Distributed Packet Forwarding and Caching Based on Stochastic Network Utility Maximization - 2018


Cache-enabled network architecture has nice potential for enhancing the potency of content distribution in addition to reducing the network congestion. This, in turn, has known as for joint optimization of traffic engineering and caching ways while considering each network congestion and content demands. In this Project, we present a distributed framework for joint request/data forwarding and dynamic cache placement in cache-enabled networks. Specifically, to retrieve the information concerning content demands and network congestion over the network, we have a tendency to establish a twin queue system for both requests and data, and outline a dynamic mapping between the 2 queues with the assistance of dummy data such that the nodes can determine packet forwarding and caching methods based mostly solely on local info. Because the native objective function associated with Lyapunov optimization is time-varying due to the stochastic evolution of request/knowledge queues, we develop an occasional-complexity distributed forwarding and caching algorithm via stochastic network utility maximization. We have a tendency to also prove the proposed algorithm achieves queue stability, and derive its region stability property for time-varying local optimization to demonstrate the convergence behavior. The simulation results verify queue stability and shows the proposed algorithm outperforms the prevailing ones.

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