Towards Self-Healing in Wireless Sensor Networks

Bourdenas, Themistoklis; Sloman, Morris

doi:10.1109/bsn.2009.14

Cited by 21 publications

(14 citation statements)

References 8 publications

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“…In [22] a self-healing framework(primarily for Wireless Sensor Networks), which enables a flexible choice of components for detection and masking of faults as well as reconfiguration of the network is proposed. Here the correlation feature between two pairs of sensor signals is used as a metric for fault detection.…”

Section: Related Work On Models and Architectures Of Self-healingmentioning

confidence: 99%

A parameter-influencer based model of a Self-healing network

Raghunandan

Bedekar

2011

2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)

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Autonomic features can be built into systems by including Self-* properties. There is a dire need to find new techniques of building in Self-* features in networks for delivering important goals like maintaining uptime and QoS, since system adminstrators are crying for help as complexity of networks and their management systems continues to grow unabatedly and managing them effectively and efficiently turning out to be a veritable nightmare. In this paper we describe how a correlation based parameter-influencer model can be used to build in Selfhealing features in a network. We describe various combinations of parameters and influencers which can be used to model features of varying complexity that can be added to networking systems. Statistical techniques like linear regression are used to identify positive and negative correlation amongst parameters and influencers and changes made by the Autonomic Manager(AM) or the network management systems (NMS) to bring the network to a state of stability and thus reduce downtime. Our model is programmed as daemon on the network and two case studies are described where historical data is used to tune the network parameters more accurately. The first demonstrates how uptime can be sustained and the second demonstrates how performance (and in turn QoS) can be maintained.

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Section: Related Work On Models and Architectures Of Self-healingmentioning

confidence: 99%

A parameter-influencer based model of a Self-healing network

Raghunandan

Bedekar

2011

2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)

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“…al. specify policies as Java classes in the Prism-MX platform [22]; IRIDIUM adaptation policies map faulttree-like rules to an action, at a configurable evaluation rate [27]; Starfish provides a policy language that supports event-condition-actions as well as authorization (which Stitch does not have) [31]; Vogel and Giese's modeldriven approach specifies adaptation policies in terms of model transformation rules [32]; although versatile and powerful, these policy mechanisms lack support for timing and uncertainty, and make it difficult to specify impact on quality-of-service and, thus, to resolve conflicts as well as to make QoSbased choice of the best adaptation. PBAAM [33] and StarMX [28] specify policies as expert system rules, which supports notions of uncertainty, but does not inherently support QoS evaluation, conflict resolution, and settling time.…”

Section: Languages For Specifying Adaptation Policiesmentioning

confidence: 99%

Stitch: A language for architecture-based self-adaptation

Cheng

Garlan

2012

Journal of Systems and Software

133

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Requirements for high availability in computing systems today demand that systems be self-adaptive to maintain expected qualities-of-service in the presence of system faults, variable environmental conditions, and changing user requirements. Autonomic computing tackles the challenge of automating tasks that humans would otherwise have to perform to achieve this goal. However, existing approaches to autonomic computing lack the ability to capture routine human repair tasks in a way that takes into account the business context that humans use in selecting an appropriate form of adaptation, while dealing with timing delays and uncertainties in outcome of repair actions. In this article, we present Stitch, a language for representing repair strategies within the context of an architecture-based self-adaptation framework. Stitch supports the explicit representation of repair decision trees together with the ability to express business objectives, allowing a self-adaptive system to select a strategy that has optimal utility in a given context, even in the presence of potential timing delays and outcome uncertainty.

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“…The Starfish framework [10] supports development of adaptive, autonomous applications for power constrained, embedded devices running the TinyOS 2.x operating system. It is a realisation of the Self-Managed Cell (SMC) architecture [9] that incorporates the basic building blocks to form federations of autonomous components that compose to large-scale autonomic systems.…”

Section: Starfish Frameworkmentioning

confidence: 99%

Autonomic Role and Mission Allocation Framework for Wireless Sensor Networks

Bourdenas

Tei

Honiden

et al. 2011

2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems

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Abstract-Pervasive applications incorporate physical components that are exposed to everyday use and a large number of conditions and external factors that can lead to faults and failures. It is also possible that application requirements change during deployment and the network needs to adapt to a new context. Consequently, pervasive systems must be capable to autonomically adapt to changing conditions without involving users becoming a transparent asset in the environment. In this paper, we present an autonomic mechanism for initial task assignment in sensor networks, an NP-hard problem. We also study on-line adaptation of the original deployment which considers real-time metrics for maximising utility and lifetime of applications and smooth service degradation in the face of component failures.

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Towards Self-Healing in Wireless Sensor Networks

Cited by 21 publications

References 8 publications

A parameter-influencer based model of a Self-healing network

A parameter-influencer based model of a Self-healing network

Stitch: A language for architecture-based self-adaptation

Autonomic Role and Mission Allocation Framework for Wireless Sensor Networks

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