review的例子

       This paper is written by two professors and two postgraduates,published in Ruan Jian Xue Bao/Journal of Software.The main contents of managing and allocating the resources in cloud environment are studied.

      In cloud environment, all kinds of idle resources can be pooled to establish a resource pool, and different kinds of resources can be combined as a service to the users through virtualization. In this paper, economic and intelligent methods are employed to form an intelligent resource allocation scheme based on double combinatorial auction with respect to the characteristics of resources in cloud environment.In the  scheme,a system on the basis of quality of experience (QoE) is devised, providing QoE support to resource dealing.In order to determine bidding price rationally, a bidding price decision mechanism based on back propagation (BP) neural network is presented to comprehensively consider various influence factors to make price adapt to the fluctuating market.Finally,simulation studies are conducted to demonstrate the feasibility and effectiveness of the proposed scheme.

       This paper is of great significance.Through the scheme,It can support any auctions of multiple resources and decrease the negative effects of malicious behaviors on resource auctions.The paper is clear in logic.In System framework part, paper gives five roles : cloud service provider,provider agent,cloud service consumer,consumer agent,auction intermediary,and shows relationships between the roles. In QoE system,the paper provides QoE support to resource dealing through algorithm process. In Auction protocol part,there are several subparts: provider Bid    description,consumer Bid description, provider Total quotation,Rule of winning Bid Each subpart is introduced in detail. In Bidding price decision part,it's about getting PA and CA to make rational decisions. That Mainly in order to increase the benefits of both parties.The factors affecting the final bid are complex, it is difficult to find a bidding formula that takes all factors into account.Therefore, BP neural network is introduced to solve this problem. Because,a three-layer neural network can be approximate to any function.Due to the fact that the problem of winner determination in combinatorial auction is NP-complete. The strategy of winning the bidding part gives a method,a group search optimization algorithm is adopted to find the specific resource allocation solution with market surplus and total reputation optimized.The final part,simulation studies are base on SimJava2.0 tools and uses JDK 1.6 to implement the study.It compare in several cases to show the superiority of the method.The study conducted to demonstrate the feasibility and effectiveness of the proposed scheme.

      The structure of the paper is clear and easy to understand.That is well organized and well written.