Backup Nodes Research Articles

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

An optimized stable clustering algorithm for mobile ad hoc networks

In mobile ad hoc network, each node is capable of sending message (data) dynamically without requirement of any fixed infrastructure. Mobile nodes frequently move in/out from the network dynamically, making network topology unstable in mobile ad hoc network (MANET). As a result, it becomes an extremely challenging task to maintain stable network. In this research article, we have proposed an optimized stable clustering algorithm that will provide more stability to the network by minimizing the cluster head changes and reducing clustering overhead. In proposed algorithm, a new node is introduced which acts as a backup node in the cluster. Such backup node acts as cluster head, when actual cluster head moves out (or died) from the cluster. Latter, the cluster head reelect a new backup node. This practice keeps network availability without disturbance. Further, the priority of cluster head and backup node is calculated based on the node degree and the remaining battery life for mobile nodes. Decision for electing cluster head and backup node depends on the priority factor.

Stable geographic forwarding with link lifetime prediction in mobile adhoc networks for battlefield environment

AbstractMobile adhoc network (MANET) is one of the most relevant areas of research in wireless communication that has gained prevalence due to its diversity over large-scale highly mobile networks to small-scale networks having low mobility and power constraints. Adhoc networks are inherently envisioned to be highly vulnerable to dynamic changes because of mobile sensor nodes. Node mobility often results in breakage of communication links, thereby introducing additional overhead for establishing new routes and transmitting table updates, further causing rapid exhaustion of energy reserve. Especially in military applications, preventing communication disruptions is an important security concern for defence applications engaged in safeguarding national boundaries. This necessitates the need for efficient routing strategy for battlefield environments susceptible to frequent link failures due to random mobility of groups/individuals. In this regard, we have proposed an efficient stable geographic forwarding with link-lifetime prediction (SGFL) that utilizes the broadcast nature of wireless channel and multicasts with node mobility. During the next hop selection process, a node preferably selects the neighbours which are at the least distance from the destination with low mobility. Unlike position based opportunistic routing, our scheme allows selection of backup node that lies within the transmission range of selected neighbours. Link lifetime prediction with backup nodes enhances efficiency and reliability of routing in highly mobile and congested adhoc networks. Simulation results show that our proposed SGFL achieves better performance than existing counterparts in terms of packet delivery ratio, packet loss and end-to-end delay under high node density as well as increased traffic flow.

Context sensitive trust based geographic opportunistic routing in mobile ad hoc networks

Position based opportunistic routing (POR) is a stateless, robust, and reliable geographic routing protocol in Mobile AdHoc NETwork (MANET). The opportunistic routing embraces broadcast property of wireless channels and utilizes it for opportunistic forwarding. Both the malicious node behavior and the backup nodes’ behavior are equally treated as malicious in the existing misbehavior detection mechanisms. Hence, incorporating a general trust model in POR is not combative with routing attacks. It is necessary to determine whether the misbehavior is likely a result of malicious activity or due to the backup scenario of opportunistic forwarding. On the other hand, if context-sensitive trust information is available on every node, it ensures a fair decision making and also supports secured routing in an opportunistic approach. This work investigates the utilization of context attributes along with generic trust model to allow POR for secure and reliable data forwarding. This paper introduces context-sensitive trust for choosing the data forwarding node in POR (CPOR) to assist opportunistic routing in selecting the trusted optimal data forwarding node and to cope with both security and reliability of communications. The proposed work exercises both coarse- and fine-grained trust evaluation to strengthen the trustworthiness. The coarse-grained trust measure includes positive progress per hop and behavioral attribute of the nodes in terms of routing service. The fine-grained trust evaluation differs the opportunistic routing environment from the adverse scenarios and aids the source node such that it builds a highly trusted positive progress set using contextual attributes. The fine-grained trust evaluation deduces the ideal contextual information such as the link quality, battery energy, and the backup service to determine the accurate trust value of nodes. As a result, it involves optimal routes and enables CPOR to maintain the routing performance equal to the POR even in the presence of malicious nodes in the network. The simulation results demonstrate that the packet delivery ratio of the proposed context-aware trust model is substantially high even when 50% of the total nodes are found malicious and outperforms the trust-aware opportunistic routing protocol (TAOR).

Redundant Design in Interdependent Networks

Modern infrastructure networks are often coupled together and thus could be modeled as interdependent networks. Overload and interdependent effect make interdependent networks more fragile when suffering from attacks. Existing research has primarily concentrated on the cascading failure process of interdependent networks without load, or the robustness of isolated network with load. Only limited research has been done on the cascading failure process caused by overload in interdependent networks. Redundant design is a primary approach to enhance the reliability and robustness of the system. In this paper, we propose two redundant methods, node back-up and dependency redundancy, and the experiment results indicate that two measures are effective and costless. Two detailed models about redundant design are introduced based on the non-linear load-capacity model. Based on the attributes and historical failure distribution of nodes, we introduce three static selecting strategies-Random-based, Degree-based, Initial load-based and a dynamic strategy-HFD (historical failure distribution) to identify which nodes could have a back-up with priority. In addition, we consider the cost and efficiency of different redundant proportions to determine the best proportion with maximal enhancement and minimal cost. Experiments on interdependent networks demonstrate that the combination of HFD and dependency redundancy is an effective and preferred measure to implement redundant design on interdependent networks. The results suggest that the redundant design proposed in this paper can permit construction of highly robust interactive networked systems.

Towards Promoting Backup-Sharing in Survivable Virtual Network Design

In a virtualized infrastructure where multiple virtual networks (or tenants) are running atop the same physical network (e.g., a data center network), a single facility node (e.g., a server) failure can bring down multiple virtual machines, disconnecting their corresponding services and leading to millions of dollars in penalty cost. To overcome losses, tenants or virtual networks can be augmented with a dedicated set of backup nodes and links provisioned with enough backup resources to assume any single facility node failure. This approach is commonly referred to as Survivable Virtual Network (SVN) design. The achievable reliability guarantee of the resultant SVN could come at the expense of lowering the substrate network utilization efficiency, and subsequently its admissibility, since the provisioned backup resources are reserved and remain idle until failures occur. Backup-sharing can replace the dedicated survivability scheme to circumvent the inconvenience of idle resources and reduce the footprints of backup resources. Indeed the problem of SVN design with backup-sharing has recurred multiple times in the literature. In most of the existing work, designing an SVN is bounded to a fixed number of backup nodes; further backup-sharing is only explored and optimized during the embedding phase. This renders the existing redesign techniques agnostic to the backup resource sharing in the substrate network, and highly dependent on the efficiency of the adopted mapping approach. In this paper, we diverge from this dogmatic approach, and introduce ProRed, a novel prognostic redesign technique that promotes the backup resource sharing at the virtual network level, prior to the embedding phase. Our numerical results prove that this redesign technique achieves lower-cost mapping solutions and greatly enhances the achievable backup sharing, boosting the overall network's admissibility.

ZBFR: zone based failure recovery in WSNs by utilizing mobility and coverage overlapping

Wireless sensor networks are more prone to failures as compared to other traditional networks. The frequent faults and failures sometime create large holes causing loss of sensing and connectivity coverage in the network. In present work, a zone based failure detection and recovery scheme is presented to reliably handle such node failures. We first propose a consensus and agreement based approach to elect a suitable monitor node called as zone monitor (ZM). ZM is responsible for coordinating failure recovery activities and maintaining desired coverage within a zone. In order to overcome failure overhead due to false failure detection, a consensus is carried out amongst neighboring nodes of a suspicious node to confirm the correct status with high accuracy. On confirmation of a node failure, the impact of resulting hole on coverage is analyzed and if impact exceeds beyond a particular threshold, a recovery process is initiated. The recovery process utilizes backup nodes having overlapping sensing coverage with failed node and may also relocate some nodes. Firstly a backup node is probed and activated if available. If no backup node is found, the solution strives to recover coverage jointly by recursively relocating some mobile nodes and probing backup nodes. The proposed scheme is analyzed and validated through NS-2 based simulation experiments.

An Approach for Robust In-Network Caching in Information-Centric Networks

In-network caching is critical for information-centric networking (ICN) and has gained plenty of interests from the academic community. In recent years, many in-network caching approaches have been proposed in the literature. To the best of our knowledge, however, these approaches do not consider the failure of routers in the network. Accordingly, their performance could be significantly affected by node failures. To fill this gap, this paper presents a Robust In-Network caching Approach (RINA) for ICN. In RINA, the nodes in a network are divided into two groups: a backup node and some normal nodes. To provide robustness, RINA caches some most popular content chunks at both the given backup node and the normal nodes so that the failure of nodes in the network does not significantly affect the caching performance such as cache hit ratio. We carry extensive simulations to compare RINA and some existing approaches. The results show that RINA outperforms them in robustness and also has good cache hit ratio.

A BER and 2-Hop Routing Information-Based Stable Geographical Routing Protocol in MANETs for Multimedia Applications

In order to guarantee the QoS of multimedia applications in a mobile ad hoc network (MANET), a reliable packet transmitting mechanism used in MANETs is developed. In this paper, we synthesize the geographical information, bit error rates of the links and 2-hop routing information to elaborate a most durable routing path between the source node and the destination node. In route discovery phase, all the possible paths from the source node to the destination node are checked on the basis of path reliability and number of hops. Meanwhile, 2-hop routing tables are created. Aided by the geographical information, our mechanism can reduce broadcast packets significantly in RREQ phase compared with other flooding-based protocols. The 2-hop routing information is employed just like backup node information used in other stable routing protocols. Once the path breaks, it can be repaired locally and rapidly by setting up a short path to a 2-hop neighboring node. Compared with other four stable mechanisms with excellent performance, our mechanism (B2RP) exhibits a slightly better in terms of packet delivery ratio, average route lifetime and end-to-end delay.

Reliability model of fault-tolerant data processing system with primary and backup nodes

This paper deals with the fault-tolerant data processing systems, which are widely used in modern world of information technologies and have acceptable overhead expenses in hardware implementation. A simplified reliability model for duplex systems and the offered by authors advanced model for data processing systems with primary and backup nodes based on a three-state model of recoverable elements, which takes into consideration different failure rates of passive and active nodes and finite time of node activation, are also given. A calculation formula for the availability factor of the dual-node data processing system with primary and backup nodes and calculation examples are also provided.

Optimized Minimum Spanning Tree for Secure Routing in MANET

Secure group communication transfers message from one member to another confidentially. Key management for secure communication in wireless networks is primitive based on cryptographic techniques. Intercluster routing was used to improve wireless networks security. In the new scheme, Minimum Spanning Tree (MST) and GBest-BAT algorithm are computed to identify Cluster Heads (CH) with a concept of backup nodes being introduced for effective key management. This study proposes MST formation for inter-cluster routing and it is optimized with GBEST- BAT algorithm.

Distributed Hybrid Fault Tolerant Model with Fault Recovery for Mobile Grid

This paper proposes a distributed hybrid fault tolerant model for mobile grid systems. It consists of proactive and reactive fault tolerant approaches. Before resource allocation, all the jobs are sorted and assigned to different level based on precedence. The reliability and failure probability of each resource is estimated. In case of proactive approach, the high priority jobs are assigned to the resources with high reliabilities. In reactive approach, a backup node with low failure probability will have the replica of jobs assigned for the resources with high failure probability. If a failure is detected in the primary resource, the backup resource will perform failure recovery by executing the remaining job.

A multi-criterion fuzzy logic intra-cluster and inter-cluster-based stable cluster head election approach in large scale WSN

Extending the lifetime of wireless sensor networks (WSNs) is a major concern in recent years. The main problem seems in the recent proposed approaches is that these use direct communication among nodes with the rotation of cluster heads (CHs) periodically to distribute energy consumption among various cluster heads (CHs). Energy saving mechanisms based only on metrics related to nodes' residual power cannot be directly applied to find stable CHs. The reason is that a sensor node or a CH having more residual power is willing to accept all requests, because it has enough residual battery power, therefore, much traffic will be injected to that node. In that case, a sharp decay of node's backup battery power. In this research paper, a multi-criterion fuzzy logic intra-cluster and inter-cluster based multi-hop routing protocol is proposed. The simulation results confirm that our proposed approach is more efficient than state-of-the-art approaches.

A multi-criterion fuzzy logic intra-cluster and inter-cluster-based stable cluster head election approach in large scale WSN

Extending the lifetime of wireless sensor networks WSNs is a major concern in recent years. The main problem seems in the recent proposed approaches is that these use direct communication among nodes with the rotation of cluster heads CHs periodically to distribute energy consumption among various cluster heads CHs. Energy saving mechanisms based only on metrics related to nodes' residual power cannot be directly applied to find stable CHs. The reason is that a sensor node or a CH having more residual power is willing to accept all requests, because it has enough residual battery power, therefore, much traffic will be injected to that node. In that case, a sharp decay of node's backup battery power. In this research paper, a multi-criterion fuzzy logic intra-cluster and inter-cluster based multi-hop routing protocol is proposed. The simulation results confirm that our proposed approach is more efficient than state-of-the-art approaches.

Similarity and Locality Based Indexing for High Performance Data Deduplication

Data deduplication has gained increasing attention and popularity as a space-efficient approach in backup storage systems. One of the main challenges for centralized data deduplication is the scalability of fingerprint-index search. In this paper, we propose SiLo, a near-exact and scalable deduplication system that effectively and complementarily exploits similarity and locality of data streams to achieve high duplicate elimination, throughput, and well balanced load at extremely low RAM overhead. The main idea behind SiLo is to expose and exploit more similarity by grouping strongly correlated small files into a segment and segmenting large files, and to leverage the locality in the data stream by grouping contiguous segments into blocks to capture similar and duplicate data missed by the probabilistic similarity detection. SiLo also employs a locality based stateless routing algorithm to parallelize and distribute data blocks to multiple backup nodes. By judiciously enhancing similarity through the exploitation of locality and vice versa, SiLo is able to significantly reduce RAM usage for index-lookup, achieve the near-exact efficiency of duplicate elimination, maintain a high deduplication throughput, and obtain load balance among backup nodes.

Mojim

Next-generation non-volatile memories (NVMs) promise DRAM-like performance, persistence, and high density. They can attach directly to processors to form non-volatile main memory (NVMM) and offer the opportunity to build very low-latency storage systems. These high-performance storage systems would be especially useful in large-scale data center environments where reliability and availability are critical. However, providing reliability and availability to NVMM is challenging, since the latency of data replication can overwhelm the low latency that NVMM should provide. We propose Mojim, a system that provides the reliability and availability that large-scale storage systems require, while preserving the performance of NVMM. Mojim achieves these goals by using a two-tier architecture in which the primary tier contains a mirrored pair of nodes and the secondary tier contains one or more secondary backup nodes with weakly consistent copies of data. Mojim uses highly-optimized replication protocols, software, and networking stacks to minimize replication costs and expose as much of NVMM?s performance as possible. We evaluate Mojim using raw DRAM as a proxy for NVMM and using an industrial NVMM emulation system. We find that Mojim provides replicated NVMM with similar or even better performance than un-replicated NVMM (reducing latency by 27% to 63% and delivering between 0.4 to 2.7X the throughput). We demonstrate that replacing MongoDB's built-in replication system with Mojim improves MongoDB's performance by 3.4 to 4X.

Mojim

Next-generation non-volatile memories (NVMs) promise DRAM-like performance, persistence, and high density. They can attach directly to processors to form non-volatile main memory (NVMM) and offer the opportunity to build very low-latency storage systems. These high-performance storage systems would be especially useful in large-scale data center environments where reliability and availability are critical. However, providing reliability and availability to NVMM is challenging, since the latency of data replication can overwhelm the low latency that NVMM should provide. We propose Mojim, a system that provides the reliability and availability that large-scale storage systems require, while preserving the performance of NVMM. Mojim achieves these goals by using a two-tier architecture in which the primary tier contains a mirrored pair of nodes and the secondary tier contains one or more secondary backup nodes with weakly consistent copies of data. Mojim uses highly-optimized replication protocols, software, and networking stacks to minimize replication costs and expose as much of NVMM?s performance as possible. We evaluate Mojim using raw DRAM as a proxy for NVMM and using an industrial NVMM emulation system. We find that Mojim provides replicated NVMM with similar or even better performance than un-replicated NVMM (reducing latency by 27% to 63% and delivering between 0.4 to 2.7X the throughput). We demonstrate that replacing MongoDB's built-in replication system with Mojim improves MongoDB's performance by 3.4 to 4X.

Fault Tolerance Oriented Sensors Relay Monitoring Mechanism for Overhead Transmission Line in Smart Grid

Recently, sensors are applied to support the realization of the innovative smart grid. As the high reliability requirements of electric power, communication sensors with fault tolerance have been the focus of many researchers. In this paper, sensors are used to monitor and control the power distribution network. As the limitation of linear topology, we investigate redundancy of relay nodes in hybrid network architecture and propose an integrated fault tolerance framework. The framework provides solutions for the three subproblems which are number problem, placement problem, and adaptive problem. The number of backup nodes and cellular modules is explored with optimization. The exact deployment position is examined and the adaptive action will be taken when a fault occurs in the framework. Three paradigms are sequential in different stage and a fault tolerance framework is being built up. The extensive experiments illustrate effectiveness of our framework and numerical results highlight some interesting observations.

ON-DEMAND CHECKPOINT AND RECOVERY SCHEME FOR WIRELESS SENSOR NETWORKS

In future, WSN (Wireless Sensor Network) which consists of n number of tiny wireless embedded systems will be an indispensable part of our daily life. Fault tolerance is an imported technique which has to be implemented in sensor networks to avoid catastrophic events in the network; failure in the network may lead to wastage of resources. Fault tolerance is the property that enables a system to continue operate properly in the event of failure of (or one or more faults within) some of its components. An improved version of checkpointing called on-demand checkpoint and rollback recovery scheme is implemented in this paper. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, our method uses coordinating checkpoint, non blocking checkpoint to make the checkpoint taken consistent in nature. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head on demand. Experimental comparisons with CTP (Collection Tree Protocol) and demand checkpoint with CTP shows time and Packet Delivery Ratio values are identical saying checkpointing does not affect the WSN performance due to inclusion of checkpoint. The proposed scheme is designed and implemented in Contiki OS using sensor network simulator COOJA.

A Self-Healing Connectivity Recovery Algorithm in Wireless Sensor-Actor Networks

Wireless sensor and actor networks (WSANs) additionally employ actor nodes within the wireless sensor network (WSN) which can process the sensed data and perform certain actions based on this collected data. In most applications, inter-actor coordination is required to provide the best response. One actor failure may lead to partitioning the inter-actor networks, tolerating the actor failure and restoring the lost connectivity need to be performed while imposing the least overhead on the individual actors autonomously. In this paper, we present a Self-healing Connectivity Recovery Algorithm (SCRA) which is to recover the failure actor. SCRA proactively identifies actors whether is a cut vertex or not to the network connectivity based on the depth-first search algorithm (DFS), and designates a minimal CDS backup nodes. If an actor node suddenly fails, the minimal block backup nodes move and initiate a recovery process until the network is reconnected. Through simulated experiments, the results show that the algorithm is more effective than present algorithms in terms of total travel distance, and total number of messages.