Failure Detection Service Research Articles

Low-Power Failure Detection for Environmental Monitoring Based on IoT

Many environmental monitoring applications that are based on the Internet of Things (IoT) require robust and available systems. These systems must be able to tolerate the hardware or software failure of nodes and communication failure between nodes. However, node failure is inevitable due to environmental and human factors, and battery depletion in particular is a major contributor to node failure. The existing failure detection algorithms seldom consider the problem of node battery consumption. In order to rectify this, we propose a low-power failure detector (LP-FD) that can provide an acceptable failure detection service and can save on the battery consumption of nodes. From simulation experiments, results show that the LP-FD can provide better detection speed, accuracy, overhead and battery consumption than other failure detection algorithms.

An energy-efficient failure detector for vehicular cloud computing

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.

A QoS-configurable failure detection service for internet applications

Unreliable failure detectors are a basic building block of reliable distributed systems. Failure detectors are used to monitor processes of any application and provide process state information. This work presents an Internet Failure Detector Service (IFDS) for processes running in the Internet on multiple autonomous systems. The failure detection service is adaptive, and can be easily integrated into applications that require configurable QoS guarantees. The service is based on monitors which are capable of providing global process state information through a SNMP MIB. Monitors at different networks communicate across the Internet using Web Services. The system was implemented and evaluated for monitored processes running both on single LAN and on PlanetLab. Experimental results are presented, showing the performance of the detector, in particular the advantages of using the self-tuning strategies to address the requirements of multiple concurrent applications running on a dynamic environment.

Low-Overhead Accrual Failure Detector

Failure detectors are one of the fundamental components for building a distributed system with high availability. In order to maintain the efficiency and scalability of failure detection in a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. In this paper, an new accrual failure detector—LA-FD with low system overhead has been proposed specifically for current mobile network equipment on the Internet whose processing power, memory space and power supply are all constrained. It does not rely on the probability distribution of message transmission time, or on the maintenance of a history message window. By simple calculation, LA-FD provides adaptive failure detection service with high accuracy to multiple upper applications. The related experiments and results have also been presented.

A Novel Failure Detection Algorithm for Reliable Distributed Systems

A failure detection service is perfect if it eventually detects all failures and every detection correctly identifies a failure that has occurred. Such a perfect failure detection service serves as a basic building block for many reliable distributed systems, for example in distributed lock services. In this paper, we introduce a perfect failure detection scheme in order to improve the fault tolerance of the service. We provide the precise system model and specification for a failure detection service. We present two novel algorithms that implement the failure detection service. We further develop a set of quality-of-service (QoS) metrics for perfect failure detection services, and apply probabilistic analysis to quantify the QoS metrics of the two algorithms.

Fault-Management in P2P-MPI

We present in this paper a study on fault management in a grid middleware. The middleware is our home-grown software called P2P-MPI. This framework is MPJ compliant, allows users to execute message passing parallel programs, and its objective is to support environments using commodity hardware. Hence, running programs is failure prone and a particular attention must be paid to fault management. The fault management covers two issues: fault-tolerance and fault detection. Fault-tolerance deals with the program execution: P2P-MPI provides a transparent fault tolerance facility based on replication of computations. Fault detection concerns the monitoring set of modules called failure detectors. The contribution of this paper is twofold. The first contribution is the evaluation of the failure probability of an application depending on the replication degree. The failure probability depends on the execution length, and we propose a model to evaluate the duration of a replicated parallel program. Then, we give an expression of the replication degree required to keep the failure probability of an execution under a given threshold. The second contribution is a study of the advantages and drawbacks of several fault detection systems found in the literature. The criteria of our evaluation are the reliability of the failure detection service and the failure detection speed. We retain the binary round-robin protocol for its failure detection speed, and we propose a variant of this protocol which is more reliable than the application execution in any case. Experiments involving of up to 256 processes, carried out on Grid'5000, show that the real detection times closely match the predictions.

A crash faults detection service for wireless and mobile ad hoc networks

PurposeThe purpose of this paper is to describe an adaptive approach for diagnosing faulty nodes in a wireless mobile environment.Design/methodology/approachBased on a diagnosis approach that has been previously developed for wired networks. A discussion of the novel diagnosis protocol and its correctness is also included.FindingsIn this paper, the author presents a new implementation of a failure detection service for wireless ad hoc and sensor systems that is based on an adaptation of a gossip‐style failure detection protocol and the heartbeat failure detector. The authors show that the failure detector is eventually perfect – that is, there is a time after which every faulty mobile is permanently suspected by every fault‐free host, and no host will be suspected before it crashes.Research limitations/implicationsThe main limitations of this work is the lack of simulations results. Future works will be directed at providing such performance evaluations.Practical implicationsThe work introduced in this paper aims mainly at identifying faulty nodes in a wireless mobile environment. This service has been identified as one of the basic building blocks for dependable mobile ad hoc networks (MANETs).Originality/valueThe paper is first work that adapts a previously developed failure detection service to wireless and MANETs.

Design of the notification system for failure detectors

It is widely recognised that distributed systems would greatly benefit from the availability of a generic failure detection service. In this paper, we highlighted the issue on the construction of the monitoring network of failure detectors. We proposed an algorithm to construct and manage the monitoring network that each failure detector is monitored by some failure detectors. Notification of failures is propagated along the network. Especially it can involve various types of failure detectors from simple timeout-based failure detectors to accrual failure detectors, and help to spread information on suspected processes/nodes. In addition, we have made a simulation of the proposed algorithm for constructing the monitoring network. It shows that the algorithm is scalable for increasing the number of failure detectors.

DRIC: Dependable Grid Computing Framework

Grid computing presents a new trend to distributed and Internet computing to coordinate large scale resources sharing and problem solving in dynamic, multi-institutional virtual organizations. Due to the diverse failures and error conditions in the grid environments, developing, deploying, and executing applications over the grid is a challenge, thus dependability is a key factor for grid computing. This paper presents a dependable grid computing framework, called DRIC, to provide an adaptive failure detection service and a policy-based failure handling mechanism. The failure detection service in DRIC is adaptive to users' QoS requirements and system conditions, and the failure-handling mechanism can be set optimized based on decision-making method by a policy engine. The performance evaluation results show that this framework is scalable, high efficiency and low overhead.

A Flexible Framework for Fault Tolerance in the Grid

This paper presents a failure detection service (FDS) and a flexible failure handling framework (Grid-WFS) as a fault tolerance mechanism on the Grid. The FDS enables the detection of both task crashes and user-defined exceptions. A major challenge in providing such a generic failure detection service on the Grid is to detect those failures without requiring any modification to both the Grid protocol and the local policy of each Grid node. This paper describes how to overcome the challenge by using a notification mechanism which is based on the interpretation of notification messages being delivered from the underlying Grid resources. The Grid-WFS built on top of FDS allows users to achieve failure recovery in a variety of ways depending on the requirements and constraints of their applications. Central to the framework is flexibility in handling failures. This paper describes how to achieve the flexibility by the use of workflow structure as a high-level recovery policy specification, which enables support for multiple failure recovery techniques, the separation of failure handling strategies from the application code, and user-defined exception handlings. Finally, this paper presents an experimental evaluation of the Grid-WFS using a simulation, demonstrating the value of supporting multiple failure recovery techniques in Grid applications to achieve high performance in the presence of failures.

Experimental Analysis of a Gossip-Based Service for Scalable, Distributed Failure Detection and Consensus

Gossip protocols and services provide a means by which failures can be detected in large, distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. Extending the gossip protocol such that a system reaches consensus on detected faults can be performed via a flat structure, or it can be hierarchically distributed across cooperating layers of nodes. In this paper, the performance of gossip services employing flat and hierarchical schemes is analyzed on an experimental testbed in terms of consensus time, resource utilization and scalability. Performance associated with a hierarchically arranged gossip scheme is analyzed with varying group sizes and is shown to scale well. Resource utilization of the gossip-style failure detection and consensus service is measured in terms of network bandwidth utilization and CPU utilization. Analytical models are developed for resource utilization and performance projections are made for large system sizes.

Simulative performance analysis of gossip failure detection for scalable distributed systems

Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. The hierarchical protocol leverages the underlying network topology to achieve faster failure detection. In addition to studying the effectiveness and efficiency of these two agreement protocols, we propose a third protocol that extends the hierarchical approach by piggybacking gossip information on application-generated messages. The protocols are simulated and evaluated with a fault-injection model for scalable distributed systems comprised of clusters of workstations connected by high-performance networks, such as the CPlant system at Sandia National Laboratories. The model supports permanent and transient node and link failures, with rates specified at simulation time, for processors functioning in a fail-silent fashion. Through high-fidelity, CAD-based modeling and simulation, we demonstrate the strengths and weaknesses of each approach in terms of agreement time, number of gossips, and overall scalability.