Due to high complexity and heterogeneity of cloud environment, and this had interchangeably been imposed by a plethora of socially co-engineered cloud application architectures, designers are yet facing difficulties in choosing from approaches to model transformation between multiple domains solutions. In fact most of cloud based application development became hectic due to overwhelming number of layers which interrelate to significant application problem area. Such newly growing challenges had demanded to choose more cost effective ways of how to elicit efficient solutions that can articulate several types of requirements. Focusing on high level conceptual views; this paper introduces a new dynamic domain driven design method, which serves self-optimizing of socially interacted organizational patterns in cloud based environment. Such method helps to describe user aspects of tackled domains and problems to be solved rather than being concerned about choosing which program model should be used to satisfy features, goals and objectives for such software application
The promise of robust software that can self-manage significant aspects of its operation, including the ability to self-configure, self-heal, self-optimise and self-protect through having the requisite functionality to respond and adapt to changes in its operational environment is both seductive and compelling. There are a growing number of examples of partial implementations appearing in the literature and continued development across a number of areas can be expected in the future.One of the less travelled areas of research concerns the problem of developing an accurate and current model of the environment in which such adaptive systems will operate. It would seem a compelling argument that holding a current model of both the environment and the current capability of the system allowing the system to "know itself" are desirable additions to any adaptive system. As such they have a view of the complex space within which they can adapt and that without these properties the system could only be considered as purely reactive.Here, the use of Learning Classifier Systems and genetic algorithms to provide the modelling element required of effective adaptive software systems is presented and evaluated. The work uses the virtual world platform of "Second Life" to represent an appropriate experimental environment. One outcome of this work is the restatement of some classical cybernetic principles to reflect the need for constant evolution
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