Adaptive Middleware to Analyze and Confirm Data Centric Parameters for Data Aggregation in Federated Cloud Environment

In the last decade rapid data evolution has contributed to tremendous data movement. The efficient data movement from origin to cloud storage and vice versa leads to the significant performance of application. A software layer situated between user and cloud storage called middleware plays major role in handling data to full fill user goals and requirements. In this paper, proposed a development of middleware frameworks from generic to context aware framework. Explicit importance is given to the adaptation feature of the middleware. A preliminary background is presented to list out importance and details of adaptability of the middleware and curious differentiation in static and self-adaptive adaptation features of the middleware. The literature started with the description of many generic middleware which can be used for building applications in variety of domains and further the limitations imposed are exposed. The issues like multidisciplinary data, vendor lock-in, disparity of service and interoperability related to federated cloud services serving to the fast-developing technology are highlighted. Along with that the use of context aware data management techniques for efficient handling of federated cloud system are defined. An extensive and comprehensive analysis of context-aware middleware is presented. For skilful data management processes need of context aware application with self-adaptation capability is presented especially in response to dynamic situations in federated cloud environment. At the end three techniques to design and develop context-aware middleware are presented. Alongside, four different perspectives of realizing adaptive middleware are also detailed. The presented work concludes with the highlighted need of context aware middleware framework to enhance the performance of federated cloud system.