Incentive-Vacation Queueing for Extreme Edge Computing Systems

TL;DR: This work evaluates an orchestrator-based extreme edge system, that oversees user-owned worker devices, and it provides resources in exchange for an incentive payment, and proposes the Incentive-Vacation Queueing (IVQ) model, which provides insight into the impact of introducing incentives on the workers' performance.

Abstract: The demand for cloud services is expected to exceed the capacity of the centralized cloud. This rise compelled service providers to decentralize the cloud by physically pushing service provision to the proximity of the end-users, which led to the synthesis of solutions such as Fog and Edge computing. Edge Computing seeks to deploy services in the last mile to the end-user, however there is still opportunity on the edge beyond the last mile: the user's own devices. Extreme Edge Computing (EEC) is an edge sub-paradigm that seeks to tap into the idle computational power on non-enterprise user-owned devices. In this work, we navigate some of the challenges posed by EEC that constrain the usage of resources on user-owned devices. We evaluate an orchestrator-based extreme edge system, that oversees user-owned worker devices, and it provides resources in exchange for an incentive payment. We propose the Incentive-Vacation Queueing (IVQ) model to investigate the performance of user-owned worker devices under a vacation policy that is influenced by incentives. We derive closed-form expressions for the system performance that capture the epistemic uncertainty stemming from unexpected user behavior, to show the impact of each parameter in the system performance, and to optimize it. The IVQ model provides insight into the impact of introducing incentives on the workers' performance.