Architectural styles and the design of network-based software architectures
Architectural styles and the design of network-based software architectures
Scalable Run-Time Correlation Engine for Monitoring in a Cloud Computing Environment
ECBS '10 Proceedings of the 2010 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
Lightweight Policy-Based Management of Quality-Assured, Device-Based Service Systems
WAINA '10 Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops
Otus: resource attribution in data-intensive clusters
Proceedings of the second international workshop on MapReduce and its applications
A Software Architecture for the Analysis of Large Sets of Data Streams in Cloud Infrastructures
CIT '11 Proceedings of the 2011 IEEE 11th International Conference on Computer and Information Technology
Tool-Supported Refinement of High-Level Requirements and Constraints Into Low-Level Policies
POLICY '11 Proceedings of the 2011 IEEE International Symposium on Policies for Distributed Systems and Networks
Andes: A Highly Scalable Persistent Messaging System
ICWS '12 Proceedings of the 2012 IEEE 19th International Conference on Web Services
| Hi-index | 0.00 |
Although cloud computing has become an important topic over the last couple of years, the development of cloud-specific monitoring systems has been neglected. This is surprising considering their importance for metering services and, thus, being able to charge customers. In this paper we introduce a monitoring architecture that was developed and is currently implemented in the EASI-CLOUDS project. The demands on cloud monitoring systems are manifold. Regular checks of the SLAs and the precise billing of the resource usage, for instance, require the collection and converting of infrastructure readings in short intervals. To ensure the scalability of the whole cloud, the monitoring system must scale well without wasting resources. In our approach, the monitoring data is therefore organized in a distributed and easily scalable tree structure and it is based on the Device Management Specification of the OMA and the DMT Admin Specification of the OSGi. Its core component includes the interface, the root of the tree and extension points for sub trees which are implemented and locally managed by the data suppliers themselves. In spite of the variety and the distribution of the data, their access is generic and location-transparent. Besides simple suppliers of monitoring data, we outline a component that provides the means for storing and preprocessing data. The motivation for this component is that the monitoring system can be adjusted to its subscribers - while it usually is the other way round. In EASI-CLOUDS, the so-called Context Stores aggregate and prepare data for billing and other cloud components.