A Research Perspective on Data Management Techniques for Federated Cloud Environment

Cloud computing has given a large scope of improvement in processing, storage and retrieval of data that is generated in huge amount from devices and users. Heterogenous devices and users generates the multidisciplinary data that needs to take care for easy and efficient storage and fast retrieval by maintaining quality and service level agreements. By just storing the data in cloud will not full fill the user requirements, the data management techniques has to be applied so that data adaptiveness and proactiveness characteristics are upheld. To manage the effectiveness of entire eco system a middleware must be there in between users and cloud service providers. Middleware has set of events and trigger based policies that will act on generated data to intermediate users and cloud service providers. For cloud service providers to deliver an efficient utilization of resources is one of the major issues and has scope of improvement in the federation of cloud service providers to fulfill user’s dynamic demands. Along with providing adaptiveness of data management in the middleware layer is challenging. In this paper, the policies of middleware for adaptive data management have been reviewed extensively. The main objectives of middleware are also discussed to accomplish high throughput of cloud service providers by means of federation and qualitative data management by means of adaptiveness and proactiveness. The cloud federation techniques have been studied thoroughly along with the pros and cons of it. Also, the strategies to do management of data has been exponentially explored

Service Quality Assessment for Cloud-based Distributed Data Services

The issue of less-than-100% reliability and trust-worthiness of third-party controlled cloud components (e.g., IaaS and SaaS components from different vendors) may lead to laxity in the QoS guarantees offered by a service-support system S to various applications. An example of S is a replicated data service to handle customer queries with fault-tolerance and performance goals. QoS laxity (i.e., SLA violations) may be inadvertent: say, due to the inability of system designers to model the impact of sub-system behaviors onto a deliverable QoS. Sometimes, QoS laxity may even be intentional: say, to reap revenue-oriented benefits by cheating on resource allocations and/or excessive statistical-sharing of system resources (e.g., VM cycles, number of servers). Our goal is to assess how well the internal mechanisms of S are geared to offer a required level of service to the applications. We use computational models of S to determine the optimal feasible resource schedules and verify how close is the actual system behavior to a model-computed \u27gold-standard\u27. Our QoS assessment methods allow comparing different service vendors (possibly with different business policies) in terms of canonical properties: such as elasticity, linearity, isolation, and fairness (analogical to a comparative rating of restaurants). Case studies of cloud-based distributed applications are described to illustrate our QoS assessment methods. Specific systems studied in the thesis are: i) replicated data services where the servers may be hosted on multiple data-centers for fault-tolerance and performance reasons; and ii) content delivery networks to geographically distributed clients where the content data caches may reside on different data-centers. The methods studied in the thesis are useful in various contexts of QoS management and self-configurations in large-scale cloud-based distributed systems that are inherently complex due to size, diversity, and environment dynamicity

Optimal Framework for Level Based Access Control for VM Auditing on Cloud

The growth in the cloud computing have motivated and enable lot of application developer to deploy the applications on cloud. The major challenge of hosting on cloud is the service provider or the application provider must comply to a good number of rules. These compliance reports are time to time validated and checked by external auditors. The auditing process for the cloud services are critical and the access controls must be enabled. Due to the higher complexity and less flexibility of the virtual machines, most of the cases this access control mechanism is compromised. This work proposes four algorithms to identify and enhance the LBAC mechanism for cloud services with access updates based on time variant characteristics analysis and predictive analysis with selective cryptographic methods. The proposed model produces significantly improved results to overcome three major issues in the cloud service management as selective LBAC, static privileges and open access control for the auditors.  &nbsp

Systematic survey on evolution of cloud architectures

Cloud architectures are becoming an active area of research. The quality and durability of a software system are defined by its architecture. The architecture approaches that are used to build cloud-based systems are not available in a blended fashion to achieve an effective universal architecture solution. The paper aims to contribute to the systematic literature review (SLR) to assist researchers who are striving to contribute in this area. The main objective of this review is to systematically identify and analyse the recently published research topics related to software architecture for cloud with regard to research activity, used tools and techniques, proposed approaches, domains. The applied method is SLR based on four selected electronic databases proposed by (Kitchenham and Charters, 2007). Out of 400 classified publications, we regard 121 as relevant for our research domain. We outline taxonomy of their topics and domains, provide lists of used methods and proposed approaches. At present, there is little research coverage on software architectures for cloud, while other disciplines have become more active. The future work is to develop a secure architecture to achieve quality of service and service level agreements