DECO: Joint Computation, Caching and Forwarding in Data-Centric Computing Networks

The emergence of IoT devices and the predicted increase in the number of data-driven and delay-sensitive applications highlight the importance of dispersed computing platforms (e.g. edge computing and fog computing) that can intelligently manage in-network computation and data placement. In this paper, we propose the DECO (Data-cEntric Computation) framework for joint computation, caching, and request forwarding in data-centric computing networks. DECO utilizes a virtual control plane which operates on the demand rates for computation and data, and an actual plane which handles computation requests, data requests, data objects and computation results in the physical network. We present a throughput optimal policy within the virtual plane, and use it as a basis for adaptive and distributed computation, caching, and request forwarding in the actual plane. We demonstrate the superior performance of the DECO policy in terms of request satisfaction delay as compared with several baseline policies, through extensive numerical simulations over multiple network topologies.