Node Failure Detection Research Articles

Efficient identification of node failure and recovery through end to end Probing techniques

Identification of Node failure detection and a localization is a very important challenge in a network community to get a quick recovery and avoid useless traffic in network. But it is very difficult to check the failure nodes or locations because of the large number of Screw ups in dense network. As finding the main source for failure of network is always challenging our proposed work will achieve that, it identifies the node failure by using probing measurement of binary state to end to end paths. Apart from identifying the network failure, it also quantifies the total failure nodes and the ip address or vicinity of failure nodes, Identification of node failure is done by monitoring nodes which are deployed in the netwok. Our Proposed word is divided majorly in two phases one is identifying the node failures by using Probing Packets and other is finding of the failure and its recovery.

Research on the Application of Computer P2P Network Technology in Local Area Network

This article analyzes the basic content, application advantages, and infrastructure of computer P2P network technology. The author studies the specific application of computer P2P network technology in application structure, download mode, node function design, overlay network protocol, network data distribution, multiple copy redundancy processing, node failure detection, and copy repair processing. The author studied the countermeasures against hacker attacks, virus transmission problems, and transmission speed problems in the process of technology application. The purpose of this article is to give full play to the application effects of computer P2P network technology and improve the security of the local area network operation process.

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.

A Blockchain-Based Storage System With Financial Incentives for Load-balancing

Most storage systems adopt distributed architecture to reach high reliability. In these distributed systems, a well-balanced data distribution can improve storage reliability. However, existing schemes rely on dealers to distribute data, bring back the risk of single-point failure again. In this paper, we propose a blockchain-based storage system with financial incentives for load-balancing. Nodes in the system are rational and compete for data to earn a reward. The only source of storage rewards is from users' payment for leasing storage. To reach load-balancing, we design a new incentive scheme, which contains an income function to reward the nodes who own proper data and punish the nodes who own excessive data. In the system, each node continuously generates a proof of storage. We present a chain structure using the proofs to detect node failures and record data distribution. The state of distribution could be taken as input to the income function for reward allocation. We decouple the role of nodes from miners to reduce their workload, making the system more compatible. Our simulation experiments show efficient performance in the data distribution. The system can always recover to a balanced status as the blockchain grows up.

A Binary Feedback Schemes for Detecting Failure of Node in Mobile Wireless Network

The network topology of association was always active but the association between them may not be always connected and properties are restricted. On the time there is a chance of node failures and detecting the node failure is important. Two node failure detection schemes are implemented which are binary and non-binary feedback schemes. These schemes unite locality estimation, localized monitoring and node association. These results are applicable to both attached and detached networks. The schemes accomplish high disappointment discovery rates, low forged positive rates, and low correspondence overhead.

SENSOR NODE FAILURE DETECTION USING ROUND TRIP DELAY IN WIRELESS SENSOR NETWORK

In these days, the application of Wireless Sensor Networks (WSNs) have been increased .Advance in microelectronic fabrication technology also reduces the manufacturing cost. Detecting node failures in Wireless Sensor Networks is very challenging because the network topology can be highly dynamic, the network may not always connected and the resources are limited . It becomes trend to deploy the large number of portable wireless sensors in Wireless Sensor Networks, in order to increase the Quality of Service (QoS). The QoS is mainly affected by the failure of sensor node .The sensor node failure increases with the increase in number of sensors in Wireless Sensor Networks. In order to maintain better QoS in such failure condition, Identifying and Detaching such faults are essential. In the proposed method the faulty sensor node is detected by measuring the Round Trip Delay (RTD) time of Discrete Round Trip paths and comparing them with threshold value. In proposed method, Scalability is verified by simulating the WSNs with large numbers of sensor nodes in NS2. The RTD time results derived in hardware and software implementation are almost equal, justifying the real time applicability of the investigated method.

Reliability model of the symmetric dual-node data processing system with functional redundancy

This scientific paper deals with the reliability model of the symmetric system based on two data processing nodes with the functional redundancy. The simplified reliability model of the system and the advanced model offered by the authors considering nonzero time of activation of the node primary functions, nonzero times for node failure detection and switching to the function backing-up mode are presented. The formulas for calculation of stationary availability factor, mean time to failure and mean time to repair are also discussed. Finally, the examples of reliability indices calculations according to the simplified and advanced reliability models are also given.

A Novel based Approach for Detecting Node Failures in Mobile Wireless Networks

A Novel based Approach for Detecting Node Failures in Mobile Wireless Networks

Node Failure Detection in both Wired and Wireless Sensor Network Using Binary and Non-Binary Schemes

Node Failure Detection in both Wired and Wireless Sensor Network Using Binary and Non-Binary Schemes

Discrete Path Selection and Entropy Based Sensor Node Failure Detection in Wireless Sensor Networks

Abstract Exertion of wireless sensor networks has been increasing in recent years, and it imprints in almost all the technologies such as machine industry, medical, military and civil applications. Due to rapid growth in electronic fabrication technology, low cost, efficient, multifunctional and accurate sensors can be produced and thus engineers tend to incorporate many sensors in the area of deployment. As the number of sensors in the field increases, the probability of failure committed by these sensors also increases. Hence, efficient algorithms to detect and recover the failure of sensors are paramount. The current work concentrates mainly on mechanisms to detect sensor node failures on the basis of the delay incurred in propagation and also the energy associated with sensors in the field of deployment. The simulation shows that the algorithm plays in the best possible way to detect the failure in sensors. Finally, the Boolean sensing model is considered to calculate the network coverage of the wireless sensor network for various numbers of nodes in the network.

Detecting Node Failures in Mobile Wireless Networks: A Probabilistic Approach

Detecting node failures in mobile wireless networks is very challenging because the network topology can be highly dynamic, the network may not be always connected, and the resources are limited. In this paper, we take a probabilistic approach and propose two node failure detection schemes that systematically combine localized monitoring, location estimation and node collaboration. Extensive simulation results in both connected and disconnected networks demonstrate that our schemes achieve high failure detection rates (close to an upper bound) and low false positive rates, and incur low communication overhead. Compared to approaches that use centralized monitoring, our approach has up to 80 percent lower communication overhead, and only slightly lower detection rates and slightly higher false positive rates. In addition, our approach has the advantage that it is applicable to both connected and disconnected networks while centralized monitoring is only applicable to connected networks. Compared to other approaches that use localized monitoring, our approach has similar failure detection rates, up to 57 percent lower communication overhead and much lower false positive rates (e.g., 0.01 versus 0.27 in some settings).

Sensor Node Failure Detection using Multiway Tree based Round Trip Path in Wireless Sensor Networks

To upgrade the Quality of Services among the sensor node correspondence in WSN, the recognizing confirmation of sensor node range, ID of reduced sensor nodes, amounts of sensor nodes included, recognizable proof of issue nodes are the over the top testing civil argument. The main objective of this work is to identify the faulty node, its readings, detection of the malfunctioning nodes. Round Trip Path is used to evaluate the Round Trip Delay time with which the information about the sensor nodes is accomplished. In perspective of the round trek deferral time esteem, the deficiency node is diagnosed. The detection of the faulty node is determined by the previous work but the obtained path for the detection is more. In the proposed Multi way Tree based Round Trip Path (MTrTP) system, the faulty node is identified with less number of paths when compared to the existing work. In this method, the shortcoming sensor node is recognized, by measuring the RTD time of every single possible way and the results are appeared differently in relation to edge esteem. MTrTP system is had a go at using six at mega sensor nodes with Xbee Series2 ZigBee modules. By taking a gander at the distinctive results got using the RTD examination, MTrTP strategy exhibits that, it will give raised results in regards to number of RTP and investigation time. In this work, diverse gained results are plotted and the relating examinations are inspected. The plotted result of the existing work and the current work is compared. The proposed work has much more advantages when compared to existing because the number of path obtained and the analysis time for the fault node detection is less. Thus, the detection of the fault node is determined by the MTrTP algorithm. Therefore, the lifetime of the wireless sensor network, the degree of coverage and connectivity among the sensor network are increased. This work can be used for industrial automation and all WSN applications.

The Wi-STARK architecture for resilient real-time wireless communications

Networking communications play an important role to secure a dependable and timely operation of distributed and real-time embedded system applications; however, an effective real-time support is not yet properly addressed in the wireless realm. This paper presents Wi-STARK , a novel architecture for resilient and real-time wireless communications within an one-hop communication domain. Low level reliable (frame) communications, node failure detection, membership management, and networking partition control are provided; since these low level services extend and build upon the exposed interface offered by networking technologies, Wi-STARK is in strict compliance with wireless communication standards, such as IEEE 802.15.4 and IEEE 802.11p. The Wi-STARK service interface is then offered as operating system primitives, helpful for building distributed control applications. The one-hop dependability and timeliness guarantees offered by Wi-STARK are a fundamental step towards an effective design of real-time wireless networks with multiple hops, including end-to-end schedulability analysis of networking operations.

Sensor Node Failure Detection Based on Round Trip Delay and Paths in WSNs

In recent years, applications of wireless sensor networks (WSNs) have been increased due to its vast potential to connect the physical world to the virtual world. Also, an advance in microelectronic fabrication technology reduces the cost of manufacturing portable wireless sensor nodes. It becomes a trend to deploy the large numbers of portable wireless sensors in WSNs to increase the quality of service (QoS). The QoS of such WSNs is mainly affected by the failure of sensor nodes. Probability of sensor node failure increases with increase in number of sensors. In order to maintain the better QoS under failure conditions, identifying and detaching such faults are essential. In the proposed method, faulty sensor node is detected by measuring the round trip delay (RTD) time of discrete round trip paths and comparing them with threshold value. Initially, the suggested method is experimented on WSNs with six sensor nodes designed using microcontroller and ZigBee. Scalability of proposed method is verified by simulating the WSNs with large numbers of sensor nodes in NS2. The RTD time results derived in hardware and software implementations are almost equal, justifying the real time applicability of the investigated method. Necessity of received signal strength measurement in cluster head variation and assigning separate wavelength for each link in other fault detection techniques are overcome here.

In-network outlier detection in wireless sensor networks

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy usage,(3) only uses single hop communication thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance using simulation with real sensor data streams. Our results demonstrate that our approach is accurate and imposes a reasonable communication load and level of power consumption.

Still Alive: Extending Keep-Alive Intervals in P2P Overlay Networks

Detecting node failures within Peer-to-Peer networks is an inherent trade-off between timely detection and consuming bandwidth on network maintenance. In the absence of user-driven messages, the majority of P2P networks rely upon the exchange of periodic keep-alive messages to maintain connections and network topology. We investigate three novel algorithms which prioritise keep-alive messages to nodes that are more likely to have failed. In doing so, these algorithms significantly reduce the expected delay between failures occurring and their subsequent detection in comparison to the standard approach, whilst consuming similar levels of bandwidth. Our algorithms build upon several studies that have shown that older peers are more likely to remain in the network than their short-lived counterparts. Each of our algorithms increase the interval between successive keep-alive messages as peers age in the system, based upon the distribution of peer session times and the current age of peers. We extensively describe the details of each algorithm, before comparing them to the standard periodic approach using simulations based upon measured network data. Furthermore, we show that these algorithms are complimentary to existing gossip-based mechanisms and investigate alternate methods of ascertaining a node’s age so that our algorithms can be robustly deployed in untrustworthy environments.

무선 센서 네트워크 모니터링 시스템을 위한 데이터 통계 분석 기반 데이터 필터링 기법

Recently, various monitoring systems are implemented actively by using wireless sensor networks(WSN). When implementing WSN-based monitoring system, there are three important issues to consider. At First, we need to consider a sensor node failure detection method to support the ongoing monitoring. Secondly, because sensor nodes use limited battery power, we need an efficient data filtering method to reduce energy consumption. At Last, a reducing processing overhead method is necessary. The existing Kalman filtering scheme has good performance on data filtering, but it causes too much processing overhead to estimate sensed data. To solve these problems, we, in this paper, propose a new data filtering scheme based on data statical analysis. First, the proposed scheme periodically aggregates node survival massages to support a node failure detection. Secondly, to reduce energy consumption, it sends the sample data with a node survival massage and do data filtering based on those messages. Finally, it analyzes the sample data to estimate filtering range in a server. As a result, each sensor node can use only simple compare operation for filtering data. In addition, we show from our performance analysis that the proposed scheme outperforms the Kalman filtering scheme in terms of the number of sending messages.

Connectivity monitoring in wireless sensor networks

Connectivity monitoring is useful in practical deployment of wireless sensor network. In order to understand the behavior and performance bottleneck, knowledge of the network connectivity is crucial. In this paper, we propose a flexible and efficient connectivity monitoring algorithm (H 2CM) that has three components and operates in a divide-and-conquer manner. The components include hop vector distance based filtering, Bloom filters and signature hashing and are designed to work with different combinations of network and neighbor set sizes. In simulation, communication cost reduction of H 2CM compare to maximal compression of neighborhood information varies from 65% to 85% for large networks (>1000 nodes) and from 40% to 70% for a medium size network (a few hundred nodes). We have also implemented the algorithm in TinyOS and evaluated its performance on a testbed with 34 motes. Lastly, we study the problem of node failure detection — a simple application of connectivity monitoring. We show that by combining H 2CM with the concept of dominating set, the communication cost can be drastically reduced compare to traditional data collection method.

An Improved Soft-Error Rate Measurement Technique

Soft errors caused by ionizing radiation have emerged as a major concern for current generation of CMOS technologies, and the trend is expected to get worse. The measurement unit for failures due to soft errors is failure in time (FIT) that represents the number of failures encountered per billion hours of device operation. FIT rate measurement is time consuming and calls for accelerated testing. To improve effectiveness of soft-error rate (SER) testing, the patterns must be targeted toward detecting node failures that are most likely. In this paper, we present a technique for identifying soft-error-susceptible sites based on efficient electrical analysis that treats soft errors as Boolean errors but uses analog strengths to decide whether such errors can propagate to the next stage. Next, we present pattern generation techniques for manifestable soft errors such that each pattern targets a maximal set of soft errors. These patterns maximize the likelihood of detecting a soft error when it occurs. The pattern generators target scan architecture. It is well known that scan test time is dominated by scan shifts, when no useful testing is being done. To improve efficiency of scan-based testing, we extend the functionality of the existing built-in logic block observation (BILBO) architecture to support test-per-clock operation. Such targeted pattern generation and test application improve SER characterization time by an order of magnitude.

Failure detectors for wireless sensor-actuator systems

Wireless sensor-actuator systems (WSAS) offer exciting opportunities for emerging applications by facilitating fine-grained monitoring and control, and dense instrumentation. The large scale of such systems increases the need for such systems to tolerate and cope with failures, in a localized and decentralized manner. We present abstractions for detecting node failures and link failures caused by topology changes in a WSAS. These abstractions were designed and implemented as a set of reusable components in nesC under TinyOS. Results, which demonstrate the performance and viability of the abstractions, based on experiments on an 80 node testbed are presented. In the future, these abstractions can be extended to detect and cope with larger classes of failures in WSAS.