Connected Coverage Optimization for Sensor Scheduling in Wireless Sensor Networks

Adulyasas, Attapol; Sun, Zhili; Wang, Ning

doi:10.1109/jsen.2015.2395958

Cited by 34 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent years, many experts, scholars at home and abroad have carried out plenty of researches thoroughly and carefully. Adulyasas et al 16 take the symmetry of the regular hexagon of a given circle as the research object and propose the connected coverage optimization algorithm, which can reduce the overlapping coverage area to improve the effective coverage of the whole monitoring area. Sun et al 17 propose the enhanced coverage control algorithm.…”

Section: Methodsmentioning

confidence: 99%

k-degree coverage algorithm based on optimization nodes deployment in wireless sensor networks

Sun

Xing

et al. 2017

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

In the process of the wireless sensor network research, the issue on the energy consumption and coverage is an essential and critical one. According to the characteristic of the sensor nodes, it is homogeneous, and we proposed the kdegree coverage algorithm based on optimization nodes deployment. First, the algorithm gives the solving procedure of the maximum seamless coverage ratio, when the three-node joint coverage has been provided. Second, when the sensor nodes are covering the monitoring area, the algorithm gives the solving procedure of the expected coverage quality and the judgment methods of the coverage ratio, when the nodes are compared with the nearby ones. And when there is redundancy coverage in the given monitoring area, we have given the solving procedure of any sensor nodes that exist in the redundant nodes coverage. Finally, using the simulation experiment, the results of the coverage algorithm based on optimization nodes deployment are compared with other algorithms in terms of the coverage quality and the network lifetime, the performance indexes have enhanced to 13.36% and 12.92% on average. Thus, the effectiveness and viability of the coverage algorithm based on optimization nodes deployment have been proved.

show abstract

Section: Methodsmentioning

confidence: 99%

k-degree coverage algorithm based on optimization nodes deployment in wireless sensor networks

Sun

Xing

et al. 2017

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…However, their proposed scheme requires the centralized network architecture, which is not desirable for the WANETs. Furthermore, the authors in [21] presented a method of coverage optimization for sensor scheduling in duty-cycled WSNs using a virtual hexagon partition composed of hexagonal cells. However, they assumed that the nodes are aware of their locations, which requires the Global Positioning System (GPS) or other positioning systems in practice.…”

Section: Related Workmentioning

confidence: 99%

A Physical-Layer Scheduling Approach in Large-Scale Cooperative Networks

et al. 2019

View full text Add to dashboard Cite

In a sensor, mesh, or ad hoc network, different transmissions take place between multiple source-destination pairs, which is referred to as data flows. In this paper, each data flow is associated with a certain duty cycle schedule to avoid collisions of multiple flows in an energy-efficient manner. Cooperative routes in the network are assumed to be linear and strip-shaped, where each hop or a level contains multiple nodes, and the distance between the nodes is kept constant. We assume all nodes in a cooperative route, which corresponds to one source-destination pair, follow the same duty cycle schedule, while schedules of different routes are orthogonal in time to avoid interference between routes. Therefore, when a new route is formed, it is important to select a duty cycle schedule that is not already in use by the nodes participating in the new route. As part of route setup , an orthogonal frequency division multiplexing packet travels from the source to the destination, identifying the schedules in use by the nodes along the path. Our objective in this paper is to analyze the probabilities of detection for this method of detecting schedules, which is useful to gain insights into duty cycling-based medium access protocol design in the presence of multiple data flows. To this end, the successive transmissions in a linear network are modeled using an irreducible discrete time Markov chain. Also, three different approaches to detect a certain schedule are investigated, which are distinguished by the binary integration process with multiple sub-carriers corresponding to the schedule. We derive the probability transition matrix for the Markov chain based on different distributions of the received signal energy, the left eigenvector of which yields the probability of detection. INDEX TERMS Wireless network, stochastic modeling, cooperative communication, Markov chains, scheduling. HAEJOON JUNG received the B.S. degree (Hons.

show abstract

“…Coverage control technology is an important basic research issue and is one of the hotspots in the field of wireless sensor network, and coverage quality affects the network lifetime directly [18]. In recent years, many experts at home and abroad have carried out research on the coverage technology in wireless sensor network elaborately and profoundly as it was developed and widely used.…”

Section: Related Workmentioning

confidence: 99%

A Novel Nonlinear Multitargetk-Degree Coverage Preservation Protocol in Wireless Sensor Networks

Sun

Xing

et al. 2016

Journal of Sensors

View full text Add to dashboard Cite

Due to the existence of a large number of redundant data in the process of covering multiple targets, the effective coverage of monitored region decreases, causing the network to consume more energy. To solve this problem, this paper proposes a multitargetk-degree coverage preservation protocol. Firstly, the affiliation between the sensor nodes and target nodes is established in the network model; meanwhile the method used to calculate the coverage expectation value of the monitored region is put forward; secondly, in the aspect of the network energy conversion, use scheduling mechanisms on the sensor nodes to balance the network energy and achieve different network coverage quality with energy conversion between different nodes. Finally, simulation results show that NMCP can improve the network lifetime by effectively reducing the number of active nodes to meet certain coverage requirements.

show abstract

Connected Coverage Optimization for Sensor Scheduling in Wireless Sensor Networks

Cited by 34 publications

References 25 publications

k-degree coverage algorithm based on optimization nodes deployment in wireless sensor networks

k-degree coverage algorithm based on optimization nodes deployment in wireless sensor networks

A Physical-Layer Scheduling Approach in Large-Scale Cooperative Networks

A Novel Nonlinear Multitargetk-Degree Coverage Preservation Protocol in Wireless Sensor Networks

Contact Info

Product

Resources

About