Minimal path sets models for reliability computation of wireless sensor networks

In this paper we consider the problem of modeling and evaluating the infrastructure communication reliability (ICR) of wireless sensor networks (WSN). Our approach is progressive and based on reduced ordered binary decision diagrams (ROBDD). Due to the nature of the ROBDD and the reduction scheme used in the progressive process, the approach is computationally efficient and is easy to implement. We also incorporate the consideration of common cause failures (CCF) into the reliability analysis of WSN. We illustrate the application and advantages of our approach by working through the analysis of an example WSN

A new hierarchical belief-rule-based method for reliability evaluation of wireless sensor network

In this short note we give and discuss a general multilinear expression of the structure function of an arbitrary semicoherent system in terms of its minimal path and cut sets. We also examine the link between the number of minimal path and cut sets consisting of 1 or 2 components and the concept of structure signature of the system.

In this study a model for data reliability in wireless sensor networks is proposed, in which machine learning methods are used. Proposed framework includes data modelling, missing data prediction, anomaly detection, data fusion and trust mechanism phases. Thus, temporal analysis is performed on the preprocessed sensor data and missing data are predicated. Then outliers on collected data are detected on the cluster head nodes by using Eta one-class Support Vector Machines. If an event is detected data are fused and then send to sink. If an anomaly is detected for a node's data, the trust weight of the node is decreased.

Wireless sensor networks are used for sensing data if wired communication is not suitable. Connection losses and depletion of nodes, however, result in reduced data availability of such networks. This is problematic in upcoming scenarios like health care or home automation where data availability is highly important. In this paper, we present an approach to provide robust data storage for wireless sensor networks. We achieve this goal by providing FAME-DBMS, a customizable database management system which can be tailored according to the varying requirements of a sensor network. FAME-DBMS provides reliable data storage using security and integrity features, transaction management and recovery and a customizable query engine. Since data reliability in wireless sensor networks also suffers from node failures, we propose a new S - RAID storage layer inspired from the RAID approach of server systems. This S-RAID is integrated in FAME-DBMS to store data redundantly and distributed in a wireless sensor network and thus provides access to data even when nodes fail.

The emergence of Wireless Sensor Networks has enabled the detection of potentially dangerous or catastrophic events prior to their actual occurrence. Wireless Sensor Networks rely on sensors that collect data on environmental conditions, allowing an early warning system to be implemented for potentially dangerous or catastrophic events, enabling an organization to take actions to prevent or mitigate these types of events. The technology digital twin has potential to improve ability of a wireless sensor network to detect faults and recover from them before the fault occurs. Digital Twins are real-time representations of physical objects or systems that track activity and behaviour of that physical object or system. By combining the Digital Twin with a Wireless Sensor Network, it is possible to create a model of predictive maintenance that can detect potential fault conditions before they occur by utilizing fault-analysis techniques. By utilizing this model to improve the Wireless Sensor Network, it is possible to improve the reliability and reduce the incidence of natural disasters. This report describes how Digital Twins can be created and how they can be used in Predictive Maintenance to increase the reliability of wireless sensor networks. These findings illustrate the power of such an AI-based approach toward completely transforming fault management within WSNs, toward being more robust, efficient, and reliable sensor networks in today's world.

Design of reliable wireless sensor network (WSN) needs to address the failure of single or multiple network components and implementation of the techniques to tolerate the faults occurred at various levels. The issues and requirements of reliability improvement mechanism depend on the available resources and application for which the WSN is deployed. This paper discusses the different modeling approaches to evaluate the reliability and classification of the approaches to improve it. Also the paper analyzes reliability enhancement by existing fault tolerant methods in WSN and compares the performance of these techniques with the technique we developed. From the results of the analysis we highlight the challenges and the characteristics of the sensor network affects the reliability and give some scope of future research directions in order to enhance reliability.

A wireless sensor network (WSN) (singular and plural of acronyms are spelled the same) is a distributed system composed of autonomous sensor nodes wireless connected and randomly scattered into a geographical area to cooperatively monitor physical or environmental conditions. Adequate techniques and strategies are required to manage a WSN so that it works properly, observing specific quantities and metrics to evaluate the WSN operational conditions. Among them, one of the most important is the reliability. Considering a WSN as a system composed of sensor nodes the system reliability approach can be applied, thus expressing the WSN reliability in terms of its nodes' reliability. More specifically, since often standby power management policies are applied at node level and interferences among nodes may arise, a WSN can be considered as a dynamic system. In this article we therefore consider the WSN reliability evaluation problem from the dynamic system reliability perspective. Static–structural interactions are specified by the WSN topology. Sleep/wake-up standby policies and interferences due to wireless communications can be instead considered as dynamic aspects. Thus, in order to represent and to evaluate the WSN reliability, we use dynamic reliability block diagrams and Petri nets. The proposed technique allows to overcome the limits of Markov models when considering non-linear discharge processes, since they cannot adequately represent the aging processes. In order to demonstrate the effectiveness of the technique, we investigate some specific WSN network topologies, providing guidelines for their representation and evaluation.

One of the remarkable challenges in the area of Wireless Sensor Networks (WSNs) is how to route the collected data and transfer them in the nodes. Due to the high rate of packet loss, guaranteeing reliable and efficient packet transfer and delivery is considered to be one of the hot issues in the area of WSNs. Indeed, due to energy limitation of nodes in WSNs, reliability and energy are regarded as critical parameters in these networks. In this paper, a method has been proposed for optimizing the parameters of reliability and energy consumption in multimedia WSNs. In the proposed protocol, Increasing the Delivery Ratio with Network Coding (IDRNC) a network coding mechanism has been used for transmitting data which enhances the reliability of the network. Furthermore, reducing the number of transmissions and receptions in network nodes results in the reduction of energy consumption. In the proposed protocol, the transmitted packets are first coded and transmitted to the sink through the shortest route. In the middle of the route, in case packets are lost, median nodes can detect and recover the lost packet through the coded packet. The simulation results indicated that the method proposed in this study operates better than the LIEMRO method with respect to the following features: system efficiency, average remaining energy of the network, the number of lost packets and reliability. Keywords: Multipath Routing, Network Coding, Reliability, Wireless Multimedia Sensor Networks (WMSNs)

In order to improve the communication reliability of wireless sensor networks, a wireless sensor network access authentication system based on embedded microcontroller is designed. Design the overall structure and hardware configuration of wireless sensor network access authentication system, and collect the information of sensor nodes; Creatively based on the duapii protocol, the node trust is calculated according to the node behavior, and the dynamic access authentication of wireless sensor network users is realized through the authentication and login process. According to the system test results, the designed system can realize the access authentication of wireless sensor networks. When the wireless sensor network is attacked by different types of attacks, the communication delay is less than 100 ms, which improves the reliability of network communication.

WITHDRAWN: Developing a software reliability evaluation model for wireless sensor networks based on analysis of software fault growth

In order to improve the throughput and transmission reliability in wireless sensor network with limited resources, multicast network coding technology is imported in. On this basis, through random linear network coding by nodes' cooperation to make improvement in delayed and expense. The simulation results show that the transmission, to the opportunity routing, by cooperation network coding strategies is improved in making full use of space-time reusability, reducing the delay and enhancing the throughput and transmission reliability of wireless sensor network.

Energy efficiency is a key parameter in the design of wireless sensor networks (WSNs). Sensor nodes are generally operated by using batteries of limited capacity. To achieve energy efficiency, a reduction in radio communication is necessary. The communication unit consumes the major power in a wireless sensor node. Reduction in power consumption to make reliable wireless sensor networks, due to the exchange of data between sensor nodes can be attained with the help of data compression approach. A lossless data compression (LDC) approach is proposed to attain reliability in wireless sensor networks. Compression schemes have advantages that they can allow dynamical adjustment for the change in source data statistics for performance maximization. The proposed algorithm requires less computational power and its effectiveness has been computed by compression of temperature and relative humidity data sets gathered by real WSNs. The compression ratio has been obtained up to 73.54% and 61.82% for temperature and relative humidity data sets.

Existing flooding algorithms have demonstrated their effectiveness in achieving communication efficiency and reliability in wireless sensor networks. However, further performance improvement has been hampered by the assumption of link independence, a design premise imposing the need for costly acknowledgements (ACKs) from every receiver. In this paper, we present Collective Flooding (CF), which exploits the link correlation to achieve flooding reliability using the concept of collective ACKs. CF requires only 1-hop information from a sender, making the design highly distributed and scalable with low complexity. We evaluate CF extensively in real-world settings, using three different types of testbeds: a single hop network with 20 MICAz nodes, a multihop network with 37 nodes, and a linear outdoor network with 48 nodes along a 326-meter-long bridge. System evaluation and extensive simulation show that CF achieves the same reliability as the state-of-the art solutions, while reducing the total number of packet transmission and dissemination delay by 30 - 50% and 35 - 50%, respectively.

Reliability evaluation can help to minimize costs and maximize reliability of wireless sensor networks (WSN). To evaluate the reliability of WSN, a mathematical model and an enhanced factoring (EF) algorithm are presented in this paper. Being different from traditional factoring algorithm, the node contraction is enhanced by source expansion and the isomorphic sub-networks are identified. These operations can help to decrease the number of repeated computations and make the reliability computing fast. The traditional factoring algorithm and EF are compared in experiments, and the results show EF is more efficient than traditional factoring for large size network.