An adaptive trust based service quality monitoring mechanism for cloud computing

Cloud computing is the newest paradigm in distributed computing that delivers computing resources over the Internet as services. Due to the attractiveness of cloud computing, the market is currently flooded with many service providers. This has necessitated the customers to identify the right one meeting their requirements in terms of service quality. The existing monitoring of service quality has been limited only to quantification in cloud computing. On the other hand, the continuous improvement and distribution of service quality scores have been implemented in other distributed computing paradigms but not specifically for cloud computing. This research investigates the methods and proposes mechanisms for quantifying and ranking the service quality of service providers. The solution proposed in this thesis consists of three mechanisms, namely service quality modeling mechanism, adaptive trust computing mechanism and trust distribution mechanism for cloud computing. The Design Research Methodology (DRM) has been modified by adding phases, means and methods, and probable outcomes. This modified DRM is used throughout this study. The mechanisms were developed and tested gradually until the expected outcome has been achieved. A comprehensive set of experiments were carried out in a simulated environment to validate their effectiveness. The evaluation has been carried out by comparing their performance against the combined trust model and QoS trust model for cloud computing along with the adapted fuzzy theory based trust computing mechanism and super-agent based trust distribution mechanism, which were developed for other distributed systems. The results show that the mechanisms are faster and more stable than the existing solutions in terms of reaching the final trust scores on all three parameters tested. The results presented in this thesis are significant in terms of making cloud computing acceptable to users in verifying the performance of the service providers before making the selection

A comprehensive survey on quality of service implementations in cloud computing

Quality of service plays is an important factor in distributed computing.Cloud computing has been the paradigm in distributed computing.Under cloud computing, computing resources are hosted in the internet and delivered to customers as services.Prior to the commencement of services, the customers and cloud providers negotiate and enter into an agreement named service level agreement.The services level agreements clarify the roles, set charges and expectations and provide mechanisms for resolving service problems within a specified and agreed upon time period. Service level agreements also cover performance, reliability conditions in terms of quality of service guarantees. In this paper, the authors present a comprehensive survey on quality of service implementations in cloud computing with respect to their implementation details, strengths and weaknesses

A SEMANTIC BASED POLICY MANAGEMENT FRAMEWORK FOR CLOUD COMPUTING ENVIRONMENTS

Cloud computing paradigm has gained tremendous momentum and generated intensive interest. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this dissertation, we mainly focus on issues related to policy management and access control in the cloud. Currently, users have to use diverse access control mechanisms to protect their data when stored on the cloud service providers (CSPs). Access control policies may be specified in different policy languages and heterogeneity of access policies pose significant problems.An ideal policy management system should be able to work with all data regardless of where they are stored. Semantic Web technologies when used for policy management, can help address the crucial issues of interoperability of heterogeneous CSPs. In this dissertation, we propose a semantic based policy management framework for cloud computing environments which consists of two main components, namely policy management and specification component and policy evolution component. In the policy management and specification component, we first introduce policy management as a service (PMaaS), a cloud based policy management framework that give cloud users a unified control point for specifying authorization policies, regardless of where the data is stored. Then, we present semantic based policy management framework which enables users to specify access control policies using semantic web technologies and helps address heterogeneity issues of cloud computing environments. We also model temporal constraints and restrictions in GTRBAC using OWL and show how ontologies can be used to specify temporal constraints. We present a proof of concept implementation of the proposed framework and provide some performance evaluation. In the policy evolution component, we propose to use role mining techniques to deal with policy evolution issues and present StateMiner, a heuristic algorithm to find an RBAC state as close as possible to both the deployed RBAC state and the optimal state. We also implement the proposed algorithm and perform some experiments to demonstrate its effectiveness

Cross-layer SLA selection for Cloud services

International audienceCloud computing is a paradigm for enabling remote, on-demand access to a set of configurable computing resources as a service. The pay-per-use model enables service providers to offer their services to customers in different Quality-of-Service (QoS) levels. These QoS parameters are used to compose some bipartisan Service Level Agreement (SLA) between a service provider and a service consumer. A main challenge for a service provider is to manage SLAs for its service consumers, i.e. automatically determine the appropri- ate resources required from the lower layer in order to respect the QoS requirements of his consumers. This paper proposes an optimization framework driven by consumer preferences to address the SLA dependencies problem across the different cloud layers as well as the need of flexibility and dynamicity required by the domain of Cloud computing. Our approach aims to select the optimal vertical business process designed by cross-layer cloud services, enforcing SLA dependen- cies between layers. Based on Constraint Programming (CP), our approach can take into account dynamic QoS parameters in a flexible manner to compose the best vertical business process. Experimental results demonstrate the flexibility and effectiveness of our approach