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Abstract-PaaS (Platform as a service) is an increasingly popular cloud model, providing a complete development and hosting environment for cloud applications. As the use of PaaS becomes pervasive, defining and maintaining SLAs (Service Level Agreements) between PaaS customers and providers becomes essential. Useful SLAs should provide guarantees on application quality properties (e.g., response time) rather than on resource availability (e.g., number of virtual machines). Current PaaS offerings either provide no support for providing such guarantees or provide support targeting a restricted set of application types. In this paper, we propose an SLA-driven PaaS architecture, called Meryn, which supports cloud bursting and is designed to be easily extensible to host new application types. Meryn relies on a decentralized optimization policy that aims at maximizing the overall provider profit, taking into account the payment of penalties incurred when quality guarantees are unsatisfied. We implemented and evaluated a prototype of the Meryn system through a series of simulations on the Grid5000 testbed.The results show that our approach provides up to 14.77% more profit for the provider and uses up to 80.99% less public clouds resources compared with a basic approach.

Abstract. Distributed operating systems simplify building and executing applications on large-scale infrastructures, such as clusters, grids and clouds. These systems operate in a constantly changing environment characterized by varying application needs and varying physical infrastructure capabilities. To handle the diversity and dynamism of both the applications and the underlying infrastructures, the distributed Operating System (OS) should continually adapt to its changing environment. Two challenges arise in this context: how to design the distributed OS in order to facilitate dynamic adaptation, and how to ensure that OS-level adaptation does not conflict with application-level adaptation. This paper proposes to address these challenges by: (1) building the distributed OS as an assembly of adaptable services following the service-oriented architecture; and (2) using a common multi-level adaptation framework to adapt both the OS and the application layers in a coordinated way. Moreover, the paper presents experimental evidence of the usefulness of this approach in adapting the distributed shared memory service of a specific distributed OS.

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International audienceThe socioeconomic impact of cloud solutions and particularly PaaS (platform as a service) solutions is becoming increasingly critical. The main objective of PaaS providers is to generate the maximum profit from the services they provide. This requires them to face a number of challenges such as efficiently managing the underlying resources and satisfying the SLAs of the hosted applications. In this paper, we consider a cloud-bursting PaaS environment where the PaaS provider owns some private resources and is able to rent public cloud resources on demand. In that context, we propose a profit-efficient solution for managing such a system under SLA constraints. We define a profit optimization policy that evaluates the cost of hosting each application using public and private resources and chooses the option that generates the highest profit. During peak periods, the optimization policy considers two more options. The first option is to obtain some resources from running applications, taking into account the payment of penalties if their promised quality of service is affected. The second option is to wait until private resources become available, taking into account the payment of penalties if the quality of service promised to the new application is affected. Furthermore, we designed and implemented an open cloud-bursting PaaS system, called Meryn, which integrates the proposed optimization policy and provides support for batch and MapReduce applications. The results of our evaluation show the effectiveness of our approach in optimizing the provider profit. Indeed, compared to a basic approach, our approach provides up to 11.59% and 9.02% more provider profit in, respectively, simulations and experiments