Utilising stream reasoning techniques to underpin an autonomous framework for cloud application platforms

Rustem Dautov,Iraklis Paraskakis,Mike Stannett

doi:10.1186/s13677-014-0013-5

Abstract

As cloud application platforms (CAPs) are reaching the stage where the human effort required to maintain them at an operational level is unsupportable, one of the major challenges faced by the cloud providers is to develop appropriate mechanisms for run-time monitoring and adaptation, to prevent cloud application platforms from quickly dissolving into a non-reliable environment. In this context, the application of intelligent approaches to Autonomic Clouds may offer promising opportunities. In this paper we present an approach to providing cloud platforms with autonomic capabilities, utilising techniques from the Semantic Web and Stream Reasoning research fields. The main idea of this approach is to encode values, monitored within cloud application platforms, using Semantic Web languages, which then allows us to integrate semantically-enriched observation streams with static ontological knowledge and apply intelligent reasoning. Using such run-time reasoning capabilities, we have developed a conceptual architecture for an autonomous framework and describe a prototype solution we have constructed which implements this architecture. Our prototype is able to perform analysis and failure diagnosis, and suggest further adaptation actions. We report our experience in utilising the Stream Reasoning technique in this context as well as further challenges that arise out of our work.

Highlights

Cloud computing impacts upon almost every aspect of daily life and the economy – pervasive cloud services are revolutionising the way we do business, maintain our health, and educate and entertain ourselves
In this paper we have presented a novel approach to enhancing cloud platforms with self-managing capabilities
We have introduced a conceptual architecture which follows the MAPE-K reference model to implement closed adaptation loops, and a prototype framework developed in Java and deployed on Heroku

Summary

Introduction

Cloud computing impacts upon almost every aspect of daily life and the economy – pervasive cloud services are revolutionising the way we do business, maintain our health, and educate and entertain ourselves. As will be explained in more detail below, our approach relies on annotating monitored values with semantic descriptions, thereby enabling the framework to combine observation streams with static ontological knowledge and perform run-time formal reasoning.

Results

Conclusion