Elevating Localization Accuracy in Wireless Sensor Networks:A Refined DV-Hop Approach

Localization is crucial in wireless sensor networks for various applications,such as tracking objects in outdoor environments where GPS(Global Positioning System)or prior installed infrastructure is unavailable.However,traditional techniques involve many anchor nodes,increasing costs and reducing accuracy.Existing solutions do not address the selection of appropriate anchor nodes and selecting localized nodes as assistant anchor nodes for the localization process,which is a critical element in the localization process.Furthermore,an inaccurate average hop distance significantly affects localization accuracy.We propose an improved DV-Hop algorithm based on anchor sets(AS-IDV-Hop)to improve the localization accuracy.Through simulation analysis,we validated that the ASIDV-Hop proposed algorithm is more efficient in minimizing localization errors than existing studies.The ASIDV-Hop algorithm provides an efficient and cost-effective solution for localization in Wireless Sensor Networks.By strategically selecting anchor and assistant anchor nodes and rectifying the average hop distance,AS-IDV-Hop demonstrated superior performance,achieving a mean accuracy of approximately 1.59,which represents about 25.44%,38.28%,and 73.00%improvement over other algorithms,respectively.The estimated localization error is approximately 0.345,highlighting AS-IDV-Hop’s effectiveness.This substantial reduction in localization error underscores the advantages of implementing AS-IDV-Hop,particularly in complex scenarios requiring precise node localization.

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

Mobile ad-hoc networks （MANETs） and wireless sensor networks （WSNs） have gained remarkable apprecia- tion and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challeng- ing issue due to the nature of environments in which nodes operate. Nodes＇ physical capture, malicious or selfish behav- ior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recog- nition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the state- of-the-art into two groups namely node-centric trust mod- els and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assign- ments, we evaluate the efficacy of the existing schemes. Fi- nally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation manage- ment.

Interference-Aware Multipath Routing Protocol for QoS Improvement in Event-Driven Wireless Sensor Networks

The existing multipath routing protocols for wireless sensor networks demonstrate the efficacy of traffic distribution over multiple paths to fulfill the Quality of Service （QoS） requirements of different applications. However, the performance of these protocols is highly affected by the characteristics of the wireless channel and may be even inferior to the performance of single-path approaches. Specifically, when multiple adjacent paths are being used concurrently, the broadcast nature of wireless channels results in inter-path interference which significantly degrades end-to-end throughput. In this paper, we propose a Low- Interference Energy-efficient Multipath Routing protocol （LIEMRO） to improve the QoS requirements of event-driven applications. In addition, in order to optimize resource utilization over the established paths, LIEMRO employs a quality-based load balancing algorithm to regulate the amount of traffic injected into the paths. The performance gain of LIEMRO compared to the ETX-based single-path routing protocol is 85%, 80%, and 25% in terms of data delivery ratio, end-to-end throughput, and network lifetime, respectively. Furthermore, the end-to-end latency is improved more than 60%.