On the Reliability of Large-Scale Distributed Systems A Topological View

He, Yuan; Ren, Hao; Yang, Baijian

doi:10.1109/icpp.2008.9

Cited by 6 publications

(6 citation statements)

References 42 publications

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“…Generally, determining critical nodes has been investigated in various network contexts such as P2P [10] and overlay networks [7,[11][12][13]. Several reasons such as ad hoc and wireless nature and dynamic conditions make these approaches unsuitable for MAHSNs.…”

Section: Related Workmentioning

confidence: 99%

Formal Specification and Validation of a Localized Algorithm for Segregation of Critical/Noncritical Nodes in MAHSNs

Alnuem

Zafar

Imran

et al. 2014

International Journal of Distributed Sensor Networks

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Timely segregation of critical/noncritical nodes is extremely crucial in mobile ad hoc and sensor networks. Most of the existing segregation schemes are centralized and require maintaining network wide information, which may not be feasible in large-scale dynamic networks. Moreover, these schemes lack rigorous validation and entirely rely on simulations. We present a localized algorithm for segregation of critical/noncritical nodes (LASCNN) to the network connectivity. LASCNN establishes and maintains a k-hop connection list and marks a node as critical if its k-hop neighbours become disconnected without the node and noncritical otherwise. A noncritical node with more than one connection is marked as intermediate and leaf noncritical otherwise. We use both formal and nonformal techniques for verification and validation of functional and nonfunctional properties. First, we model MAHSN as a dynamic graph and transform LASCNN to equivalent formal specification using Z notation. After analysing and validating the specification through Z eves tool, we simulate LASCNN specification to quantitatively demonstrate its efficiency. Simulation experiments demonstrate that the performance of LASCNN is scalable and is quite competitive compared to centralized scheme with global information. The accuracy of LASCNN in determining critical nodes is 87% (1-hop) and 93% (2-hop) and of noncritical nodes the accuracy is 91% (1-hop) and 93% (2-hop).

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Section: Related Workmentioning

confidence: 99%

Formal Specification and Validation of a Localized Algorithm for Segregation of Critical/Noncritical Nodes in MAHSNs

Alnuem

Zafar

Imran

et al. 2014

International Journal of Distributed Sensor Networks

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“…Secondly, the accurate ratio of articulation point is lower on dynamic network. Localized Detection Algorithm for Articulation Points.There are some related works about localized algorithms [2,5,6,9]. The CUD [2] could be applied to dynamic networks.…”

Section: Related Workmentioning

confidence: 99%

“…Localized Detection Algorithm for Articulation Points.There are some related works about localized algorithms [2,5,6,9]. The CUD [2] could be applied to dynamic networks. Hence, we discuss and compare with the CUD.…”

Section: Related Workmentioning

confidence: 99%

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LDFS: Localized Depth First Search for Member Loss Detection of Moving Group in Wireless Networks

Chang

Sun

et al. 2013

AMM

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In a distributed system, a portion of nodes are more critical than others, and named them articulation points, all paths between certain nodes have to pass through these points. Most of previous works try to detect the articulation point problem in static networks such as wireless sensor networks, P2P networks. In dynamic networks, as group moving behavior, it is a challenge to detect articulation points because these nodes are moving with time. Group moving in this paper means that a group of mobile members move from one place to another place with different directions and speeds. We aim to propose a distributed LDFS algorithm to check the articulation points in dynamic networks, such as a moving group. The algorithm sets the number of hops for traversing and multiple initiators to reduce message overhead and improve the accuracy rate. In simulations, we design several schemes to compare message overhead, and correctness. Simulation results show that our scheme is better than GlobalDFS and CUD scheme. The scheme could be applied on different applications and is efficient helping us to save and alarm loss on group moving.

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“…In order to provide qualified services, many applications require overlays [5] to guarantee reliability and avoid network failures [6]. For a large-scale distributed system, it is often not cost-effective to protect all the nodes [7]. While node failures may affect network coverage [8] and connectivity, this paper focuses on both, especially on maintaining the latter when a node is lost.…”

Section: System Model and Problem Statementmentioning

confidence: 99%

Application-Oriented Fault Detection and Recovery Algorithm for Wireless Sensor and Actor Networks

Xie

Sun

et al. 2012

International Journal of Distributed Sensor Networks

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Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In WSANs, maintaining interactor connectivity is of vital concern in order to reach application level. Failure of a critical actor may partition the inter-actor network into disjoint segments. This paper proposed an application-oriented fault detection and recovery algorithm (AFDR), a novel distributed algorithm to reestablish connectivity. AFDR identifies critical actors and designates backups for them. A backup actor detects the critical node failure and initiates a recovery process via moving to the optimal position. The purpose of AFDR is to satisfy application requirements, reduce recovery overhead, and limit the impact of critical node failure on coverage and connectivity to the utmost. The effectiveness of AFDR is validated through simulation experiments.

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On the Reliability of Large-Scale Distributed Systems A Topological View

Abstract: Abstract

Cited by 6 publications

References 42 publications

Formal Specification and Validation of a Localized Algorithm for Segregation of Critical/Noncritical Nodes in MAHSNs

Formal Specification and Validation of a Localized Algorithm for Segregation of Critical/Noncritical Nodes in MAHSNs

LDFS: Localized Depth First Search for Member Loss Detection of Moving Group in Wireless Networks

Application-Oriented Fault Detection and Recovery Algorithm for Wireless Sensor and Actor Networks

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