Fault-tolerant Node Research Articles

A fault tolerant node placement algorithm for WSNs and IoT networks

The operation of Internet of Things (IoT) Network and Wireless Sensor Networks (WSNs) can be often disrupted by a number of factors, such as node faults, security attacks, as well as path disconnections. Despite any disruptions or any failures of network components the functionality and performance of the network should remain unaltered. An approach that can assist in resolving the above issues is the use of mobile nodes. In this work, we present a Fault Tolerant Node Placement Algorithm (FTNPA) that utilizes mobile nodes for addressing failures in the network. We initially propose a Mobile Fault Tolerant (MobileFT) Framework, that supplies the two main functionalities of the Fault Tolerant Node Placement Algorithm (FTNPA), which are the detection and the recovery. Then, we present two variations of the FTNPA algorithm, the Decentralized FTNPA and the Centralized FTNPA. The first variation uses a decentralized detection method, where the detection is performed by the neighboring nodes in the network, as well as a local recovery method, where a mobile node is placed in a certain position to assist the affected area. Whereas, the second variation employs a centralized detection method, where the sink is responsible for the detection, and a recovery method that creates alternatives paths of mobile nodes towards a destination node. Simulation results show that the proposed algorithms can significantly contribute to the detection and recovery of faults in IoT Networks and WSNs.

Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services

Blockchain-based healthcare IoT technology research enhances security for smart healthcare services such as real-time monitoring and remote disease diagnosis. To incentivize positive behavior among participants within a blockchain-based smart healthcare system, existing efforts employ benefit distribution and reputation assessment methods to enhance performance. Yet, there remains a significant gap in multidimensional assessment strategies and consensus improvements in addressing complex healthcare scenarios. In this paper, we propose a blockchain and trusted reputation assessment-based incentive mechanism for healthcare services (BtRaI). BtRaI provides a realistic and comprehensive reputation assessment with feedback to motivate blockchain consensus node participation, thus effectively defending against malicious behavior in the healthcare service system. Specifically, BtRaI first introduces multiple moderation factors for comprehensive multidimensional reputation assessment and credibly records the assessment results on the blockchain. Then, we propose an improved PBFT algorithm, grounded in the reputation assessment, to augment blockchain consensus efficiency. Finally, BtRaI designs a token-based reward and punishment mechanism to motivate honest participation in the blockchain, inhibit potential misbehavior, and promote enhanced service quality in the healthcare system. Theoretical analysis and simulation experiments conducted across various scenarios demonstrate that BtRaI effectively suppresses malicious attacks in healthcare services, improves blockchain node fault tolerance rates, and achieves blockchain transaction processing efficiency within 0.5 s in a 100-node consortium chain. BtRaI’s reputation assessment and token incentive mechanism, characterized by realistic differentiation granularity and change curves, are well-suited for dynamic and complex healthcare service environments.

A Fault-Tolerant Model for Performance Optimization of a Fog Computing System

In a distributed heterogeneous fog environment, fog nodes may change their state at any time. Their reliability changes accordingly. A dynamic analysis of state changes can help one detect fault-tolerant fog nodes, which is conducive to promoting the reliability of fog services. This article proposes a fault-tolerant model based on a Markov chain for a fog system’s performance optimization. The real-time reliability of fog nodes is analyzed by using dynamic distributed parameters. Thus, the state transition process of fog nodes is modeled with a continuous-time Markov chain. The steady-state probability of a fog system is analyzed. Then, a fault-tolerant strategy and its algorithms are designed to select nodes with the minimum cost based on their steady-state probabilities. The proposed method can predict the number of faulty ones of a fog system via the steady-state probability. An intelligent optimization method called simulated annealing (ISA) is designed and used to select the most appropriate fog nodes to substitute faulty ones. The experimental results show that the method is feasible and effective for selecting the right fault-tolerant nodes according to different performance requirements. ISA can well outperform such methods as random selection, discrete differential evolution, and simulated annealing in terms of cost and time.

Largest Component and Node Fault Tolerance for Grids

A graph $G$ is called $t$-node fault tolerant with respect to $H$ if $G$ still contains a subgraph isomorphic to $H$ after removing any $t$ of its vertices. The least value of $|E(G)|-|E(H)|$ among all such graphs $G$ is denoted by $\Delta(t,H)$. We study fault tolerance with respect to some natural architectures of a computer network, i.e. the $d$-dimensional toroidal grids and the hypercubes. We provide the first non-trivial lower bounds for $\Delta(1,H)$ in these cases. For this aim we establish a general connection between the notion of fault tolerance and the size of a largest component of a graph. In particular, we give for all values of $k$ (and $n$) a lower bound on the order of the largest component of any graph obtained from $C_n\Box C_n$ via removal of $k$ of its vertices, which is in general optimal.

Reliable Mobile Edge Service Offloading Based on P2P Distributed Networks

Intelligent vehicles and their applications increasingly demand high computing power and low task delays, which poses significant challenges for providing reliable and efficient vehicle services. Mobile edge computing (MEC) is a new model that reduces the completion time of tasks and improves vehicle service by performing computation offloading near the moving vehicles. Considering the high-speed mobility of the vehicles and the unstable connection of the wireless cellular network, symmetric and geographically distributed edge servers are regarded as peers in a peer-to-peer (P2P) network, and a P2P-based vehicle edge offloading model is proposed in this paper to determine the optimal offloading server for the vehicle and the offloading ratio of tasks to achieve the goal of minimizing execution time. Because the edge computing infrastructure is deployed at the edge of the network, the data in the edge nodes are easily damaged or lost. Therefore, a P2P-based edge node fault tolerance mechanism is proposed to improve the reliability and fault tolerance of the system. The feasibility and effectiveness of our proposed system have been verified through simulation experiments, which greatly reduces the task completion delay.

Node set optimization problem for complete Josephus cubes

The problem of finding an optimal node set in an interconnection network plays an important role in minimizing the layout of embedding the network into linear chassis. In this paper we find the nested optimal node sets for a complete Josephus cube, a recently proposed fault-tolerant node cluster architecture variant of the binary hypercube which has the same number of nodes as the hypercube but exhibits enhanced embedding, fault tolerance and communications performance than the hypercube and many of its variants. As a byproduct we obtain the minimum layout of embedding the complete Josephus cube into a path, 1-rooted complete binary tree, sibling tree and caterpillar.

Master node fault tolerance in distributed big data processing clusters

Distributed computing clusters are often built with commodity hardware which leads to periodic failures of processing nodes due to relatively low reliability of such hardware. While worker node fault-tolerance is straightforward, fault tolerance of master node poses a bigger challenge. In this paper master node failure handling is based on the concept of master and worker roles that can be dynamically re-assigned to cluster nodes along with maintaining a backup of the master node state on one of worker nodes. In such case no special component is needed to monitor the health of the cluster while master node failures can be resolved except for the cases of simultaneous failure of master and backup. We present experimental evaluation of the technique implementation, show benchmarks demonstrating that a failure of a master does not affect running job, and a failure of backup results in re-computation of only the last job step.

Development of sensor nodes based on fault tolerance

In the present paper, and a fail-safe system capable of operating in safety side even upon occurrence of failures was designed where internet of things (IoTs)-based sensor nodes allowed fault tolerance based on hardware redundancy. The fault tolerance system masked faults with the application of triple modular redundancy (TMR) system and enabled fail-safe control by using a comparator for fault detection and self-diagnostics. The fault-tolerant sensor nodes presented in the paper were installed outdoors where disasters/calamities could occur and could execute the specified algorithms even upon occurrence of faults allowing the use in areas with poor environments and particularly the application to plant facilities for management of oil and gas pipelines, etc. as the high reliability could be guaranteed.

A Reliable and Fault Tolerant Job Scheduling System in Market-Based Grids Using Case-Based Reasoning Method

In market-based Grid systems, a main aim is to execute jobs with considered quality of service requirements based on user defined budget. Since grid has heterogonous resource with unpredictable faults, the user cost constraints and expected service requirements may not provided. Therefore, using a better approach to resource scheduling to reduce fault is necessary. This paper presents a predictive approach on fault tolerance mechanisms for faultless job scheduling on market-based grids. The Case-Based Reasoning technique has been used for selecting fault tolerant nodes. This approach applies a specific structure in order to prepare fault tolerance between provider nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.

Fault-Tolerant Event Monitoring in Wireless Sensor Networks

Event monitoring is an important issue in wireless sensor networks,however,the limits of sensor networks and the uncertainty existed in sensed data propose challenges for it.This paper analyzes the uncertainty existed in sensor networks and presents fault-tolerant event monitoring mechanism.We first introduce the fault-tolerant event detection and monitoring nodes choosing algorithms,and then estimate the event appearing area under the condition of static sensor nodes and moving sensor nodes.Finally,we evaluate our algorithms via a serial of simulations.The experimental results show that the proposed algorithms can obtain optimal performance in event monitoring.

An Efficient Constructive Approximation Approach to Design A K-Connected Network Topology

The purpose of designing an optimal and fault tolerant communication network is to achieve a precise performance without any disruption at a minimal cost. A network is said to be k- link fault tolerant (nodes are assumed reliable) if it is able to maintain connectivity in the presence of failures in any set of arbitrarily k links simultaneously. Communication network topology design cost depends on the number of the links used to design a desired fault tolerant communication network and is equal to the sum of the cost of all required links. The main objective of a fault tolerant network design approach is therefore to select the minimum number of low cost links while satisfying the pre-specified fault tolerance/connectivity. It has also been proved that designing a minimum cost communication network topology under the connectivity constraint is a NP hard problem. Several constructive approximation algorithms have be enproposed to design a fault tolerant network topology. But the existing algorithms are not so much effective for selecting minimum number of low cost links to design a computer network topology. In this paper, we have proposed an efficient constructive approximation approach for designing a k – connected network which is survivable in the presence of k-1 links failures in the network. The design cost and number of links required to design such network using proposed approach is less than the existing approaches. Effectiveness of proposed approach is also checked using various examples.

Relay node placement and addition algorithms in wireless sensor networks

The node placement is the foundation of network operation in wireless sensor networks. In many applications, the positions of gateway node and sensor node are relatively fixed. To guarantee network connectivity and reliability, some relay nodes must be reasonably placed between the gateway node and the sensor node. In the context of the above applications, we introduce many constraint conditions into the existing placement model, and adopt a hybrid placement method based on enumeration and greedy optimization algorithms to determine relay node positions from their candidate location sets, and we finally achieve the relay node initial placement and follow-up adjustment strategies, owing to new sensor nodes joining the current network. The simulation results demonstrate that our operable and optimized relay node placement algorithm can ensure multi-restricted fault-tolerant relay node placement, and the presented new evaluation standard based on the minimum distance factor can significantly improve the energy-efficiency of relay node placement algorithm.

An Architecture for a Dependable Distributed Sensor System

In future smart environments, mobile applications will find a dynamically varying number of networked sensors that offer their measurement data. This additional information supports mobile applications in operating faster, with a higher precision and enhanced safety. The potentially increased redundancy obtained in such scenarios, however, is seriously affected by additional uncertainties as well. First, the dependence on wireless communication introduces new latencies and faults, as well as errors, and second, sensors of the environment may be disturbed, of low quality, or even faulty. The quality of the collected data therefore has to be dynamically assessed. Our work aims to provide a generic programming abstraction for fault-tolerant sensors and fusion nodes that cope with varying quality of measurements and communication.

A Fault-tolerant Adaptive Node Scheduling Scheme for Wireless Sensor Networks *

In wireless sensor networks, the limited battery resources of sensor nodes have a direct impact on network lifetime. To improve energy efficiency, there have been a variety of sensor node scheduling methods to keep only a minimum number of sensor nodes in active mode. However, those existing sensor node scheduling methods mainly focus on the coverage problems, largely ignoring the fault-tolerance issues. In this paper, we proposes a new fault-tolerant sensor node scheduling algorithm, called FANS (Fault-tolerant Adaptive Node Scheduling), that does consider not only sensing coverage but also sensing level. The proposed FANS algorithm enables to preserve sensing coverage, maximize network lifetime and achieve energy efficiency. Experimental results show that the FANS algorithm provides enhanced performance in terms of sensing coverage, energy consumption and the number of control messages.

Developing dual-surveillance based networks for intelligent tunnel management

Although more than 100-kilometer-long tunnel structures are considered in many areas including the Taiwan Strait, the risk challenges of long tunnels, including sabotage / terrorism, need be concerned accordingly. Hence, establishing SCADA networks with distributed intelligence and real-time fault-tolerance mechanism is worthwhile for long tunnels. Besides, the dual-surveillance system can be featured with better functionality just as the human beings can have better vision by two eyes instead of by one in addition to node fault-tolerance. For professionals' interest, the features of the bipartite GHT network are proofed with graphs: GHT(m,n,0) / GHT(m,n,n/2) is 1-edge hamiltonian if n greater than or equal to.4, and GHT(m,n,0) / GHT(m,n,n/2) is 1p-hamiltonian if and only if either n greater than or equal to 6 or m = 2 and n greater than or equal to 4. Therefore, the proposed GHT-SCADA network prototypes can be dual-surveillance based, with optimal degree (3 connected links to a node) and have both nodes' and links' fault-tolerance as well as a mechanism supporting orderly inspection and maintenance. Such reliable SCADA networks are not only for preventing disasters, but also actively for best judgment and control of incidents in tunnels. (A) This paper was presented at Safety in the underground space - Proceedings of the ITA-AITES 2006 World Tunnel Congress and the 32nd ITA General Assembly, Seoul, Korea, 22-27 April 2006. For the covering abstract see ITRD E129148. Reprinted with permission from Elsevier.

Fault-tolerance of Complete Josephus Cubes

The Complete Josephus Cube is proposed as a fault-tolerant node cluster architecture A reliable and cost-effective communications strategy is also presented. For a Complete Josephus Cube of dimension r, the strategy tolerates up to (r + 1) encountered faults in its routes that are deadlock-free and livelock-free. The message is optimally (respectively, sub-optimally) delivered in at most r (respectively, 2r + 1) hops. Message overhead is one of the lowest reported for the specified fault tolerance--with only a single (r + 2)-bit routing vector accompanying the message to be communicated. Associated routing hardware may be implemented with standard logic.

Reliability and safety analysis of fault tolerant and fail safe node for use in a railway signalling system

In this paper, we propose a Markov Reliability model for a transputer based fail safe and fault tolerant node for use in a network of distributed safety critical railway signalling systems. Using the Markov model we quantify the reliability and safety in terms of Probability of being in unsafe state, Probability of Safe shutdown during the useful life period and last phase of bath-tub curve. A fault analysis of the fail safe and fault tolerant node addressing Byzantine (malicious) faults with an extension of Byzantine General's problem is given.

Node fault tolerance in graphs

A graph G* is a k-node fault-tolerant supergraph of a graph G, denoted k-NFT (G), if every graph obtained by removing k nodes from G* contains G. A k-NFT (G) graph G* is said to be optimal if it contains n + k nodes, where n is the number of nodes of G and G* has the minimum number of edges among all (n + k)-node k-NFT supergraphs of G. We survey prior results on the design of optimal k-NFT supergraphs of various useful forms of G; this work covers cycles and various types of trees. We also introduce the concept of exact node fault tolerance, which requires that every graph obtained by removing k nodes from G* be isomorphic to G, and explore its basic properties. We conclude with a discussion of some unsolved and partially solved problems. © 1996 John Wiley & Sons, Inc.

One node fault tolerance for caterpillars and starlike trees

For a given tree T with n nodes, we say that a supergraph G tolerates T (having one faulty node) if for each node u of G the subgraph G-u contains T up to isomorphism. Then G tolerates T optimally if G has just one new node and no supergraph of T with n + 1 nodes having fewer edges than G tolerates T. The one-node fault tolerance edge cost of T is the number of new edges in G. We derive theorems which determine this cost exactly for two type of trees, namely, caterpillar and starlike trees.

Resource allocation for primary-site fault-tolerant systems

Resource allocation for a distributed system employing the primary site approach for fault tolerance is discussed. Two kinds of systems are considered. The first consists of fault-tolerant nodes where each node has many duplicated servers. One server is the primary, which serves user requests, and the rest are backup. The second does not have fault-tolerant nodes. To tolerate node failures, each node uses other nodes as backups. When a node fails, all requests initially allocated to the node are served by one of its backups. To study the resource allocation for such systems, an approximate model for each system is developed. Using these models, efficient allocation algorithms that take into account the failure/repair rates of the system and the fault-tolerant overheads are presented. Using experimental results, it is shown that the algorithms give the optimal or suboptimal allocations. The algorithms, which incur little overhead, can improve the system performance significantly over an intuitive allocation algorithm.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>