The successful development of fifth generation systems require enormous computational capability and flexibility necessitating the ability to achieve operational responses in hard real-time through optimal resource utilization. This entails dynamically balancing the computational load among all the processing nodes in the system. We propose a graph-theoretic, receiver-initiated, distributed protocol for dynamic load balancing protocol in large-scale hyper-cube ensembles. Using attributed hypergraphs as the primary data structure for constraint modeling and dynamic optimization, we consider systems running precedence-constrained heterogeneous tasks. Fault Tolerance is ensured by incorporating an integrity check for the decision nodes and their subsequent reelection if needed. Simulation studies are used to evaluate the performance of the algorithm.
