Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
An Architecture-Based Approach to Self-Adaptive Software
IEEE Intelligent Systems
An Artificial Intelligence Perspective on Autonomic Computing Policies
POLICY '04 Proceedings of the Fifth IEEE International Workshop on Policies for Distributed Systems and Networks
The dawning of the autonomic computing era
IBM Systems Journal
Research directions in reflective middleware: the Lancaster experience
ARM '04 Proceedings of the 3rd workshop on Adaptive and reflective middleware
A survey of autonomic computing—degrees, models, and applications
ACM Computing Surveys (CSUR)
OGC® Sensor Web Enablement: Overview and High Level Architecture
GeoSensor Networks
IEEE Internet Computing
Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda
IEEE Internet Computing
Foundations of Semantic Web Technologies
Foundations of Semantic Web Technologies
A native and adaptive approach for unified processing of linked streams and linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Ontology paper: The SSN ontology of the W3C semantic sensor network incubator group
Web Semantics: Science, Services and Agents on the World Wide Web
Enabling Query Technologies for the Semantic Sensor Web
International Journal on Semantic Web & Information Systems
Proceedings of the 2013 international workshop on Hot topics in cloud services
A vision for monitoring cloud application platforms as sensor networks
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Semantic-based QoS management in cloud systems: Current status and future challenges
Future Generation Computer Systems
Utilising Stream Reasoning Techniques to Create a Self-Adaptation Framework for Cloud Environments
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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As computing systems evolve and mature, they are also expected to grow in size and complexity. With the continuing paradigm shift towards cloud computing, these systems have already reached the stage where the human effort required to maintain them at an operational level is unsupportable. Therefore, the development of appropriate mechanisms for run-time monitoring and adaptation is essential to prevent cloud platforms from quickly dissolving into a non-reliable environment. In this paper we present our approach to enable cloud application platforms with self-managing capabilities. The approach is based on a novel view of cloud platforms as networks of distributed data sources - sensors. Accordingly, we propose utilising techniques from the Sensor Web research community to address the challenge of monitoring and analysing continuously flowing data within cloud platforms in a timely manner.