Towards Supporting Interactions between Self-Managed Cells

Schaeffer-Filho, Alberto; Lupu, Emil; Dulay, Naranker; Keoh, Sye Loong; Twidle, K.; Sloman, Morris; Heeps, S.; Strowes, Stephen D.; Sventek, J.

doi:10.1109/saso.2007.64

Cited by 11 publications

(16 citation statements)

References 13 publications

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“…Once an SMC is assigned to a role, policies previously associated with a role (i.e., having that role as subject or target) will then apply to SMCs assigned to it. This allows us to specify policies governing the interactions with an SMC before that SMC is discovered [3].…”

Section: Self-managed Cells and Their Interactionsmentioning

confidence: 99%

Verification of Policy-Based Self-Managed Cell Interactions Using Alloy

Schaeffer-Filho

Lupu

Sloman

et al. 2009

2009 IEEE International Symposium on Policies for Distributed Systems and Networks

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Self-Managed Cells (SMCs) define an infrastructure for building ubiquitous computing applications. An SMC consists of an autonomous administrative domain based on a policy-driven feedback control-loop. SMCs are able to interact with each other and compose with other SMCs to form larger autonomous components. In this paper we present a formal specification of an SMC's behaviour for the analysis and verification of its operation in collaborations of SMCs. These collaborations typically involve SMCs originated from different administrative authorities, and the definition of a formal model has helped us to verify the correctness of their operation when SMCs are composed or federated.

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Section: Self-managed Cells and Their Interactionsmentioning

confidence: 99%

Verification of Policy-Based Self-Managed Cell Interactions Using Alloy

Schaeffer-Filho

Lupu

Sloman

et al. 2009

2009 IEEE International Symposium on Policies for Distributed Systems and Networks

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“…The adaptive management of UAVs is achieved using policy-based techniques that allow dynamic modification of the management strategy relating to resources, task behaviour, communications and team management, without reloading the basic software within the UAV. SMCs can be combined in peer-to-peer or composition relationships to reflect complex collaborations between multiple teams to achieve an overall mission [36].…”

Section: Introductionmentioning

confidence: 99%

Self-Management Framework for Mobile Autonomous Systems

et al. 2011

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The advent of mobile and ubiquitous systems has enabled the development of autonomous systems such as wireless-sensors for environmental data collection and teams of collaborating Unmanned Autonomous Vehicles (UAVs) used in missions unsuitable for humans. However, with these range of new application-domains come a new challenge -enabling self-management in mobile autonomous systems. Autonomous systems have to be able to manage themselves individually as well as to form self-managing teams which are able to recover or adapt to failures, protect themselves from attacks and optimise performance.This paper proposes a novel distributed policy-based framework that enables autonomous systems of varying scale to perform self-management individually and as a team. The framework allows missions to be specified in terms of roles in an adaptable and reusable way, enables dynamic and secure team formation with a utility-based approach for optimal role assignment, caters for communication link maintenance amongst team-members and recovery from failure. Adaptive management is achieved by employing a policy-based architecture to enable dynamic modification of the management strategy relating to resources, role behaviour, communications and team management, without interrupting the basic software within the system. Evaluation of the framework shows that it is scalable with respect to the number of roles, and consequently the number of autonomous systems participating in the mission. It is also shown to be optimal with respect to role assignments, and robust to intermittent communication link disconnections and permanent team-member failures.

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“…The adaptive management of UAVs is achieved by using policy-based techniques that allow dynamic modification of the management strategy relating to resources, task behaviour, communications and team management, without reloading the basic software within the UAV. SMCs can be combined in peer-to-peer or composition relationships to reflect complex collaborations between multiple teams to achieve an overall mission [4].…”

Section: Introductionmentioning

confidence: 99%

A policy-based management architecture for mobile collaborative teams

Asmare

Gopalan

Sloman

et al. 2009

2009 IEEE International Conference on Pervasive Computing and Communications

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Abstract-Many missions are deemed dangerous or impractical to perform by humans, but can use collaborating, self-managing Unmanned Autonomous Vehicles (UAVs) which adapt their behaviour to current context, recover from component failure or optimise performance. This paper describes a policy-based distributed self-management framework for both individual and teams of UAVs. We use three levels of specifications -policy, mission class and mission instance to enable reuse of both policies and mission classes. The architecture has been tested on devices ranging from small laptops to body area networks. Initial evaluation shows the distributed architecture is scalable and outperforms a centralised mission management scheme.

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Towards Supporting Interactions between Self-Managed Cells

Abstract: Abstract

Cited by 11 publications

References 13 publications

Verification of Policy-Based Self-Managed Cell Interactions Using Alloy

Verification of Policy-Based Self-Managed Cell Interactions Using Alloy

Self-Management Framework for Mobile Autonomous Systems

A policy-based management architecture for mobile collaborative teams

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