Exploring computation offloading in IoT systems. Issue 107 (July 2022)
- Record Type:
- Journal Article
- Title:
- Exploring computation offloading in IoT systems. Issue 107 (July 2022)
- Main Title:
- Exploring computation offloading in IoT systems
- Authors:
- Shahhosseini, Sina
Anzanpour, Arman
Azimi, Iman
Labbaf, Sina
Seo, DongJoo
Lim, Sung-Soo
Liljeberg, Pasi
Dutt, Nikil
Rahmani, Amir M. - Abstract:
- 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. Highlights: Explore the impact of computation offloading on response timeAbstract: 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. Highlights: 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. … (more)
- Is Part Of:
- Information systems. Issue 107(2022)
- Journal:
- Information systems
- Issue:
- Issue 107(2022)
- Issue Display:
- Volume 107, Issue 107 (2022)
- Year:
- 2022
- Volume:
- 107
- Issue:
- 107
- Issue Sort Value:
- 2022-0107-0107-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Internet of Things -- Fog computing -- Computation offloading
Database management -- Periodicals
Electronic data processing -- Periodicals
Bases de données -- Gestion -- Périodiques
Informatique -- Périodiques
Database management
Electronic data processing
Periodicals
005.7 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03064379 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.is.2021.101860 ↗
- Languages:
- English
- ISSNs:
- 0306-4379
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.367300
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British Library HMNTS - ELD Digital store - Ingest File:
- 21279.xml