Design and evaluation of elastic media resource allocation algorithms using CloudSim extensions

With the maturity of Cloud computing comes research into converting a range of traditionally best effort programs into cloud-enabled services. One such service currently under investigation in the Elastic Media Distribution (EMD) project, is how to enable qualitative, reliable and scalable real-time media collaboration services using proven Cloud technology. While existing best-effort solutions provide plenty of features, they do not provide the quality guarantees and reliability required for critical services in globally distributed corporations. On the other hand, some pricey dedicated solutions do offer these low-delay, reliable cooperation services, but without the benefits that clouds can bring in terms of scalability. In this paper we describe results attained in the EMD project on novel resource provisioning algorithms for a mixture of end-to-end Audio/Video streams with file-based transfers, allowing for configurable trade-offs between service response time and cost. We extended the CloudSim simulator with models allowing us to simulate collaborative interactive sessions (more specifically educational real-time collaboration), and evaluated the performance of our proposed provisioning heuristics. The results show that the proposed dynamic algorithm allows for automated cost-performance trade-off by reducing average total Virtual Machine (VM) cost by a maximum of 58% compared to more naive approaches, while keeping average time for clients to join a meeting in line

Data as a Service (DaaS) for sharing and processing of large data collections in the cloud

Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft

SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions

Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated services to users and meet their quality expectations. Existing resource management systems in data centers are yet to support Service Level Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to realize cloud computing and utility computing. In addition, no work has been done to collectively incorporate customer-driven service management, computational risk management, and autonomic resource management into a market-based resource management system to target the rapidly changing enterprise requirements of Cloud computing. This paper presents vision, challenges, and architectural elements of SLA-oriented resource management. The proposed architecture supports integration of marketbased provisioning policies and virtualisation technologies for flexible allocation of resources to applications. The performance results obtained from our working prototype system shows the feasibility and effectiveness of SLA-based resource provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011, IEEE Press, USA), Hong Kong, China, December 12-14, 201