A1 Journal article – refereed

Exploring computation offloading in IoT systems




List of Authors: Shahhosseini Sina, Anzanpour Arman, Azimi Iman, Labbaf Sina, Seo DongJoo, Lim Sung-Soo, Liljeberg Pasi, Dutt Nikil, Rahmani Amir M.

Publisher: Elsevier

Publication year: 2021

Journal: Information Systems

Journal name in source: Information Systems

ISSN: 0306-4379

eISSN: 1873-6076

DOI: http://dx.doi.org/10.1016/j.is.2021.101860

URL: https://doi.org/10.1016/j.is.2021.101860


Abstract

Internet of Things (IoT) paradigm raises challenges for devising efficient strategies that offload applications to the fog or the cloud layer while ensuring the optimal response time for a service. Traditional computation offloading policies assume the response time is only dominated by the execution time. However, the response time is a function of many factors including contextual parameters and application characteristics that can change over time. For the computation offloading problem, the majority of existing literature presents efficient solutions considering a limited number of parameters (e.g., computation capacity and network bandwidth) neglecting the effect of the application characteristics and dataflow configuration. In this paper, we explore the impact of the computation offloading on total application response time in three-layer IoT systems considering more realistic parameters, e.g., application characteristics, system complexity, communication cost, and dataflow configuration. This paper also highlights the impact of a new application characteristic parameter defined as Output–Input Data Generation (OIDG) ratio and dataflow configuration on the system behavior. In addition, we present a proof-of-concept end-to-end dynamic computation offloading technique, implemented in a real hardware setup, that observes the aforementioned parameters to perform real-time decision-making.


Last updated on 2021-13-09 at 15:24