An effective approach for tolerating simultaneous failures in wireless sensor and actor networks

Alfadhly, Abdullah; Baroudi, Uthman; Younis, Mohamed

doi:10.1145/2348656.2348664

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…The isolated failure models the independent node failure, and patterned failure models the geographically correlated failure. The works in [ 44 , 45 , 46 ] consider simultaneous failures. Nevertheless, losing a large number of nodes simultaneously is a low probability event [ 36 ].…”

Section: Network Modelmentioning

confidence: 99%

“…Placing the minimum number of nodes for maintaining network connectivity, such that the transmission range of each sensor does not exceed a threshold, is the minimum number of Steiner points (SMT-MSP) [ 102 ], which is NP-Hard, as well. Many node placement optimization problems can be reduced to an SMT-MSP problem, e.g., [ 44 , 45 , 97 , 103 , 104 ].…”

Section: Topology Controlmentioning

confidence: 99%

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ResilientWireless Sensor Networks Using Topology Control: A Review

Huang

Martínez-Ortega

Sendra

et al. 2015

Sensors

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Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs.

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Section: Network Modelmentioning

confidence: 99%

Section: Topology Controlmentioning

confidence: 99%

ResilientWireless Sensor Networks Using Topology Control: A Review

Huang

Martínez-Ortega

Sendra

et al. 2015

Sensors

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“…Adaptivity. We note the emergence of data processing techniques in each of the three categories that are adaptive, i.e., they have the ability to respond to changes in the computing fabric or environment during data processing, e.g., [1,34]. Adaptation typically incurs a resource overhead, and it is done with the hope of obtaining a future saving as a result of having carried out the adaptation.…”

Section: Desiderata and Scopementioning

confidence: 99%

“…However, these evaluations differ in The benchmark has been developed by groups that have experience developing and evaluating both (rather different) sensor query processors and bespoke in-network algorithms. As discussed in Section 5, the benchmark subsumes many of the published evaluations of data processing techniques for WSNs, and the public availability of scripts to support the running of the benchmark and presentation of results should enable its cost-effective application by the wider community 1 .…”

Section: Introductionmentioning

confidence: 99%

“…Related work on benchmarking and performance evaluations for data intensive tasks over WSNs is provided in Section 5, and conclusions are presented in Section 6. 1 The benchmark, including scripts that provide support for running the data processing techniques evaluated in this paper on the Avrora emulator [38], is available from https: //code.google.com/p/sensorbench/. The scripts are designed to be easily extensible to accommodate other data processing techniques and/or simulators according to user requirements.…”

Section: Introductionmentioning

confidence: 99%

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SensorBench

Galpin

Stokes

Valkanas

et al. 2014

Proceedings of the 26th International Conference on Scientific and Statistical Database Management

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Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.

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Research on Connectivity Restoration of Multiple Failures in UAV Cooperative Reconnaissance System

Zhang¹,

Zhu²

2020

Communications in Computer and Information Science

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An effective approach for tolerating simultaneous failures in wireless sensor and actor networks

Cited by 10 publications

References 8 publications

ResilientWireless Sensor Networks Using Topology Control: A Review

ResilientWireless Sensor Networks Using Topology Control: A Review

SensorBench

Research on Connectivity Restoration of Multiple Failures in UAV Cooperative Reconnaissance System

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