Fault Tolerance Mechanisms Research Articles

Energy aware fault tolerant clustering with routing protocol for improved survivability in wireless sensor networks

Wireless Sensor Networks (WSN) remain a hot research topic due to its wide range of application areas like environmental monitoring, military surveillance, healthcare, and disaster management. Network survivability is one of the challenging issues in WSN that needs to be maximized for long-run operation of the network. It can be proficiently improved by effective utilization of available energy since the nodes in WSN operate only via in-built batteries. The studies conducted earlier have mainly focused on the design of clustering and routing protocols to reduce energy consumption in the network. With this motivation, the current research paper presents a novel Energy-Aware Fault Tolerant Clustering with Routing for Improved Survivability (EAFTC-RIS) technique in WSN. The proposed EAFTC-RIS technique intends to select the Cluster Heads (CHs) and optimal routes to the destination in an optimal manner with fault tolerant mechanism. The proposed EAFTC-RIS technique primarily designs Moth Flame Optimization (MFO)-based clustering scheme for CH selection and cluster construction. Also, fault tolerant mechanism is considered to further enhance the survivability of the network. In addition, Social Spider Optimization (SSO)-based routing approach is also employed for optimal selection of routes in WSN. Clustering, routing, and fault tolerant mechanism designs, with multiple input variables, result in enhanced network survivability. The proposed EAFTC-RIS technique was validated for its performance and the outcomes were inspected under various aspects. The simulation outcomes demonstrate the superiority of EAFTC-RIS technique over recent approaches namely, EAFTC-RIS, FUCCAR-GWSO, FBECS, MLSLEEP, and Bee Cluster.

Fault-tolerant control for T-S fuzzy systems with an aperiodic adaptive event-triggered sampling

This article investigates the exponential stabilization problem for Takagi-Sugeno (T-S) fuzzy systems with actuator faults and aperiodic sampling. First, the fault-tolerant control is designed for T-S fuzzy systems under the given actuator fault model. Second, unlike the existing periodic mechanisms, an improved aperiodic adaptive event-triggered (AET) control scheme is established. The threshold is updated adaptively during the sampling process, which greatly reduces the amount of information transmitted. Then, based on Lyapunov-Krasovskii functional (LKF) method, two sufficient exponential stability conditions are derived. In order to derive the less conservative result, a two-sided looped-functional is constructed. In addition, according to stability conditions and fault-tolerant mechanism, the corresponding sampled-data controller is designed. Finally, a numerical example and a simplified gas turbine system are employed to demonstrate the virtue and effectiveness of application of the proposed scheme.

CyberChain: Cybertwin Empowered Blockchain for Lightweight and Privacy-Preserving Authentication in Internet of Vehicles

Internet of Vehicles (IoVs) presents promising opportunities for vehicle to everything (V2X) applications, wherein authentication acts as the cornerstone to realize trustworthy vehicular context and to support advanced applications. However, existing authentication schemes mainly depend on centralized servers with both security and privacy issues. In this paper, we propose a CyberTwin (CT) empowered blockchain framework for authentication, namely CyberChain, to reduce both the communication and storage cost while maintaining vehicular privacy. By designing a blockchain system in the cyberspace, we decouple the consensus process from the physical world, so that the operation cost of blockchain can be reduced. A Privacy-Preserving Parallel Pedersen Commitment (P4C) algorithm is designed to protect the privacy of vehicles and accelerate the authentication process. To further enhance the operation efficiency of CyberChain, we propose a Diffused Practical Byzantine Fault Tolerance (DPBFT) mechanism to reach consensus in the cyberspace that can reduce consensus latency. The proposed cyberchain framework and the associated mechanisms are evaluated by qualitative analysis and simulations. The evaluation results demonstrated that the proposed cyberchain based framework significantly improves the authentication performance in terms of authentication latency, privacy, communication overhead and storage cost.

Privacy-preserving statistical analysis over multi-dimensional aggregated data in edge computing-based smart grid systems

Smart grid systems enable bidirectional data communication between users and a smart grid control center (CC), by utilizing various communication infrastructures and embedded devices. To extract valuable information from users’ power consumption data efficiently, multi-dimensional data of users are required to be analyzed deeply. To protect users’ privacy, power consumption data are usually encrypted before transmission, which simultaneously makes it difficult to conduct statistical analysis. In this paper, we propose a scheme which enables privacy-preserving statistical analysis over multi-dimensional aggregated data (SA-MAD) in smart grid systems equipped with edge computing. We modify Boneh–Goh–Nissim (BGN) public key cryptosystem to a dual-message encryption mode, combining with two special superincreasing sequences to deal with multi-dimensional encrypted data aggregation. Besides, we design an identity-based aggregate signature to ensure encrypted data integrity in smart grid systems, and employ shamir secret sharing technique to support transmission fault-tolerance mechanism from smart meters to corresponding edge servers. SA-MAD enables CC to flexibly conduct privacy-preserving statistical analysis (e.g., sum, average, and variance) over aggregated data, and it could be easily extended to support covariance and linear regression computation. The performance evaluation demonstrates the feasibility of SA-MAD in edge computing-based smart grid systems.

Architecture for Fault Tolerance in Mobile Cloud Computing using Disease Resistance Approach

The mobile cloud computing (MCC) is one of the emerging fields in the distributed computing. MCC is an integration of both mobile computing and cloud computing. The limitations of the mobile devices are storage, battery and processing proficiency.These sensitive characteristics of mobile devices can be effectively handled with the introduction of cloud computing. The increasing functionality of the cloud and complexity of the applications causes resource failures in the cloud computing and it reduces the overall performance of the MCC environment. On the other hand, the existing approaches for resource scheduling in MCC proposed several architectures and they are only concentrated on the allocation of resources. The existing architectures are lack of fault tolerance mechanism to handle the faulty resources. To overcome the issues stated above, this paper proposes architecture for fault tolerance in MCC using Disease Resistance approach (DRFT). The main aim of the DRFT approach is to effectively handle the faultyVMs in the MCC. This DRFT approach utilizes the human disease resistance mechanism which is used as materials and methods in the proposed model. The DRFT is capable of identifying the faulty virtual machines and reschedules the tasks to the identified suitable virtual machines. This procedure ultimately leads to minimization of makespan value and it improves the overall performance of the scheduling process. To validate the effectiveness of the proposed approach, a series of simulations has been carried out using CloudSim simulator. The performance of the proposed DRFT approach is compared with the Dynamic group based fault tolerance approach (DGFT-approach). The makespan value of DRFT is reduced to 7% and the performance of DRFT is increased when compare to the DGFT approach. The experimental results show the effectiveness of the proposed approach.

Distributed Fault-Tolerant Algorithm for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are a set of tiny autonomous and interconnected devices. These nodes are scattered in a region of interest to collect information about the surrounding environment depending on the intended application. In many applications, the network is deployed in harsh environments such as battlefield where the nodes are susceptible to damage. In addition, nodes may fail due to energy depletion and breakdown in the onboard electronics. The failure of nodes may leave some areas uncovered and degrade the fidelity of the collected data. Therefore, establish a fault-tolerant mechanism is very crucial. Given the resource-constrained setup, this mechanism should impose the least overhead and performance impact. This paper focuses on recovery process after a fault detection phase in WSNs. We present an algorithm to recover faulty node called Distributed Fault-Tolerant Algorithm (DFTA).The performance evaluation is tested through simulation to evaluate some factors such as: Packet delivery ratio, control overhead, memory overhead and fault recovery delay. We compared our results with referenced algorithm: Fault Detection in Wireless Sensor Networks (FDWSN), and found that our DFTA performance outperforms that of FDWSN.

Reinforced cost effective architecture for fault tolerance mechanism through meta heuristics

Grid computing removes the limitations that exist in traditional shared computing environment, and becomes a leading trend in distributed computing system. It aggregate heterogeneous resources distributed across Internet, regardless of differences between resources such as platform, hardware, software, architecture, language, and geographical location. Such resources, which include computing, storage, data, communication bandwidth resources and other resources, are combined dynamically to form high performance computing capability of solving problems in large-scale applications. Dynamically sharing resources gives rise to resource contention. One of the challenging problems is deciding the destination nodes where the tasks of grid application are to be executed. From the perspective of system architecture, resource allocation and job scheduling are the most crucial functions of grid computing. Resource allocation and job scheduling are the core functions of grid computing. These functions are based on adequate information of available resources. Timely acquiring resource status information is of great importance in ensuring overall performance of grid computing. This work aims at building a distributed system for grid resource monitoring and prediction. Major achievements include the design and evaluation of system architecture for grid resource monitoring and prediction through Meta heuristic conditions.

Microgrid Data Security Sharing Method Based on Blockchain under Internet of Things Architecture

The efficient and secure data sharing mechanism can support the microgrid to achieve more accurate business control, while the current data processing methods have the problems of large computing overhead and low data sharing security. Aiming at the current problems, this paper proposes a microgrid data sharing method based on blockchain technology based on the processing mode of cloud-edge-terminal architecture. Firstly, the elliptic curve encryption algorithm is used on the edge side to encrypt the data collected by the terminal equipment reliably, so as to improve the security and efficiency of microgrid key management. Then, in the cloud, the Reputation-Evaluation Practical Byzantine Fault Tolerant mechanism (REPBFT) based on smart contract and reputation evaluation can effectively manage the data sharing of edge computing devices, avoid the waste of network computing resources, and further improve the efficiency of microgrid data sharing. The simulation results show that when the number of edge devices reaches 25, the calculation and communication overhead of the proposed method are 63.46 ms and 2.66 KB, respectively, and when the processing data reaches 1024 KB, the security of the microgrid system is still 95%, which can realize safe and reliable data sharing and interaction, and can stably support the optimal operation of the microgrid.

Research progress on wireless sensor network (WSN) security technology

Abstract Wireless sensor network (WSN) has been a frontier technology field that integrates a variety of technologies and has a wide range of applications in the military. Network security is of great significance in military warfare. First, this paper outlines the technical advantages of the application of military based on the technical characteristics of WSN. In military applications, WSN has been used in modern military combat while WSN features easy and fast deployment, high concealment, good fault tolerance, high accuracy and other obvious advantages. Moreover, from the perspective of network security, this paper reviews the research progress of network security technology at the network level and data level. The network level includes security protocols, key management, and secure routing technology, and key management includes pre-shared key mode and random key pre-distribution mode. At the data level, error control and fault-tolerant algorithms are mainly included. Automatic retransmission and forward error correction techniques are traditional error control methods, which should be combined with the specific situation of WSN to propose the corresponding fault-tolerant mechanism. Finally, this paper summarizes the practical applications of WSN in the military. From battlefield reconnaissance and target localization monitoring to destruction effect control and anti-terrorism equipment research, network security has been a top priority. Against the background of practical military applications, this paper summarizes the research significance of network security technology.

Contact Sequence Planning for Hexapod Robots in Sparse Foothold Environment Based on Monte-Carlo Tree

Legged robots can pass through complex field environments by selecting gaits and discrete footholds carefully. Conventional methods plan gaits and footholds separately and treat them as a single-step optimal process. However, such approaches cause poor passability in sparse foothold environments. This letter proposes a novel coordinative planning method for hexapod robots. It treats gait and foothold planning as a sequence optimization problem while considering the harshness of the environment as the leg’s fault. The Monte Carlo tree search (MCTS) algorithm is used to optimize the entire traversing motion sequence. A slidingMCTS method is proposed to effectively strike a balance between optimization and search operations by introducing a moving root node and controlling the sampling time. The proposed planning algorithm takes advantage of the fault-tolerant mechanism, lifting legs without valid footholds and planning the contact sequence of the remained legs, to improve the passability of the hexapod robot in harsh terrains. The method has been compared with the RRT-based search method for terrains with different densities of foothold, and experiments on challenging terrains are carried out to verify the efficiency. The results have shown that the proposed method dramatically improves the hexapod robot’s ability to pass through sparse-foothold environments.

Fast Active Fault-Tolerant Control for a Quadrotor UAV Against Multiple Actuator Faults

This paper proposes a fast adaptive fault estimator-based active fault-tolerant control strategy for a quadrotor UAV against multiple actuator faults. A fast adaptive fault estimation algorithm is designed to estimate the unknown actuator fault parameters. By synthesizing the fast adaptive fault estimator with the embedded control law, an active fault-tolerant control mechanism is established to compensate the adverse effects of multiple actuator faults. The effectiveness of the proposed strategy is validated through both numerical simulations and experimental tests.

CICM: A Collaborative Integrity Checking Blockchain Consensus Mechanism for Preserving the Originality of Data the Cloud for Forensic Investigation

The originality of data is very important for achieving correct results from forensic analysis of data for resolving the issue. Data may be analysed to resolve disputes or review issues by finding trends in the dataset that can give clues to the cause of the issue. Specially designed foolproof protection for data integrity is required for forensic purposes. Collaborative Integrity Checking Mechanism (CICM), for securing the chain-of-custody of data in a blockchain is proposed in this paper. Existing consensus mechanisms are fault-tolerant, allowing a threshold for faults. CICM avoids faults by using a transparent 100% agreement process for validating the originality of data in a blockchain. A group of agreement actors check and record the original status of data at its time of arrival. Acceptance is based on general agreement by all the participants in the consensus process. The solution was tested against practical byzantine fault tolerant (PBFT), Zyzzyva, and hybrid byzantine fault tolerant (hBFT) mechanisms for efficacy to yield correct results and operational performance costs. Binomial distribution was used to examine the CICM efficacy. CICM recorded zero probability of failure while the benchmarks recorded up to 8.44%. Throughput and latency were used to test its operational performance costs. The hBFT recorded the best performance among the benchmarks. CICM achieved 30.61% higher throughput and 21.47% lower latency than hBFT. In the robustness against faults tests, CICM performed better than hBFT with 16.5% higher throughput and 14.93% lower latency than the hBFT in the worst-case fault scenario.

A planned scheduling process of cloud computing by an effective job allocation and fault-tolerant mechanism

A planned scheduling process of cloud computing by an effective job allocation and fault-tolerant mechanism

Queuing Theory of Improved Practical Byzantine Fault Tolerant Consensus

In recent years, the use of consensus mechanism to maintain the security of blockchain system has become a considerable concern of the community. Delegated proof of stake (DPoS) and practical Byzantine fault tolerant (PBFT) consensus mechanisms are key technologies in maintaining the security of blockchain system. First, this study proposes a consensus mechanism combining DPoS and PBFT, which can rapidly deal with malicious witness nodes and shorten the time of block verification. Second, the M/PH/1 queuing model is used to analyze the performance of the proposed consensus mechanism, and the performance of the improved practical Byzantine fault tolerant consensus mechanism is evaluated from steady-state conditions and key performance measure of the system. Third, the current study uses the theoretical method of open (Jackson) queuing network, combined with the blockchain consensus process, and provides theoretical analysis with special cases. Lastly, this research utilizes numerical examples to verify the computability of the theoretical results. The analytic method is expected to open a series of potentially promising research in queueing theory of blockchain systems.

QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing.

Software-defined network (SDN) and vehicular ad-hoc network (VANET) combined provided a software-defined vehicular network (SDVN). To increase the quality of service (QoS) of vehicle communication and to make the overall process efficient, researchers are working on VANET communication systems. Current research work has made many strides, but due to the following limitations, it needs further investigation and research: Cloud computing is used for messages/tasks execution instead of fog computing, which increases response time. Furthermore, a fault tolerance mechanism is used to reduce the tasks/messages failure ratio. We proposed QoS aware and fault tolerance-based software-defined V vehicular networks using Cloud-fog computing (QAFT-SDVN) to address the above issues. We provided heuristic algorithms to solve the above limitations. The proposed model gets vehicle messages through SDN nodes which are placed on fog nodes. SDN controllers receive messages from nearby SDN units and prioritize the messages in two different ways. One is the message nature way, while the other one is deadline and size way of messages prioritization. SDN controller categorized in safety and non-safety messages and forward to the destination. After sending messages to their destination, we check their acknowledgment; if the destination receives the messages, then no action is taken; otherwise, we use a fault tolerance mechanism. We send the messages again. The proposed model is implemented in CloudSIm and iFogSim, and compared with the latest models. The results show that our proposed model decreased response time by 50% of the safety and non-safety messages by using fog nodes for the SDN controller. Furthermore, we reduced the execution time of the safety and non-safety messages by up to 4%. Similarly, compared with the latest model, we reduced the task failure ratio by 20%, 15%, 23.3%, and 22.5%.

Edge-to-Cloud Collaborative for QoS Guarantee of Smart Cities

With the rapid development of big data, cloud computing, mobile Internet and other new-generation information technologies, smart cities, carry more and more intelligent applications, and put forward higher requirements for data processing capacity and network service quality. The integration system of Edge-to-Cloud collaboration provides a feasible method to effectively improve network performance to adapt to the changing needs of users. However, the existing network management mechanism is difficult to adapt to the actual demand changes due to the characteristics of the edge-cloud fusion system, such as device diversity, location complexity and resource dynamics. This article to the idea of sliding mode control function of network virtualization technology and network, the study method and collaborative optimization theory as the foundation, of the application of static and dynamic models of the intelligence cities, fault prediction and fault tolerant management mechanism, task scheduling and resource allocation adaptive collaborative optimization mechanism, to ensure that the cities network real-time, reliability, and security, At the same time, combined with the smart campus platform of our school, the real-time performance and effectiveness of the network are tested and evaluated, providing a case demonstration for the intelligent application of smart cities. This project will further enrich and improve the theoretical system of end-to-end cloud collaborative optimization and provide new means and methods for intelligent cities network QoS(Quality of Service) guarantee.

Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR)

The computational cloud aims to move traditional computing from personal computers to cloud providers on the internet. Cloud security represents an important research area. Confidentiality, integrity, and availability are the main cloud security characteristics addressed. Cloud providers apply dynamic load balancing and reactive fault tolerance techniques to build secure cloud services to achieve high service availability. Dynamic cloud load balancing approaches distribute submitted tasks to virtual machines during tasks execution and the load of virtual machines is updated based on the system’s state. Reactive cloud fault tolerance is activated for system process failures after failure effectively happens. Reactive cloud fault tolerance handles failure after the fault has occurred. Despite the significance of dynamic load balancing and reactive fault tolerance techniques and mechanisms, few reviews focus on these approaches in a systematic, unbiased method focusing on integrating cloud dynamic load balancing and reactive fault tolerance techniques. This paper conducts a systematic literature review of the existing literature concerning reactive fault tolerance, dynamic load balancing, and their integration in their basic approaches, types, frameworks, and future directions.

A Novel Blockchain Based Secured and QoS Aware IoT Vehicular Network in Edge Cloud Computing

A software-defined vehicular network is made up of an IoT (Internet of Things) based vehicular ad-hoc network and a software-defined network. For better communication in IoT based vehicle networks, researchers are now working on the VANET (Vehicular Ad-hoc Network) to increase the overall system performance. To maximize the VANET ad-hoc network’s information application performance and reliability, edge computing has gained the attention of researchers. In current research, cloud computing is used for message related task execution, which increases the response time. We propose a Software-defined Fault Tolerance and QoS-Aware (Quality of Service) IoT-Based Vehicular Networks Using Edge Computing Secured by Blockchain to reduce overall communication delay, message failure fault tolerance, and secure service provisioning for VANET ad-hoc networks in this article. We proposed heuristic algorithms to solve the above mentioned problems of response delay, message failure, fault tolerance, and security provided by the Blockchain. The proposed model gets vehicle messages through SDN (Software defined network) nodes, which are placed on nearby edge servers, and the edge servers are validated by the blockchain to provide secure services to vehicles. The SDN controller, which exists on an edge server, which is placed on the road side to overcome communication delays, receives different messages from the vehicles and divides these messages in to two different categories. The message division is performed by the edge server by judging the time line, size, and emergency situation. SDN controller organized these messages and forwarded them to their destination. After the message is delivered to its destination, a fault tolerance mechanism checks their acknowledgements. If the message delivery fails, the fault tolerance algorithm will resend the failure message. The proposed model is implemented using a custom simulator and compared with the latest VANET based QoS and fault tolerance models. The result shows the performance of the proposed model, which decreased the overall message communication delay by 55% of the normal and emergency messages by using the edge server SDN controller. Furthermore, the proposed model reduces the execution time, security risk, and message failure ratio by using the edge server, cloud server and blockchain infrastructure.

Research on Data Security Model of Environmental Monitoring Based on Blockchain

With the rapid development of the social economy, the problem of environmental pollution has been widely concerned. The existing environmental monitoring system adopts a hierarchical centralized management structure, which has some problems, such as data silos and the risk of data falsification. Thus, this paper proposes an environmental monitoring data security model based on the blockchain, which uses the blockchain distributed storage mode to realize the secure sharing of monitoring data and curb the behavior of data forgery. A practical Byzantine fault tolerant mechanism based on credit grouping supervision is adopted to reduce the computation and communication overhead caused by data consensus. Through the cloud chain fusion technology, the encrypted monitoring data is stored on the cloud storage server, and the monitoring data credentials are stored on the blockchain to reduce the storage pressure. And AES(Advanced Encryption Standard) combined with the RSA (Rivest-Shamir-Adleman) encryption algorithm to ensure the security of data transmission and storage. Security analysis and experiments demonstrate that our proposed scheme achieves authenticity, integrity, and security for monitored data. In addition, it effectively reduces the computation, communication, and storage overhead of the block nodes.

A Novel Addressing and Routing Architecture for Cloud-Service Datacenter Networks

Datacenter networks (DCNs) play a key role in providing cloud services. The energy consumption and cost of a DCN are growing sharply with the extensions of network bandwidth and network size. The energy consumption, complexity and cost of a DCN depend on some design factors such as the topology structure, addressing scheme and routing mechanism. A novel addressing and routing architecture for cloud-service DCNs with regular topologies is proposed in this paper. First of all, we propose a port-based source-routing addressing (PSRA) scheme, which makes the table-lookup operation unnecessary and decreases the switch complexity. Next, leveraging the characteristics of PSRA and the regularity of DCN topologies, an extremely simple routing mechanism is designed, without switch involvement, control message interaction and topology information storage. Lastly, a high-efficiency fault-tolerance mechanism is proposed for the addressing and routing architecture. The analysis, implementation and simulation results indicate that the proposed architecture not only decreases the energy consumption and thus the cost of a DCN, but also enhances the routing performance and solves the fault-tolerance problem in a very efficient way.