Abstract The collaboration among different organizations is considered one of the main benefits of moving applications and services to a cloud computing environment. Unfortunately, this collaboration raises many challenges such as the access of sensitive resources by unauthorized people. Usually, Role-Based Access-Control (RBAC) model is deployed in large organizations. This paper addresses the scalability problem of the online stored rules. This problem affects the performance of the access control system due to increasing number of shared resources and/or number of collaborating organizations in the same cloud environment. Therefore, this paper proposes replacing the cross-domain RBAC rules with Role-To-Role (RTR) mapping rules among all organizations. The RTR mapping rules are generated using a newly proposed Role-Mapping algorithm. A comparative study is performed to evaluate the proposed algorithm’s performance with concerning the Rule-Store size and the authorization response time. According to the results, it is found that the proposed algorithm reduces the number of stored rules which minimizes the Rule-Store size and reduces the authorization response time. Additionally, this paper proposes applying a concurrent approach on the RTR mapping model using the proposed Role-Mapping algorithm to achieve more savings in the authorization response time. Therefore, it will be suitable in highly-collaborative cloud environments.

In PaaS model, providers have different proprietary APIs, which make developers locked inside a specific platform and not able to easily port their applications among different platforms. So, vendor lock-in problem appeared. One solution to this problem is to use generic APIs with specific adapters. However, any update in a PaaS specific-API makes its corresponding adapter is unusable which causes, what we call, API synchronization problem. Therefore, STAGER (SemanTic-based GenERation of Generic-API Adapters) framework is proposed. STAGER framework provides a semi-automatic adapter generation process, which generates specific adapters of generic APIs for PaaS services (e.g., blob storage and datastore services) for target PaaS platforms. The adapter generation process is based on semantic annotations of the generic APIs and their corresponding PaaS specific-APIs. In order to evaluate STAGER framework, two generic APIs for blob storage and NoSQL datastore services have been proposed. STAGER framework is used to generate the adapters of these generic APIs for two PaaS platforms: Google App Engine (GAE) and Windows Azure. Although there is some overhead for semantically annotating the PaaS APIs, the evaluation results prove the feasibility of STAGER framework and promote the usage of the generated adapters for implementing portable cloud applications.

Multi Criteria Decision-Making (MCDM) methods mainly help finding the most desirable alternatives from a set of available alternatives versus the selected criteria. Fuzzy Decision Maps (FDM) method has been proposed in 2006 for handling MCDM problems with dependency and feedback to overcome the complexity drawback of Analytic Network Process (ANP). However, the structure of FDM method was designed to deal with single level only. Therefore, it calculates only the numerical priorities among criteria. But in complex real world MCDM problems, many levels of criteria / sub-criteria should be manipulated between goals and alternatives. This paper presents a generalized FDM method that is capable of handling the case of multilevel criteria/sub criteria and alternatives. The generalized FDM method is called Multi Level Fuzzy Decision Map (ML-FDM). An agricultural case study for selecting wheat variety to cultivate in Egypt is used to demonstrate how the proposed ML-FDM method can be applied in a real world example.

Fuzzy Decision Map (FDM) method was proposed in 2006 to solve multicriteria decision making problems (MCDM) having dependence and feedback among criteria. FDM provides a simpler approach to solve such problems compared with the method of Analytical Network Process (ANP) developed in 1996. ANP is a general form of the Analytic Hierarchy Process (AHP). On the other hand, FDM is only employed to derive evaluation criteria. It can't be used for ranking alternatives as usually required in many real world MCDM problems. The aim of this work is to enhance the FDM structure to be able to make a proper decision for complex decision making problem by selecting best alternative. The enhanced FDM method should take into consideration the alternative level. A case study was carried out to demonstrate the proposed model.