Exploring computation offloading in IoT systems

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...

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Bibliographic Details
Published in:Information systems (Oxford) 2022-07, Vol.107, p.101860, Article 101860
Main Authors: Shahhosseini, Sina, Anzanpour, Arman, Azimi, Iman, Labbaf, Sina, Seo, DongJoo, Lim, Sung-Soo, Liljeberg, Pasi, Dutt, Nikil, Rahmani, Amir M.
Format: Article
Language:English
Subjects:
Communications systems
Computation offloading
Configurations
Decision making
Fog computing
Information systems
Internet of Things
Parameters
Response time
Response time (computers)
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Summary: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. •Explore the impact of computation offloading on response time in IoT systems.•Investigate the impact of application characteristic and dataflow on system behavior.•Examine a proof-of-concept end-to-end dynamic computation offloading solution.
ISSN:0306-4379
1873-6076
DOI:10.1016/j.is.2021.101860