A combined decision fusion and channel coding scheme for distributed fault-tolerant classification in wireless sensor networks

2006 ◽  
Vol 5 (7) ◽  
pp. 1695-1705 ◽  
Author(s):  
Tsang-Yi Wang ◽  
Y.S. Han ◽  
Biao Chen ◽  
P.K. Varshney
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Channel Coding ◽  
Fault Tolerant ◽  
Decision Fusion ◽  
Wireless Sensor ◽  
Coding Scheme

scholarly journals Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Kezhong Liu ◽  
Yang Zhuang ◽  
Zhibo Wang ◽  
Jie Ma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Event Detection ◽  
Fault Tolerant ◽  
Decision Fusion ◽  
Wireless Sensor ◽  
Detection Accuracy ◽  
Fusion Algorithm ◽  
Detection Scheme ◽  
Spatiotemporal Correlation

Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. Existing fault-tolerant event detection approaches usually take the probability of faulty nodes into account and fusion techniques to weaken the influence of faulty readings are usually developed. Through extensive experiments, we discover a phenomenon that event detection accuracy degrades quickly when the faulty sensors ratio reaches a critical value. This problem has not drawn enough attention and a solution to the problem is our concern. In this paper, a spatiotemporal correlation based fault-tolerant event detection scheme (STFTED) is proposed, which leverages a two-stage decision fusion and spatiotemporal correlation to improve the event detection quality. In the low-level local stage, a location-based weighted voting scheme (LWVS) is developed to make decision fusion locally on each sensor node, which is based on neighboring nodes and the geographical distributions of two decision quorums. In the high-level global stage, a Bayesian fusion algorithm is adopted to reach a consensus among individual detection decisions made by sensor nodes. Simulation results demonstrate that the proposed approach is highly effective and a better quality of event detection can be obtained compared with the optimal threshold decision schemes (OTDS).

CODING AND INTERLEAVING SCHEMES FOR INFORMATION ACQUISITION FROM WIRELESS SENSOR NETWORKS

2013 ◽  
Vol 09 (03n04) ◽  
pp. 1350017
Author(s):  
M. E. MADKOUR ◽  
S. E. SOLIMAN ◽  
M. I. DESSOUKY ◽  
F. E. ABD EL-SAMIE
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Channel Coding ◽  
Information Acquisition ◽  
Detection System ◽  
Decision Fusion ◽  
Wireless Sensor ◽  
Modulation Scheme ◽  
Maximum Ratio Combining ◽  
Chaotic Baker Map

Transmission of data over wireless sensor networks (WSNs) poses significant constraints on the energy and bandwidth of the communication system. We consider the problem of decision fusion in a distributed detection system in a classical parallel fusion structure by incorporating the fading channel layer that is omnipresent in WSNs. We use channel coding and transmit diversity schemes, equal gain combining (EGC) and maximum ratio combining (MRC). We employ a multi-carrier modulation scheme over the wireless communication channel. This paper proposes the use of Hamming, low-density parity-check (LDPC) coding, or Viterbi coding. Interleaving is also suggested in this paper using chaotic Baker map randomization for the reduction of the bit error rate (BER). Moreover, the chaotic interleaving adds a degree of security to the transmitted data. Simulation results show that the application of coding and interleaving achieves a performance improvement in the WSN.

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

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