Optimizing Distributed Resource Allocation using Epistemic Game Theory: A Model-driven Engineering Approach

Distributed systems modelling often involves a set of heterogeneous models where each model specifies a set of local constraints capturing a specific view of the system. In real life, distributed systems are often loosely connected and interdependencies are not defined into their software models. This limits the scope of optimization of distributed resources. In this paper, we merge heterogeneous models of distributed systems and articulate distributed resource constraints via inter-metamodel constraints. We apply model-driven engineering and use model transformation rules to construct an epistemic game theory model for the purpose of optimizing distributed resource allocation. Since the application of transformation rules normally do not guarantee the satisfaction of constraints when applied on a model, it requires a conformance checking which is an expensive operation. To overcome this problem, we introduce the concept of compliant rule for efficient model transformation.