Infrastructure Communication Reliability of Wireless Sensor Networks

Shrestha, A.; Xing, Liudong; Liu, Hong

doi:10.1109/dasc.2006.31

Cited by 46 publications

(42 citation statements)

References 12 publications

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“…Model-driven design, development and maintenance of WSNs can significantly reduce the cost and time of evaluating theses networks [23,30]. Binary decision diagram (BDD) [30], logistic regression [31], fault tree [32], factoring method [33], reliability block diagram (RBD) [34] and queuing networks [35,36] are examples of model-driven design, development and maintenance of WSNs.…”

Section: Analytical Modeling Of the Proposed Data Aggregation Methodsmentioning

confidence: 99%

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An Efficient Data Aggregation Method for Event-Driven WSNs: A Modeling and Evaluation Approach

Kamarei

Hajimohammadi

Patooghy

et al. 2015

Wireless Pers Commun

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This paper proposes and models an efficient data aggregation method for wireless sensor networks (WSNs). In the proposed data aggregation method, every cluster head (CH) node incorporates a local forwarding history to decide whether to forward or to drop a recently received packet. When a new packet arrives at a CH node, a threshold value is calculated based on the information of the forwarding history; then, a random number is generated and compared with the threshold value to determine whether the packet should be dropped or not. In fact, the CH node forwards the new packet with the probability of 1 -p and drops it with probability of p where the parameter p is determined based on the forwarding history. In order The submitted manuscript is an extended version of the work previously proposed in [1]. The extensions of the current version include: (1) a wide range of simulation experiments added to the current version. To do this the proposed data aggregation method is compared with previously proposed methods i.e., RAG, SPEED, DASDR, and RDAG is terms of network performance, data aggregation rate, event miss rate. The previous version of the paper does not offer any comparison experiments, (2) an analytical performance model is proposed and validated in the paper. The proposed model estimates network performance, data aggregation rate, event miss rate of WSN using the proposed data aggregation method with an acceptable prediction error. The model provides a remarkable speed up in the evaluation process of data aggregation methods in the field of wireless sensor networks.to evaluate the proposed data aggregation method, two approaches consisting of simulation and analytical modeling are used. Various scenarios are considered in simulations conducted with NS2 software to compare the proposed data aggregation method with four previously proposed methods. Results reveal that the proposed method (1) aggregates more than 70 % of redundant packets, (2) reduces the network end-to-end delay by at least 22 %, and (3) reduces the missed event rate compared with the other methods. The proposed method is also evaluated by means of an analytical model based on queuing networks. The model accurately estimates the network performance utilizing the proposed data aggregation method. Comparisons of the results obtained by the proposed model and simulations confirm that the proposed model has at most 7 % prediction error. The proposed model allows WSN designers to easily achieve useful information about their networks before the establishment and manufacturing of the networks.

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Section: Analytical Modeling Of the Proposed Data Aggregation Methodsmentioning

confidence: 99%

“…1). Finally the top layer contains only of the sink node [23]. Obviously, in hierarchical WSN, CH nodes selection and cluster formation have a great impact on the network efficiency [24][25][26][27][28].…”

Section: Proposed Data Aggregation Methods (Llda)mentioning

confidence: 99%

An Efficient Data Aggregation Method for Event-Driven WSNs: A Modeling and Evaluation Approach

Kamarei

Hajimohammadi

Patooghy

et al. 2015

Wireless Pers Commun

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“…A Similar approach integrates a progressive reduction scheme based on binary decision diagrams for the reliability analysis and a divide-and-conquer approach for considering the effect of CCF [16]. Reliability of WSN for different topologies, routing protocols and metrics using fault trees have been proposed [17][18].…”

Section: Related Workmentioning

confidence: 99%

Modelling Failure Conditions in Zigbee based Wireless Sensor Networks

Singh¹,

Snigdh²

2017

IJWMT

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Reliable data transmissions in sensor networks are important for its longevity and require research attention. Since, fault tolerance and reliability become vital for embedded systems, estimating failure scenarios aid WSN applications to establish robust backup mechanisms in case of failures in the network. The article aims to model failure in IEEE 802.15.4 Zigbee networks in order to estimate the longevity of the network in context to the network connectivity. Ideally, IEEE 802.15.4 can manage two types of networks, the star topology or the peerto-peer topology. On combining these two we get a mesh network. Hence, the article presents the failure conditions for both star and mesh based network topology to the point where the network is disconnected owing to varied failure conditions.

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“…In our preliminary work of [11], the application communication reliability (ACR) was first formally defined and modeled. The ACR measure integrates the conventional connectivity-based network reliability with the sensing coverage measure of WSN.…”

mentioning

confidence: 99%

Application Communication Reliability of Wireless Sensor Networks Supporting K-coverage

Zonouz

Xing

Vokkarane

et al. 2013

2013 IEEE International Conference on Distributed Computing in Sensor Systems

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Application communication in wireless sensor networks (WSN) depends on two important factors: acquisition of sensed data from a specific area, and network connectivity that concerns the reliable delivery of the observed data from sensor nodes to the sink node. In this paper, we consider the application communication reliability (ACR) of WSN supporting K-coverage in the presence of shadowing for a specific monitored area. The analytical evaluation of ACR involves two steps. We first identify all the K-coverage sets. Then, we evaluate the communication reliability of delivering the observed data from sensor nodes within the identified K-coverage sets to the sink node. Two singlepath routing algorithms, shortest-path distance algorithm and shortest-path hop algorithm, are considered for evaluating the communication reliability during the second step; their performances in terms of ACR and energy consumptions are compared through an empirical analysis of several examples. Different scenarios are considered to evaluate the impact of node density, channel condition and different monitored areas on ACR. Simulation and analytical results show that WSN using the shortest-path distance algorithm is more reliable than that using the shortest-path hop algorithm in most cases, but WSN using the shortest-path hop algorithm consumes less energy for delivering the sensed data to the sink node.

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Infrastructure Communication Reliability of Wireless Sensor Networks

Cited by 46 publications

References 12 publications

An Efficient Data Aggregation Method for Event-Driven WSNs: A Modeling and Evaluation Approach

An Efficient Data Aggregation Method for Event-Driven WSNs: A Modeling and Evaluation Approach

Modelling Failure Conditions in Zigbee based Wireless Sensor Networks

Application Communication Reliability of Wireless Sensor Networks Supporting K-coverage

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