Multitiered Worker-Oriented Resource Allocation at the Extreme Edge

Abstract

Fostering Edge Computing (EC) by recycling prolific yet underutilized computational resources of the Internet of Things (IoT) devices, also referred to as Extreme Edge Devices (EEDs), has gained significant momentum lately. Fair resource allocation is a primary concern in such computing paradigms. However, fairness is typically considered from the requester's perspective, whereas fairness for workers (i.e., EEDs) is mostly overlooked. In this context, we propose the Multitiered Worker-Oriented Resource Allocation (MWORA) scheme. In MWORA, the resource allocation problem is formulated as an Integer Linear Program (ILP). MWORA aims to maximize service capacity and minimize the task response delay while enabling fair resource allocation that maintains a specific satisfactory profit for workers. Such a satisfactory level is maintained to prevent the workers from leaving the system and ensure their recurrent subscription to the service. This is done while abiding by the deadline demanded by each requester and without exceeding a certain budget. MWORA also accounts for the fact that EEDs are user-owned devices and are thus subject to a dynamic user access behavior, which can affect the level of computational resources that workers are willing to offer. In particular, MWORA enables multitiered computational resources to be granted by each worker depending on the price of the allocated task. Extensive simulations have shown that MWORA outperforms other baseline resource allocation schemes regarding average response delay, service capacity, worker satisfaction ratio, and fairness.