A quantitative fault tolerance evaluation model for topology in wireless sensor networks based on the semi-Markov process

2015 ◽  
Vol 149 ◽  
pp. 1014-1020 ◽  
Author(s):  
Rongrong Yin ◽  
Bin Liu ◽  
Haoran Liu ◽  
Yaqian Li ◽  
Mingru Dong
2010 ◽  
Vol 159 ◽  
pp. 29-34
Author(s):  
Shu Ming Xiong ◽  
Xiao Qian Qu ◽  
Yong Zhao Zhan ◽  
Xin Sheng Wang ◽  
Liang Min Wang

Due to the node failures incurred by intrusion threat, a wireless sensor networks will initiate topology re-generation, which is based on correct availability evaluation of current intrusion-tolerant topology. The paper proposes an availability evaluation model based on semi-Markov process (SMP) to estimate topology availability of the intrusion-tolerant topology concerning the effects from intrusion behaviors. In view of some limitations of node computation ability and storage ability, this model reduces the complexities resulting from modeling the different intrusion threats and is set up on the uniform intruding results to simplify the model design. Using the DTMC model embedded in SMP topology availability is computed and finally we analyze the sensitivity to parameters in the model.


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.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhiming Zhang ◽  
Yu Yang ◽  
Wei Yang ◽  
Fuying Wu ◽  
Ping Li ◽  
...  

The current detection schemes of malicious nodes mainly focus on how to detect and locate malicious nodes in a single path; however, for the reliability of data transmission, many sensor data are transmitted by multipath in wireless sensor networks. In order to detect and locate malicious nodes in multiple paths, in this paper, we present a homomorphic fingerprinting-based detection and location of malicious nodes (HFDLMN) scheme in wireless sensor networks. In the HFDLMN scheme, using homomorphic fingerprint and coding technology, the original data is divided into n packets and sent to the base station along n paths, respectively; the base station determines whether there are malicious nodes in each path by verifying the validity of the packets; if there are malicious nodes in one or more paths, the location algorithm of the malicious node is implemented to locate the specific malicious nodes in the path; if all the packets are valid, the original data is recovered. The HFDLMN scheme does not need any complex evaluation model to evaluate and calculate the trust value of the node, nor any monitoring nodes. Theoretical analysis results show that the HFDLMN scheme is secure and effective. The simulation results demonstrate promising outcomes with respect to key parameters such as the detection probability of the malicious path and the locating probability of the malicious node.


Author(s):  
Maytham Safar ◽  
Hasan Al-Hamadi ◽  
Dariush Ebrahimi

Wireless sensor networks (WSN) have emerged in many applications as a platform to collect data and monitor a specified area with minimal human intervention. The initial deployment of WSN sensors forms a network that consists of randomly distributed devices/nodes in a known space. Advancements have been made in low-power micro-electronic circuits, which have allowed WSN to be a feasible platform for many applications. However, there are two major concerns that govern the efficiency, availability, and functionality of the network—power consumption and fault tolerance. This paper introduces a new algorithm called Power Efficient Cluster Algorithm (PECA). The proposed algorithm reduces the power consumption required to setup the network. This is accomplished by effectively reducing the total number of radio transmission required in the network setup (deployment) phase. As a fault tolerance approach, the algorithm stores information about each node for easier recovery of the network should any node fail. The proposed algorithm is compared with the Self Organizing Sensor (SOS) algorithm; results show that PECA consumes significantly less power than SOS.


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