Diagnostic Tools for Wireless Sensor Networks: A Comparative Survey

Rodrigues, André; Camilo, Tiago; Silva, Jorge Sá; Boavida, Fernando

doi:10.1007/s10922-012-9240-6

Cited by 21 publications

(21 citation statements)

References 35 publications

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“…Two main modes exist to collect monitoring information [12]: an active mode (where some in-band resources are dedicated to the monitoring) and a passive mode (where monitoring information is only inferred from pre-existing data and control packets [9]). In this work, we quantitatively compare the two approaches.…”

Section: Scientific and Technical Background 21 Monitoring Wireless mentioning

confidence: 99%

Monitoring KPIs in synchronized FTDMA multi-hop wireless networks

Gaillard

Barthel

Théoleyre

et al. 2016

2016 Wireless Days (WD)

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Smart Cities rely on smart devices connected to the Internet of Things (IoT). The wireless multi-hop networks are a key building block to enable the IoT. We focus on a mutualized deployment, where a network operator offers IoT connectivity to multiple urban clients, with their specific Quality of Service (QoS) requirements. Hence, such a network must guarantee some minimum level of end-to-end delivery ratio and delay, and isolate each traffic from the others. In this paper, we aim at providing the tools to individually monitor and verify the requirements of each client. We propose to use the IETF 6TiSCH stack (IPv6 over the Time Slotted Channel Hopping mode of IEEE 802.15.4e), because it is a promising basis for meeting the latency and packet delivery ratio constraints, and because it intrinsically provides flow isolation. We propose a mechanism that collects the monitoring blocks for each client / application, by piggybacking Information Elements (IEs) onto the data packets. We show that, by using piggybacking, we save up to 45% on the monitoring overhead compared to a traditional approach.

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Section: Scientific and Technical Background 21 Monitoring Wireless mentioning

confidence: 99%

Monitoring KPIs in synchronized FTDMA multi-hop wireless networks

Gaillard

Barthel

Théoleyre

et al. 2016

2016 Wireless Days (WD)

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“…It is complementary to testing which consists of the execution of test units to detect malfunction by comparing obtained results with expected ones. In the literature, the study in 22 shows that WSN diagnosis covers the node level despite of the behavior of other nodes in a large network.…”

Section: Ffo Based Diagnosis and Testing For Ls-wsnmentioning

confidence: 99%

A Fault Fuzzy-ontology for Large Scale Fault-tolerant Wireless Sensor Networks

Benazzouz

Aktouf

Parissis

2014

Procedia Computer Science

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Fault tolerance is a key research area for many of applications such as those based on sensor network technologies. In a large scale wireless sensor network (WSN), it becomes important to find new methods for fault-tolerance that can meet new application requirements like Internet of things, urbane intelligence and observation systems. The challenge is beyond the limit of a single wireless sensor network and concerns multiple widely interconnected sub networks. The domain of fault grows considerably because of this new configuration. In this context, the paper proposes a fault fuzzy-ontology (FFO) for large scale WSNs to be used within a Web service architecture for diagnosis and testing.

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“…However, although WNS designs show good performance and behavior when being evaluated in controlled environments, experience has shown that their deployment in real environments results in poorer performance and behavior [3]. It is therefore necessary to improve this behavior, and for that, to have more accurate information of the internal WSN operation [3,4,5]. This information may be obtained by the utilization of appropriate tools, the so called WSN Monitoring Platform (WSN-MP) being the most suitable.…”

Section: Introductionmentioning

confidence: 99%

“…This model allows the comparative analysis of WSN-MPs, and offers a common environment for the design and standardization of new platforms [5]. It is based on decomposing the monitoring process into different layers, identifying the responsibilities and establishing the services, protocols and interfaces needed to accomplish them.…”

Section: Introductionmentioning

confidence: 99%

A Reference Model for Monitoring IoT WSN-Based Applications

Capella

Campelo

Bonastre

et al. 2016

Sensors

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The Internet of Things (IoT) is, at this moment, one of the most promising technologies that has arisen for decades. Wireless Sensor Networks (WSNs) are one of the main pillars for many IoT applications, insofar as they require to obtain context-awareness information. The bibliography shows many difficulties in their real implementation that have prevented its massive deployment. Additionally, in IoT environments where data producers and data consumers are not directly related, compatibility and certification issues become fundamental. Both problems would profit from accurate knowledge of the internal behavior of WSNs that must be obtained by the utilization of appropriate tools. There are many ad-hoc proposals with no common structure or methodology, and intended to monitor a particular WSN. To overcome this problem, this paper proposes a structured three-layer reference model for WSN Monitoring Platforms (WSN-MP), which offers a standard environment for the design of new monitoring platforms to debug, verify and certify a WSN’s behavior and performance, and applicable to every WSN. This model also allows the comparative analysis of the current proposals for monitoring the operation of WSNs. Following this methodology, it is possible to achieve a standardization of WSN-MP, promoting new research areas in order to solve the problems of each layer.

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Diagnostic Tools for Wireless Sensor Networks: A Comparative Survey

Cited by 21 publications

References 35 publications

Monitoring KPIs in synchronized FTDMA multi-hop wireless networks

Monitoring KPIs in synchronized FTDMA multi-hop wireless networks

A Fault Fuzzy-ontology for Large Scale Fault-tolerant Wireless Sensor Networks

A Reference Model for Monitoring IoT WSN-Based Applications

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