Repairing sensors strategies in fault-tolerant wireless sensor networks

Azzaz, Skander; Saı̈dane, Leı̈la Azouz; Minet, Pascale

doi:10.1145/2069063.2069083

Cited by 7 publications

(6 citation statements)

References 1 publication

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“…In [6], we have used a Markov Chain to represent the communication energy consumption of a sensor node. Indeed, as the figure 1 shows, a sensor MAC layer can be modeled with a 4-states Discretetime Markov Chain.…”

Section: Analytical Modelmentioning

confidence: 99%

“…Indeed, in a first step, we have used the algorithm 2 (The Repair Scheduling Algorithm) to determine a fictive replacement deadline for each expected failure. Then, the robot departure time for each failure is computed according to the equation 6 . The presented energy model can anticipate only the sensor energy depletion failures.…”

Section: The Adaptive Distributed Pre-ventive Maintenance Strategymentioning

confidence: 99%

“…In [6], we have proposed a modified version of CMA denoted by the Centralized Maintenance strategy (CMS). Similarly to CMA, with CMS, a guardian/guardee relationship is established between the network sensors to detect an occurred failure.…”

Section: Introductionmentioning

confidence: 99%

“…To achieve this goal, we use: an analytical model to estimate the life time of each sensor and a robot coordination algorithm to schedule the 85 24-25, maintainer robots activity. In [6], we have proposed a simple energy analytical model dedicated for a WSN useful to estimate the energy consumption of a sensor. Proposed model has been used conjointly with CMS to provide a centralized preventive maintenance strategy denoted by CMSA (Centralized Maintenance Strategy with Anticipation) for the WSNs.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we propose two distributed preventive maintenance strategies denoted by: (i) F-DPMS (the Fixed Distributed Preventive Maintenance Strategy) and (ii) A-DPMS (the Adaptive Distributed Preventive Maintenance Strategy). F-DPMS and A-DPMS are based on the energy analytical model presented in [6] to estimate the sensors life times. But, to share the sensors repair load among the maintainer robots, F-DPMS uses a fixed partionning technique of the WSN sensing area (as FDMA proceeds).…”

Section: Introductionmentioning

confidence: 99%

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A distributed preventive maintenance strategy for wireless sensor networks

Azzaz¹,

Saı̈dane²

2012

Proceedings of the 9th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks

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In this paper, we have proposed two distributed preventive maintenance strategies dedicated for large-scale wireless sensor networks (WSNs) using a reduced number of mobile robots : (i) Fixed Distributed Preventive Maintenance Strategy denoted by F-DPMS, (ii) Adaptive Distributed Preventive Maintenance Strategy denoted by A-DPMS.F-DPMS and A-DPMS are based on a simple analytical model to estimate the expected failures. To share the sensors repair load among the available robots, F-DPMS subdivides the WSN sensing area in equal surface subareas. Each maintainer robot is assigned to a single one area to deal with its anticipated failures. In contrary, A-DPMS uses an adaptive area partitioning technique depending on the distribution of failures over the network map, in order to balance the repair load sharing. Simulation has shown that both F-DPMS and A-DPMS provide a null network dysfunction time with a sufficient number of robots. Obtained results show also that A-DPMS requests a minimal number of robots lower than F-DPMS. But, it produces a heavier signaling cost. To remedy this problem, we have proposed a new version of A-DPMS denoted by A-DPMS*. The novel maintenance strategy reduces not only the introduced signaling messages, but also the traveled distance achieved by the maintainer robots to replace the expected failures.

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Section: Analytical Modelmentioning

confidence: 99%

Section: The Adaptive Distributed Pre-ventive Maintenance Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A distributed preventive maintenance strategy for wireless sensor networks

Azzaz¹,

Saı̈dane²

2012

Proceedings of the 9th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks

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Maintenance strategies for wireless sensor networks: from a reactive to a proactive approach

Azzaz

Saı̈dane

2013

Trans. Emerging Tel. Tech.

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In this paper, we have introduced three proactive maintenance strategies for static wireless sensor networks (WSNs) using a limited number of mobile maintainer robots: the centralised proactive maintenance strategy denoted by CPMS, the fixed distributed proactive maintenance strategy denoted by FDPMS and the adaptive distributed proactive maintenance strategy denoted by ADPMS. The proposed maintenance strategies are based on a simple energy dissipation analytical model to estimate the occurrence times of the expected sensor failures in the network. Once identified, the anticipated failures are replaced by the available robots before they happen. To select the appropriate maintainer robot for each expected failure, CPMS opts for a centralised scheduling method based on the genetic algorithm fundamentals. However, the distributed maintenance strategies (FDPMS and ADPMS) use two different WSN area partitioning methods to share the sensor maintenance tasks among the available robots. Simulation results have shown that CPMS gives the minimal network dysfunction time representing the interruption service time induced by the detected faulted nodes. However, due to its significant signalling cost, we have remarked that CPMS can be deployed only in small scale WSNs. In large-scale ones, ADPMS has demonstrated its efficiency in terms of the network dysfunction time, the robot travelled distance and the introduced signalling cost. In particular cases, when sensor failures are uniformly distributed on the network map, FDPMS has given the best performances. INTRODUCTIONProviding a continuous service is the main requirement for many wireless sensor network (WSN) applications. To achieve this goal, the WSN must deploy a set of mechanisms to protect the network coverage from the eventual sensor failures. In literature, many approaches have been proposed to conserve the initial WSN quality of service (QoS) parameters and restore the coverage and the connectivity upon a sensor failure such as the use of mobile wireless sensors [1] and the exploiting of the nodes redundancy in the network [2]. However, in order to reduce the maintenance strategy deployment cost, Y. Mei et al.[3] proposes to use a small number of mobile robots to deal with the detected sensor failures in a static WSN. Indeed, in [3], Y. Mei and all have presented a set of algorithms to detect, report and handle the occurred sensor failures in the WSN. Thus, three approaches are introduced to coordinate the robot motions: (i) the centralised manager algorithm (CMA); (ii) the fixed distributed manager algorithm (FDMA); and (iii) the Dynamic Distributed Manager Algorithm (DDMA).By reacting after the sensor failures detection, the classical WSN maintenance approaches (CMA, FDMA and DDMA) can cause the service interruption during the failure recovery times. The network dysfunction time ratio induced by the faulted node cannot be tolerable by many real-time WSN application types such as surveillance and military applications [4]. In this paper, we introduce newer proactiv...

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A Preventive Energy-Aware Maintenance Strategy for Wireless Sensor Networks

Azzaz

Saı̈dane

2014

Ad-Hoc, Mobile, and Wireless Networks

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Repairing sensors strategies in fault-tolerant wireless sensor networks

Cited by 7 publications

References 1 publication

A distributed preventive maintenance strategy for wireless sensor networks

A distributed preventive maintenance strategy for wireless sensor networks

Maintenance strategies for wireless sensor networks: from a reactive to a proactive approach

A Preventive Energy-Aware Maintenance Strategy for Wireless Sensor Networks

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