Quantifying Computational Reliability of Task Assignment in Extreme Edge Computing

Abstract

This paper presents a reliability analysis framework for distributed computing in extreme edge computing (XEC) with limited information availability. XEC pushes computation to the outermost boundaries of networks by leveraging consumer-owned devices, known as Extreme Edge Devices (XEDs). Unlike traditional distributed systems with defined computational resource states, XEC operates under uncertainty due to consumer device usage patterns, varying computational capacities, and local scheduling algorithms. In this work, we address discrete task assignment particularly. The framework analyzes scenarios for computational reliability assessments with minimal knowledge of XED capabilities and service requirements. The framework adapts to different levels of available information, from operational limits to historical performance data, providing refined reliability estimates. The aim of this work is to provide generalized reliability models for distributed computing in XEC that allow decision-makers (e.g. service orchestrators) to make informed decisions about task allocation, service placement, and resource allocation under uncertainty in XEC. Simulations and experimental analysis demonstrate the framework’s effectiveness in estimating reliability under various system conditions.