Workflow systems have become a major vehicle for easy and efficient development of scientific applications. This type of systems can benefit from the resource provisioning technology offered by the cloud computing. In fact, the latter offers on-demand virtualized resources to its users. These virtual resources can be added and released dynamically. Also, users are charged on a pay-per-use basis. How to make appropriate decisions when allocating resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. The amount of allocated resources affects the execution time of the applications and the cost incurred by the user. In fact, resource under-provisioning will necessarily affect the performance. In contrast, over-provisioning can result in idle instances and cause additional costs. Then, efficient scheduling algorithms are required for selection of best suitable resources for task execution. This paper focuses on some of the important workflow scheduling strategies. It brings out an exhaustive survey of such strategies in cloud computing and includes a detailed classification of them. Then, it presents a comparative analysis of the studied approaches. Finally, it stands out a critical challenge for further research.
Abstract. Today, adaptable and distributed component based systems need to be checked and validated in order to ensure their correctness and trustworthiness when dynamic changes occur. Traditional testing techniques can not be used since they are applied during the development phase. Therefore, runtime testing is emerging as a novel solution for the validation of highly dynamic systems at runtime. In this paper, we illustrate how a platform independent test system based on the TTCN-3 standard can be used to execute runtime tests. The proposed test system is called TT4RT: TTCN-3 test system for Runtime Testing. A case study in the telemedicine field is used as an illustration to show the relevance of the proposed test system.
Workflow technologies have become an efficient mean for the development of different applications. One wellknown challenge for executing workflows on cloud computing is the resources provisioning. The latter consists in making an appropriate decision when mapping tasks to resources considering multiple objectives that are often contradictory. The problem of resources provisioning for workflow applications in the cloud has been widely studied in the literature. However, the existing works didn't consider the change in workflow instances at runtime. This functionality has become a major requirement to deal with unusual situations and evolutions. In this paper, we present a first step towards the resources provisioning for a dynamic workflow in the cloud. In fact, we propose a provisioning algorithm which takes into account some constraints. After that, we extend it in order to support the dynamic changes of workflow. Our algorithm is evaluated using CloudSim simulator. The different experiments that we present show the efficiency of our approach in terms of financial execution cost and overhead.
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