A Model Driven Framework for Efficient Bandwidth Allocation in Fog Computing Using Priority Algorithm

Architecture of cloud computing encompasses numerous Internet of Things devices. Due to the recent proliferation of IoT devices, cloud itself is unable to provide the desired information to the end users in optimum time. Moreover, the data transmission between source and destination suffers a bottleneck due to the limited and unequal distribution of bandwidth among various interfaces. This makes the architecture of cloud / fog computing a complex one. MDA (Model Driven Architecture) is marked with abstraction and modularity which in turn reduces the complexity of development. Hence, the complex domain of fog computing and its inherent problem of bandwidth also requires exploration in the context of MDA. Consequently, this article proposes an MD-BA (Model Driven Bandwidth Allocation) framework using a priority algorithm. Primarily, a Meta Model is proposed that allows modeling and visualization of complex systems which may be further automated. As a tool support, a Sirius based graphical modeling tool/workbench has been developed. The proposed framework, along with its tool support, can model a flexible design. It reduces complexity for allocating bandwidth dynamically between all fog peers. The framework is distributable via an eclipse-based plugin. A Model to Text (M2T) transformation code that transforms the developed model into Java Specific code is written as a part of this article. The validity of the proposed framework is demonstrated with a real-world case study. Experimental results prove that the proposed framework can be used to accommodate high priority events and to ensure quick real time response from fog peers that ultimately enhance client's quality of experience.