimensional Voronoi method to divide the regions where the nodes are located. Then, we introduce a correlation force between the target and the sensor node to optimise the algorithm’s coverage mechanism, so that the sensor node can accurately move to the specified position for target coverage. Finally, by verifying the feasibility and accuracy of the proposed algorithm, the simulation experiments demonstrate that the proposed algorithm can effectively improve the network coverage and node utilisation.

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Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

Cited by 12 publications

References 40 publications

Optimal proactive monitor placement & scheduling for IoT networks

Optimal proactive monitor placement & scheduling for IoT networks

Target Detection Coverage Algorithm Based on 3D-Voronoi Partition for Three-Dimensional Wireless Sensor Networks

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

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