A Decomposition-based Architecture for Distributed Cyber-Foraging of Multiple Edge Functions

Edge computing is an emerging paradigm whose goal is to boost with cloud resources available at the edge the computational capability of otherwise weak devices. This paradigm is mostly attractive to reduce user perceived latency. A central mechanism in edge computing is cyber-foraging, i.e., the search and delegation to capable edge cloud processes of tasks too complex, time consuming or resource intensive to be running on user devices or low-latency demanding to be running remotely, as a form of edge function. An edge function is any network or device-specific process that may be run on an edge process instead. Despite the recent interest for this technology from industry and academia, cyber-foraging techniques and protocols have yet to be standardized. In this paper, we leverage decomposition theory to propose an architecture providing insights in the design and implementation of protocols for cyber-foraging of multiple edge functions. In contrast with several existing solutions, we argue that the (distributed) cyber-foraging orchestration should be policy-based and not an ad-hoc solution, i.e., either a pure edge cloud burden or a device decision. To this end, via simulations, we show how our approach can be used by edge computing providers and application programmers to compare and evaluate different alternative cyber-foraging solutions. Our decomposition-based approach has general applicability to other network utility maximization problems, even outside the edge computing domain.