Energetic sleep-scheduling via probabilistic interference K-Barrier coverage with truth-table technique in sensor network

Boualem, Adda; Dahmani, Youcef; Runz, Cyril de; Maatoug, Abdelkader

doi:10.1109/mathit.2017.8259726

Cited by 10 publications

(4 citation statements)

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“…In this context, the coverage problem have been classified in our contributions into two main categories; (a) coverage in sensor networks based on deterministic models and (b) coverage in sensor networks based on uncertain models [32]. In (a) coverage in sensor networks based on deterministic models, we quote: Energetic Sleep-Scheduling via Probabilistic Interference K-Barrier Coverage with Truth-Table Technique in Sensor Network [24], Hybrid Model Approach for Wireless Sensor Networks Coverage Improvement [21], and we quote in (b) coverage in sensor networks based on uncertain models: An Evidential Approach for Area Coverage in Mobile Wireless Sensor Networks [3], Area Coverage Optimization in Wireless Sensor Network by Semi-random Deployment (SRDP) [33], Spiderweb strategy: application for area coverage with mobile sensor nodes in 3D wireless sensor network (Spiderweb strategy) [25]…”

Section: Related Workmentioning

confidence: 99%

“…, c j k be a set of metrics generating the sensor nodes of cluster C j . The activation of the node u i necessity is defined by the following relationship (24):…”

Section: Description Of the Proposed Modelmentioning

confidence: 99%

“…, D n respectively represent the Euclidean distances of the neighboring nodes with respect to the active node u A . according to relation (24), the necessity of a node N (u i ) in a cluster j is calculated in our case study where there are two criteria; the Euclidean distance and the energy reserve, defined by (26).…”

Section: Description Of the Proposed Modelmentioning

confidence: 99%

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A fuzzy/possibility approach for area coverage in wireless sensor networks

et al. 2023

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Deterministic methods used to address the coverage problem in an uncertain deployment environment have not proven to be very successful. For this purpose, the original idea of this paper is to deal with the coverage problem in an uncertain environment with uncertain theories. We consider the imperfection in the deployment environment and in the characteristics of the sensor nodes. The selection of a minimum number of nodes for a minimum number of clusters to guarantee coverage in WSN is uncertain. As a consequence, this paper proposes a hybrid Fuzzy-Possibilistic model to schedule the Active/ Passive state of sensor nodes. This model helps to plan the scheduling of node states (Active / Passive) based on the possibilistic information fusion to make a possibilistic decision for the node activation at each period. We evaluated the proposed model with (a) a running example, (b) a statistical evaluation (calculation of the confidence interface), and (c) a comparison with maximum sensing coverage region problem (MSCR), Coverage Maximization with Sleep Scheduling (CMSS), Spider Canvas Strategy, Semi-Random Deployment Strategy (SRDP) and PEAS with location information protocols. The simulation results highlight the benefits of using the fuzzy and possibility theories for treating the area coverage problem.

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Section: Related Workmentioning

confidence: 99%

“…, c j k be a set of metrics generating the sensor nodes of cluster C j . The activation of the node u i necessity is defined by the following relationship (24):…”

Section: Description Of the Proposed Modelmentioning

confidence: 99%

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A fuzzy/possibility approach for area coverage in wireless sensor networks

et al. 2023

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“…10. Energetic Sleep-Scheduling via Probabilistic Interference K-Barrier Coverage with Truth-TableTechniquein Sensor Network[39]…”

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confidence: 99%

A Comparative Study of Deterministic and Uncertain Area Coverage Strategies in WSNs

Boualem

Runz

Ayaida

2023

Preprint

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The advent of sensor networks offers the opportunity to track events, monitor areas, and prevent withnodes barriers any intrusion type in deterministic and uncertainenvironments. This paper presents a comparative study ofour proposed strategies to address deterministic and uncertaincoverage models. Consequently, the connectivity and lifetime toaddress current and future challenges of coverage in WSNs. Thisstudy provides a comparative case focusing on our works, (a)based on deterministic models, and on (b) uncertainty models,showing the shortcomings, strengths and weaknesses of eachmodel. Finally, in present and forthcoming new technologies, asome avenues for exploring coverage problems are cited.

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