RDDP:An Efficient MDS Array Code on Toleration Triple Node Failures in Storage System

It is well known that erasure coding can be used in storage systems to efficiently store data while protecting against failures. Conventionally, the design of erasure codes has focused on the tradeoff between redundancy and reliability. Under this criterion, an maximum distance separable（MDS） code has optimal redundancy. In this paper, we address a new class of MDS array codes for tolerating triple node failures by extending the row di- agonal parity（RDP） code, named the RDDP（row double diagonal parity） code. The RDDP code takes advantages of good perform- ances of the RDP code with balanced I/0. A specific triple-erasure decoding algorithm to reduce decoding complexity is depicted by geometric graph, and it is easily implemented by software and hardware. The theoretical analysis shows that the comprehensive properties of the RDDP code are optimal, such as encoding and decoding efficiency, update efficiency and I/0 balance performance.

An Optimal Cluster Head and Gateway Node Selection with Fault Tolerance

In Mobile Ad Hoc Networks(MANET),Quality of Service(QoS)is an important factor that must be analysed for the showing the better performance.The Node Quality-based Clustering Algorithm using Fuzzy-Fruit Fly Optimiza-tion for Cluster Head and Gateway Selection(NQCAFFFOCHGS)has the best network performance because it uses the Improved Weighted Clustering Algo-rithm(IWCA)to cluster the network and the FFO algorithm,which uses fuzzy-based network metrics to select the best CH and entryway.However,the major drawback of the fuzzy system was to appropriately select the membership func-tions.Also,the network metrics related to the path or link connectivity were not considered to effectively choose the CH and gateway.When learning fuzzy sets,this algorithm employs a new Continuous Action-set Learning Automata(CALA)approach that correctly modifies and chooses the fuzzy membership functions.Despite the fact that it extends the network’s lifespan,it does not assist in the detection of defective nodes in the routing route.Because of this,a new Fault Tolerance(NQCAEFFFOCHGS-FT)mechanism based on the Distributed Connectivity Restoration(DCR)mechanism is proposed,which allows the net-work to self-heal as a consequence of the algorithm’s self-healing capacity.Because of the way this method is designed,node failures may be utilised to rebuild the network topology via the use of cascaded node moves.Founded on the fractional network information and topologic overhead related with each node,the DCR is suggested as an alternative to the DCR.When compared to the NQCAFFFOCHGS algorithm,the recreation results display that the proposed NQCAEFFFOCHGS-FT algorithm improves network performance in terms of end-to-end delay,energy consumption,Packet Loss Ratio(PLR),Normalized Routing Overhead(NRO),and Balanced Load Index(BLI).

ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network

A wireless sensor network(WSN)consists of several tiny sensor nodes to monitor,collect,and transmit the physical information from an environment through the wireless channel.The node failure is considered as one of the main issues in the WSN which creates higher packet drop,delay,and energy consumption during the communication.Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets.In this paper,Artificial Neural Network(ANN)based Node Failure Detection(NFD)is developed with cognitive radio for detecting the location of the node failure.The ad hoc on-demand distance vector(AODV)routing protocol is used for transmitting the data from the source node to the base station.Moreover,the Mahalanobis distance is used for detecting an adjacent node to the node failure which is used to create the routing path without any node failure.The performance of the proposed ANN-NFD method is analysed in terms of throughput,delivery rate,number of nodes alive,drop rate,end to end delay,energy consumption,and overhead ratio.Furthermore,the performance of the ANN-NFD method is evaluated with the header to base station and base station to header(H2B2H)protocol.The packet delivery rate of the ANN-NFD method is 0.92 for 150 nodes that are high when compared to the H2B2H protocol.Hence,the ANN-NFD method provides data consistency during data transmission under node and battery failure.

An Efficient Connectivity Restoration Technique(ECRT)for Wireless Sensor Network

Node failure in Wireless Sensor Networks(WSNs)is a fundamental problem because WSNs operate in hostile environments.The failure of nodes leads to network partitioning that may compromise the basic operation of the sensor network.To deal with such situations,a rapid recovery mechanism is required for restoring inter-node connectivity.Due to the immense importance and need for a recovery mechanism,several different approaches are proposed in the literature.However,the proposed approaches have shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration.Moreover,most of these approaches rely on the excessive mobility of nodes for restoration connectivity that affects both coverage and energy consumption.This paper proposes a novel technique called ECRT(Efficient Connectivity Restoration Technique).This technique is capable of restoring connectivity due to single and multiple node failures.ECRT achieves energy efficiency by transmitting a minimal number of control packets.It is also coverage-aware as it relocates minimal nodes while trying to restore connectivity.With the help of extensive simulations,it is proven that ECRT is effective in connectivity restoration for single and multiple node failures.Results also show that ECRT exchanges a much smaller number of packets than other techniques.Moreover,it also yields the least reduction in field coverage,proving its versatility for connectivity restoration.

CNR:A Cluster-Based Solution for Connectivity Restoration for Mobile WSNs

Wireless Sensor Networks(WSNs)are an integral part of the Internet of Things(IoT)and are widely used in a plethora of applications.Typically,sensor networks operate in harsh environments where human intervention is often restricted,which makes battery replacement for sensor nodes impractical.Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network.Without a connectivity restoration mechanism,node failures ultimately lead to a network partition,which affects the basic function of the sensor network.Therefore,the research community actively concentrates on addressing and solving the challenges associated with connectivity restoration in sensor networks.Since energy is a scarce resource in sensor networks,it becomes the focus of research,and researchers strive to propose new solutions that are energy efficient.The common issue that is well studied and considered is how to increase the network’s life span by solving the node failure problem and achieving efficient energy utilization.This paper introduces a Clusterbased Node Recovery(CNR)connectivity restoration mechanism based on the concept of clustering.Clustering is a well-known mechanism in sensor networks,and it is known for its energy-efficient operation and scalability.The proposed technique utilizes a distributed cluster-based approach to identify the failed nodes,while Cluster Heads(CHs)play a significant role in the restoration of connectivity.Extensive simulations were conducted to evaluate the performance of the proposed technique and compare it with the existing techniques.The simulation results show that the proposed technique efficiently addresses node failure and restores connectivity by moving fewer nodes than other existing connectivity restoration mechanisms.The proposed mechanism also yields an improved field coverage as well as a lesser number of packets exchanged as compared to existing state-of-the-art mechanisms.

Reliable and Energy Efficient Target Coverage for Wireless Sensor Networks

A critical aspect of applications with Wireless Sensor Networks （WSNs） is network lifetime. Power-constrained WSNs are usable as long as they can communicate sense data to a processing node. Poor communication links and hazardous environments make the WSNs unreliable. Existing schemes assume that the state of a sensor covering targets is binary： success （covers the targets） or failure （cannot cover the targets）. However, in real WSNs, a sensor covers targets with a certain probability. To improve WSNs＇ reliability, we should consider that a sensor covers targets with users＇ satisfied probability. To solve this problem, this paper first introduces a failure probability into the target coverage problem to improve and control the system reliability. Furthermore, we model the solution as the a-Reliable Maximum Sensor Covers （a-RMSC） problem and design a heuristic greedy algorithm that efficiently computes the maximal number of a-Reliable sensor covers. To efficiently extend the WSNs lifetime with users＇ pre-defined failure probability requirements, only the sensors from the current active sensor cover are responsible for monitoring all targets, while all other sensors are in a low-energy sleep mode. Simulation results validate the performance of this algorithm, in which users can precisely control the system reliability without sacrificing much energy consumption.