NLFFT: A Novel Fault Tolerance Model Using Artificial Intelligence to Improve Performance in Wireless Sensor Networks

Wireless Sensor Network (WSN) suffers from different malware attacks. Several traditional approaches are proposed for detecting fault nodes in WSN. It is necessary to redistribute the nodes and detect the fault nodes while modifying the WSN parameters. Faults can occur in the nodes interrupting the continuous communication process of the nodes in the WSN. The main reason for a fault is also the induction of the energy drain in a node to the maximum possible level, failure of links in communicating nodes due to bandwidth constraints, and attacks induced by the malicious nodes. To solve this problems, Extended Finite State Machine based Fault Tolerance (EFSM_FT) in the WSN is used to detect the fault sensor nodes in the WSN. In this approach, called the finite state machine (FSM), state prompted is modified while a set of situations are true. Every node can be absolutely to be faulty or not establishing on the sensor node states. Using sensor energy, drop rate, forward sensor rate, sensor obtained rate, bandwidth, and transmission delay, this method finds the node with the fault. As a result, this approach accurately detects the faulty nodes in the WSN. The simulation outcomes illustrate the proposed method has a better fault detection ratio and minimizes the false negative ratio in the WSN.

Due to adverse effects of hostile deployment environment(s), sensors nodes (SNs) deployed in the network may drain or get damaged. This attributes for loss of connectivity between the sensors and the sink node. Hence it is necessary to design the wireless sensor network (WSN) in a manner that the network is capable of coping up with the failure of few nodes/links. Using single hop data communication model reduces the lifetime of the network as the SNs are resource constrained (in terms of battery). Relay nodes (RNs) facilitate in improving network lifetime, fault tolerance and/or connectivity. Finding minimum number of relay nodes for a fault tolerant, fully connected network is a NP Hard problem. In this paper, we follow two phase relay node placement procedure to achieve the objective. In the first phase, we cluster the SNs using mean shift algorithm and place RNs as the cluster heads. In the second phase, we use metaheuristic algorithms like Moth Flame Optimization (MFO), Differential Evolution (DE), Bat algorithm (BA) and Biogeography Based Optimization algorithm (BBO) to place the RNs such that the required fault tolerance is achieved along with fully connected network. Extensive simulation results prove that MFO algorithm performs better for fault tolerant relay node placement problem.

Wireless Sensor Networks (WSN) have the potential of significantly enhancing our ability to monitor and interact with our physical environment. Realizing a fault-tolerant operation is critical to the success of WSN. The main challenge is providing fault-tolerance (FT) while conserving the limited resources of the network. Our main contribution in this paper is to propose a general framework for fault-tolerance in WSN. The proposed framework can be used to guide the design and development of FT solutions and to evaluate existing ones. We present a comparative study of the existing schemes and identify potential enhancements. A primary module of the framework is the learning and refinement module which enables a FT solution to be adaptive and self-configurable based on changes in the network conditions. We view this as vital to the resource-constrained and highly dynamic WSN. Up to our knowledge, we are the first to propose the implementation of such module in FT solutions for WSN.

Fault tolerance is the major issue in wireless sensor networks (WSNs). These networks are mobile in nature hence achieving fault free function in these networks is always a challenge. Therefore, need to diagnose these networks is very important for its graceful performance. In this paper, we have divided the fault diagnosis model into three major modules namely monitoring, detection and recovery. Extensive literature survey has been conducted to survey and analyze different techniques used in all these modules. Some open research problem areas have also been investigated. The given paper presents a comprehensive survey of techniques used to achieve fault tolerance in WSNs.

Applications of wireless sensor network face many censorious issues, fault tolerance being a prominent one. The problem of missing communication link(s), sensor node(s) and data is unavoidable in such networks. Fault tolerance is important for reliable delivery of data in WSN applications. This ensures the system’s availability for use in case of any interruption or occurrence of fault, thus enhancing the availability and reliability. Current work introduces the fault-tolerance behavior of a dynamically generated system of wireless sensor network that comprises of super-nodes and sensor nodes having k - vertex disjoint paths. As the parameters involved in the process of determination of fault-tolerance of a network change, the capacity of the network to tolerate the fault changes accordingly. This paper proposes an algorithm that evaluates the fault tolerance of randomly generated networks based on k - vertex disjoint path connectivity and also evaluates the results.

Wireless Sensor Networks (WSN), consists tiny but powerful devices to monitor or sense specific phenomena, e.g. temperature, visual, humidity etc. In WSNs nodes are deployed in the harsh and unattended environment. In such scenario, nodes may fail due to various reasons, e.g. link failure, battery depletion, hardware/software failure etc. In order to provide a reliable network, fault-tolerant network is required. Furthermore in WSN, energy is one of the major constraints, due to irreplaceable batteries. There have been various techniques proposed for fault tolerance and energy saving by detecting and correcting node failure. In this paper, the proposed algorithm called Cluster Head Fault Detection and Correction algorithm (FDFC), detects Cluster Head (CH) failure in a distributed manner and replace a faulty node. In this work, all the CHs present in network share status data with all the other CHs. Besides fault detection, this algorithm also suggests faulty node replacement technique. The effectiveness of the proposed algorithms is validated through simulation experiments.

This paper presents a neural model for reliable and fault tolerant transmission in Wireless Sensor Networks based on Bi-directional Associative Memory. The proposed model is an attempt to enhance the performances of both the cooperative and non cooperative Automatic Repeat Request (ARQ) schemes in terms of reliability and fault tolerance. We have also demonstrated the performances of both the schemes with the help of suitable examples.

An adaptive cellular automata scheme for diagnosis of fault tolerance and connectivity preserving in wireless sensor networks

Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN) NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH) is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH) is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling.

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

In this paper a procedure is proposed to construct a heterogeneous wireless Sensor network (WSN) that is both bi-directional and fault tolerant. Fault tolerance, is based on finding the k-best disjoint paths using trellis graph transformation. Recognizing limited energy in WSN's the proposed algorithm minimizes energy consumption. Simulation study reveals how metrics, such as average end to end delay, transmission overhead and throughput, compare for unidirectional and bidirectional graphs.

Wireless Sensor Networks (WSN) is of ubiquitous importance in the present day wireless communication. While disseminated architecture delights a more security and fault-tolerant WSN, such architecture also places a number of security challenges particularly when employed in vital applications such as health care, environment monitoring and battlefield. In this paper, we propose Trust Awaken Routing for Improving the Reliable Communication in WSN. The main objective of this paper is to develop trust management for WSNs, and this technique is used to improve the reliability of data transmission in the network. In this scheme, the trust Awaken Factor is used to select the reliable path from source to destination in the system. trust Awaken Factor computed by node interaction, node recommendation, quick response and node selfishness. The simulation results show the better improvement in throughput and reduce the network delay in the network.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The primary idea behind deploying sensor networks is to utilize the distributed sensing capability provided by tiny, low powered, and low cost devices. Multiple sensing devices can be used cooperatively and collaboratively to capture events or monitor space more effectively than a single sensing device. The realm of applications envisioned for sensor networks is diverse including military, aerospace, industrial, commercial, environmental, and health monitoring. Typical examples include: traffic monitoring of vehicles, cross-border infiltration detection and assessment, military reconnaissance and surveillance, target tracking, habitat monitoring, and structure monitoring, to name a few. Most of the applications envisioned with sensor networks demand highly reliable, accurate, and fault-tolerant data acquisition process. In this paper, we focus on innovative approaches to deal with multivariable, multispace problem domains (data integrity, energy-efficiency, and fault-tolerant framework) in wireless sensor networks and present novel ideas that have practical implementation in developing power-aware software components for designing robust networks of sensing devices. </para>

Connected dominated subsets (CDS) of nodes in wireless sensor network are always selected to form a virtual backbone. Construction of r-hop 2-connected dominating sets can reduce the size of CDS and the total amount of information to be transmitted. The 2-connected properties can provide higher fault tolerance and robustness as well. In this paper an approximation r-hop 2-connected dominating set algorithm for wireless sensor and ad-hoc networks is presented. The main strategy is partition to three phases: in the first phase, an r-hop independent dominating set is established; in the second phase, the r-hop dominating set is interconnected successively to form a connected subgraph; in the third phase, more vertices are selected and added into dominating set to make it 2-connected. Extensive simulations according to the algorithm steps have been conducted. Performance with detailed analysis has been shown at last.

Wireless Sensor Network (WSN) is one of the active research topics in the field of computer network since it provides three types of basic services: sensing, processing, and disseminating. Ad-hoc and multi-hop WSNs are commonly used in many applications; therefore, maintaining stability of WSN is an essential issue in present days. However, node failures are not exceptions in WSN. Many factors may cause sensor nodes to fail, such as energy exhaustion, out of communication range, or node module damage. These damages are usual incidents in practical WSN applications. Except node module damages that we are unable to look after, we propose an energy-efficient routing algorithm to prolong the lifetime of nodes in WSN. Another feature of the proposed algorithm is that each node routes network packets independently throughout the entire WSN. It makes that algorithm to provide autonomic management of the links in WSN.