Evaluator services for optimised service placement in distributed heterogeneous cloud infrastructures

Optimal placement of demanding real-time interactive applications in a distributed heterogeneous cloud very quickly results in a complex tradeoff between the application constraints and resource capabilities. This requires very detailed information of the various requirements and capabilities of the applications and available resources. In this paper, we present a mathematical model for the service optimization problem and study the concept of evaluator services as a flexible and efficient solution for this complex problem. An evaluator service is a service probe that is deployed in particular runtime environments to assess the feasibility and cost-effectiveness of deploying a specific application in such environment. We discuss how this concept can be incorporated in a general framework such as the FUSION architecture and discuss the key benefits and tradeoffs for doing evaluator-based optimal service placement in widely distributed heterogeneous cloud environments

Challenges for the comprehensive management of cloud services in a PaaS framework

The 4CaaSt project aims at developing a PaaS framework that enables flexible definition, marketing, deployment and management of Cloud-based services and applications. The major innovations proposed by 4CaaSt are the blueprint and its lifecycle management, a one stop shop for Cloud services and a PaaS level resource management featuring elasticity. 4CaaSt also provides a portfolio of ready to use Cloud native services and Cloud-aware immigrant technologies

A service broker for Intercloud computing

This thesis aims at assisting users in finding the most suitable Cloud resources taking into account their functional and non-functional SLA requirements. A key feature of the work is a Cloud service broker acting as mediator between consumers and Clouds. The research involves the implementation and evaluation of two SLA-aware match-making algorithms by use of a simulation environment. The work investigates also the optimal deployment of Multi-Cloud workflows on Intercloud environments

Challenges for orchestration and instance selection of composite services in distributed edge clouds

Today's centralized cloud-computing infrastructures have not been designed with geo-localized, personalized, bandwidth/processing-intensive, real-time applications in mind. High network delay and low throughput can have a significant impact on the user experience. Instead, such services could be deployed in distributed service nodes at the edge of the network, closer to the user. In this paper we focus on composite services of which the components are running in different service nodes. We present a two-layer framework that provides service orchestration and instance selection. We present the orchestration mechanisms to enable the flexible re-use of components across different composite services. For the resolution layer of our framework, we present two modes of operation that combine network and service availability information for efficient per-request instance selection among a multitude of service replicas