Cloud computing is a new computing paradigm which features renting the computation devices instead of buying them. In a typical cloud computing environment, there will always be different kinds of cloud resources and a number of cloud services making use of cloud resources to run on. As we can see, these cloud services usually have different performance traits. Some may be I/O-intensive, like those data querying services, while others might demand more CPU cycles, like 3D image processing services. Meanwhile, cloud resources also have different kinds of capabilities such as data processing, I/O throughput, 3D image rendering, etc. A simple fact is that allocating a suitable resource will greatly improve the performance of the cloud service, and make the cloud resource itself more efficient as well. In this paper, a new cloud resource allocating algorithm via fitness-enabled auction is proposed to guarantee the fitness of performance traits between cloud resources (sellers) and cloud services (buyers). We study the allocating algorithm in terms of economic efficiency and system performance, and experiments show that the allocation is far more efficient in comparison with the continuous double auction in which the idea of fitness is not introduced.

Web services are becoming the prominent paradigm for distributing, computing, and electronic business, while there is an increasing surge to provide online business- to-business collaborations. The Web services choreography description language (WS-CDL) is a Web service specification developed by W3C, in order to provide peer-to-peer collaborations for participants from different parties. Despite the great research interests it has received during recent years, no practical or even prototype execution engine has been built for WS-CDL, which is, however, essential to test and evaluate the properties of WS-CDL when doing research on it, and promote its application fields in business. This paper implements an execution engine of WS-CDL, which has never been built before, and experiments on the functionalities and performance of the engine. We also address the extensions toward WS-CDL, namely WS- CDL+, which are built into our execution engine. Finally, the whole paper is concluded, addressing the application perspectives of WS-CDL/WS-CDL+.