D3: distributed approach for the detection of dumb nodes in wireless sensor networks

Roy, Arijit; Kar, Pushpendu; Misra, Sudip; Obaidat, Mohammad S.

doi:10.1002/dac.2913

Cited by 20 publications

(10 citation statements)

References 34 publications

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“…It is dynamic in nature. Roy [2] proposed a distributed approach for the detection of dumb nodes, named D3. It uses cumulative sum test to detect the dumb behavior.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Connectivity Re-Establishment in UASNs with Dumb Nodes

Chen

Dai

et al. 2018

IEICE Trans. Inf. & Syst.

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The changes of temperature, salinity and ocean current in underwater environment, have adverse effects on the communication range of sensors, and make them become temporary failure. These temporarily misbehaving sensors are called dumb nodes. In this paper, an energyefficient connectivity re-establishment (EECR) scheme is proposed. It can reconstruct the topology of underwater acoustic sensor networks (UASNs) with the existing of dumb nodes. Due to the dynamic of underwater environment, the generation and recovery of dumb nodes also change dynamically, resulting in intermittent interruption of network topology. Therefore, a multi-band transmission mode for dumb nodes is designed firstly. It ensures that the current stored data of dumb nodes can be sent out in time. Subsequently, a connectivity re-establishment scheme of sub-nodes is designed. The topology reconstruction is adaptively implemented by changing the current transmission path. This scheme does't need to arrange the sleep nodes in advance. So it can reduce the message expenses and energy consumption greatly. Simulation results show that the proposed method has better network performance under the same conditions than the classical algorithms named LETC and A1. What's more, our method has a higher network throughput rate when the nodes' dumb behavior has a shorter duration.

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“…It is dynamic in nature. Roy [2] proposed a distributed approach for the detection of dumb nodes, named D3. It uses cumulative sum test to detect the dumb behavior.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Connectivity Re-Establishment in UASNs with Dumb Nodes

Chen

Dai

et al. 2018

IEICE Trans. Inf. & Syst.

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“…This is because above 20% most applications do not work properly; for instance, both the TCP window and the VoIP controller mechanism do not perform well under the aforementioned condition. Moreover, with this threshold, also dumb nodes are captured in the bad group (Roy et al, 2015;Kar et al, 2015).…”

Section: Wireless Scenariosmentioning

confidence: 99%

Achieving a High Throughput and a Low Latency through a Modular Packet Scheduler

Casoni

Grazia

Valente

2017

IJCNDS

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Providing QoS guarantees in a wireless environment is a challenging task because of the idiosyncrasies of the wireless media. State-of-the-art solutions for QoS provisioning over wireless links are based on cross-layering packet schedulers that deal both with the QoS guarantees and the wireless link issues. Unfortunately, such an approach is not flexible and requires technology-dependent solutions. To address these issues, we present a modular architecture which permits the use of existing high-performance packet schedulers for wired links over generic wireless technologies, as they are, and at the same time allows the flexibility to adapt to different channel conditions. We validate the effectiveness of our modular solution through a formal analysis. We also present high-throughput twin fair scheduler (HFS), a novel packet scheduler based on the modular architecture. HFS has constant execution time, accurate fairness, and low latency.

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“…There is a rich literature on object tracking using WSNs 2,19 but relatively few papers on anomalous node detection. [18][19][20] Almost all these papers detect an anomalous node based on its relative performance compared to the neighboring sensor nodes. We propose a novel anomaly detection method based on the estimated state values of the sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

A unified approach of simultaneous state estimation and anomalous node detection in distributed wireless sensor networks

Chatterjee

Venkateswaran

Mukherjee

2016

Int J Communication

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Summary Detection of anomalous node in distributed wireless sensor networks is extremely important for powerful inference and network reliability. In this paper, we propose a powerful linear statistical model for estimating the state values of the sensor nodes longitudinally, and the estimated state values are used for detecting the anomalous nodes. Our proposed approach is powerful because it considers the effect of the nearest neighbors on the current state values and then detects the anomalous nodes based on the estimated state values. Our method can estimate the missing state values of the sensor nodes, which are kept in sleep mode for energy conservation. We also propose an alternative Bayesian model that is computationally faster for state estimation and anomaly detection. The effectiveness of the proposed model is investigated through extensive simulation studies, and the usefulness of our algorithm is numerically assessed. The performance of the proposed approach is compared to that of the traditional approaches through simulation studies. The proposed model can be effectively used in security surveillance, pattern recognition, habitat monitoring, etc.

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D3: distributed approach for the detection of dumb nodes in wireless sensor networks

Cited by 20 publications

References 34 publications

Energy-Efficient Connectivity Re-Establishment in UASNs with Dumb Nodes

Energy-Efficient Connectivity Re-Establishment in UASNs with Dumb Nodes

Achieving a High Throughput and a Low Latency through a Modular Packet Scheduler

A unified approach of simultaneous state estimation and anomalous node detection in distributed wireless sensor networks

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