A self-management framework for efficient resource discovery in pervasive environments

Authors:
Apostolos Malatras;Fei Peng;Béat Hirsbrunner
Affiliations:
University of Fribourg, Fribourg, Switzerland;University of Fribourg, Fribourg, Switzerland;University of Fribourg, Fribourg, Switzerland
Venue:
Proceedings of the 8th ACM international conference on Autonomic computing
Year:
2011

Citing 2
Cited 1

Proactive information caching for efficient resource discovery in a self-structured grid

BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
A Programmable Framework for the Deployment of Services and Protocols in Mobile Ad Hoc Networks

IEEE Transactions on Network and Service Management

Semantic agent system for automatic mobilization of distributed and heterogeneous resources

Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics

Quantified Score

Hi-index	0.00

Visualization

Abstract

When considering resource discovery in pervasive environments, issues such as the diversity of application requirements, different classes of Quality of Service (QoS), device and network heterogeneity should be addressed. In these cases, static solutions prove to be ineffective since the desired characteristics of resource discovery mechanisms are constantly changing. To alleviate such problems, a promising direction involves self-management approaches that allow for adaptation of the monitoring mechanisms and their automatic reconfiguration. Accordingly, we present our ongoing work on a context-aware, policy-based framework to support the autonomic management of pervasive environments' monitoring mechanisms that rely on dynamic, bio-inspired P2P overlays.