System Level Design for Clustered Wireless Sensor Networks

Bonivento, A.; Fischione, Carlo; Necchi, L.; Pianegiani, F.; Sangiovanni-Vincentelli, A.

doi:10.1109/tii.2007.904130

Cited by 55 publications

(46 citation statements)

References 20 publications

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“…We assume that nodes of the network cannot be recharged, so the operations must conserve energy. The system scenario is quite general, because it applies to any interconnection of a plant by a multi-hop WSN to a controller tolerating a certain degree of data loss and delay [8][9][10][11][12].…”

Section: Breathmentioning

confidence: 99%

“…Similarly to SERAN [9], the routing algorithm of TREnD is hierarchically subdivided into two parts: a static route at interclusters level and a dynamical routing algorithm at node level. This is supported at the MAC layer by an hybrid TDMA and carrier sensing multiple access (TDMA/CSMA) solution.…”

Section: Trend Protocol Stackmentioning

confidence: 99%

“…In contrast to monitoring applications, for control applications there is no need to maximize the reliability. A tradeoff between latency, packet losses, and stability requirements can be exploited for the benefit of the energy consumption, as proposed by the system-level design approach [9]. Therefore, we claim that the protocol design for control needs a system-level approach whereby the need of a parsimonious use of energy and the typical requirements of the control applications are jointly taken into account and control and WSNs protocols are co-designed.…”

Section: Introductionmentioning

confidence: 99%

“…Since high reliability and low delay may demand a significant energy consumption of the network, thus reducing the WSN lifetime, the reliability and delay must be flexible design parameters that need to be adequate for the requirements. Note that controllers can usually tolerate a certain degree of packet losses and delay [8][9][10][11][12]. Hence, the maximization of the reliability and minimization of the delay are not the optimal design strategies for the control applications we are concerned within this chapter.…”

Section: Introductionmentioning

confidence: 99%

“…The protocols MMSPEED [28] and SERAN [9] are appealing for control and industrial applications. However, MMSPEED is not energy efficient because it considers a routing technique with an optimization of reliability and delay without energy constraints.…”

Section: Introductionmentioning

confidence: 99%

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Design Principles of Wireless Sensor Networks Protocols for Control Applications

Fischione

Park

Marco

et al. 2010

Wireless Networking Based Control

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Control applications over wireless sensor networks (WSNs) require timely, reliable, and energy efficient communications. This is challenging because reliability and latency of delivered packets and energy are at odds, and resource constrained nodes support only simple algorithms. In this chapter, a new system-level design approach for protocols supporting control applications over WSNs is proposed. The approach suggests a joint optimization, or co-design, of the control specifications, networking layer, the medium access control layer, and physical layer. The protocol parameters are adapted by an optimization problem whose objective function is the network energy consumption, and the constraints are the reliability and latency of the packets as requested by the control application. The design method aims at the definition of simple algorithms that are easily implemented on resource constrained sensor nodes. These algorithms allow the network to meet the reliability and latency required by the control application while minimizing for energy consumption. The design method is illustrated by two protocols: Breath and TREnD, which are implemented on a test-bed and compared to some existing solutions. Experimental results show good performance of the protocols based on this design methodology in terms of reliability, latency, low duty cycle, and load balancing for both static and time-varying scenarios. It is concluded that a system-level design is the essential paradigm to exploit the complex interaction among the layers of the protocol stack and reach a maximum WSN efficiency.

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Section: Breathmentioning

confidence: 99%

Section: Trend Protocol Stackmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design Principles of Wireless Sensor Networks Protocols for Control Applications

Fischione

Park

Marco

et al. 2010

Wireless Networking Based Control

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Dynamics of the worm transmission in wireless sensor network in the framework of fractional derivatives

Achar

Baishya

Kaabar

2021

Math Methods in App Sciences

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Wireless sensor networks (WSNs) are subject to cyber attacks. Security of such networks is a significant priority for everyone. Due to the network's frail defense mechanisms, WSNs are easy targets for worm attacks. A single unsecured node via contact can effectively propagate the worm across the entire network. Mathematical epidemic models are helpful in analyzing worm propagation in WSNs. To understand the attacking and spreading dynamics of worms in WSNs, a fractional‐order compartmental epidemic model is investigated with susceptible, exposed, infected, recovered, and vaccinated nodes. Dynamical aspects such as boundedness, existence, and uniqueness of the solutions are presented with the help of fractional calculus theory. Global stability of the points of equilibrium are established. The projected nonlinear structure is examined numerically via the generalized Adams–Bashforth–Moulton method. This study demonstrates the influence of the fractional operator on WSNs dynamics and the efficiency of the numerical method.

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A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

2020

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Summary Real‐time sensing plays an important role in ensuring the reliability of industrial wireless sensor networks (IWSNs). Sensor nodes in IWSNs have inherent limitations that give rise to different anomalies in the network. These anomalies can lead to disastrous and harmful situations or even serious system failures. This article presents a formulation to the design of an anomaly detection scheme for detecting the anomalous node along with the type of anomaly. The proposed scheme is divided into two major parts. First, spatiotemporal correlation within a cluster is obtained for the normal and anomalous behavior of sensor nodes. Second, the multilevel hybrid classifier is used by combining the sequential minimal optimization support vector machine (SMO‐SVM) as a binary classifier with optimally pruned extreme learning machine (OP‐ELM) as a multiclass classifier for detection of an anomalous node and type of anomalies, respectively. Mahalanobis distance‐based lightweight K‐Medoid clustering is used to build a new set of training datasets that represents the original training dataset, by significantly reducing the training time of a multilevel hybrid classifier. Results are analyzed using standard WSN datasets. The proposed model shows high accuracy, i.e., 94.79% and detection rate, i.e., 94.6% with a reduced false positive rate as compared to existing hybrid methods.

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System Level Design for Clustered Wireless Sensor Networks

Cited by 55 publications

References 20 publications

Design Principles of Wireless Sensor Networks Protocols for Control Applications

Design Principles of Wireless Sensor Networks Protocols for Control Applications

Dynamics of the worm transmission in wireless sensor network in the framework of fractional derivatives

A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

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