Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: A semi-greedy approach
With the rapid advancement of Internet of Things (IoT) devices, a variety of IoT applications that require a real-time response and low latency have emerged. Fog computing has become a viable platform for processing emerging IoT applications. However, fog computing devices tend to be highly distribu...
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| Vydané v: | Journal of network and computer applications Ročník 201; s. 103333 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.05.2022
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| ISSN: | 1084-8045, 1095-8592 |
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| Abstract | With the rapid advancement of Internet of Things (IoT) devices, a variety of IoT applications that require a real-time response and low latency have emerged. Fog computing has become a viable platform for processing emerging IoT applications. However, fog computing devices tend to be highly distributed, dynamic, and resource-constrained, so deploying fog computing resources effectively for executing heterogeneous and delay-sensitive IoT tasks is a fundamental challenge. In this paper, we mathematically formulate the task scheduling problem to minimize the total energy consumption of fog nodes (FNs) while meeting the quality of service (QoS) requirements of IoT tasks. We also consider the minimization of the deadline violation time in our model. Next, we propose two semi-greedy based algorithms, namely priority-aware semi-greedy (PSG) and PSG with multistart procedure (PSG-M), to efficiently map IoT tasks to FNs. We evaluate the performance of the proposed task scheduling approaches with respect to the percentage of IoT tasks that meet their deadline requirement, total energy consumption, total deadline violation time, and the system’s makespan. Compared with existing algorithms, the experiment results confirm that the proposed algorithms improve the percentage of tasks meeting their deadline requirement up to 1.35x and decrease the total deadline violation time up to 97.6% compared to the second-best results, respectively, while the energy consumption of fog resources and makespan of the system are optimized. |
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| AbstractList | With the rapid advancement of Internet of Things (IoT) devices, a variety of IoT applications that require a real-time response and low latency have emerged. Fog computing has become a viable platform for processing emerging IoT applications. However, fog computing devices tend to be highly distributed, dynamic, and resource-constrained, so deploying fog computing resources effectively for executing heterogeneous and delay-sensitive IoT tasks is a fundamental challenge. In this paper, we mathematically formulate the task scheduling problem to minimize the total energy consumption of fog nodes (FNs) while meeting the quality of service (QoS) requirements of IoT tasks. We also consider the minimization of the deadline violation time in our model. Next, we propose two semi-greedy based algorithms, namely priority-aware semi-greedy (PSG) and PSG with multistart procedure (PSG-M), to efficiently map IoT tasks to FNs. We evaluate the performance of the proposed task scheduling approaches with respect to the percentage of IoT tasks that meet their deadline requirement, total energy consumption, total deadline violation time, and the system’s makespan. Compared with existing algorithms, the experiment results confirm that the proposed algorithms improve the percentage of tasks meeting their deadline requirement up to 1.35x and decrease the total deadline violation time up to 97.6% compared to the second-best results, respectively, while the energy consumption of fog resources and makespan of the system are optimized. |
| ArticleNumber | 103333 |
| Author | Buyya, Rajkumar Shojafar, Mohammad Azizi, Sadoon Abawajy, Jemal |
| Author_xml | – sequence: 1 givenname: Sadoon orcidid: 0000-0002-5788-0438 surname: Azizi fullname: Azizi, Sadoon email: s.azizi@uok.ac.ir organization: Department of Computer Engineering and IT, University of Kurdistan, Sanandaj, Iran – sequence: 2 givenname: Mohammad orcidid: 0000-0003-3284-5086 surname: Shojafar fullname: Shojafar, Mohammad email: m.shojafar@surrey.ac.uk organization: 5GIC & 6GIC, Institute for Communication Systems (ICS), University of Surrey, Guildford, GU27XH, United Kingdom – sequence: 3 givenname: Jemal surname: Abawajy fullname: Abawajy, Jemal email: jemal.abawajy@deakin.edu.au organization: School of Information Technology, Deakin University, Geelong, VIC 3220, Australia – sequence: 4 givenname: Rajkumar surname: Buyya fullname: Buyya, Rajkumar email: rbuyya@unimelb.edu.au organization: CLOUDS lab, School of Computing and Information Systems, University of Melbourne, Melbourne, VIC 3010, Australia |
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| Keywords | Fog computing Cloud computing Energy consumption Deadline-aware Task scheduling Internet of Things Semi-greedy algorithm |
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14 Faramarzi (10.1016/j.jnca.2022.103333_b19) 2020; 152 Omer (10.1016/j.jnca.2022.103333_b48) 2021; 115 Yang (10.1016/j.jnca.2022.103333_b61) 2020 Islam (10.1016/j.jnca.2022.103333_b34) 2021 Hoseiny (10.1016/j.jnca.2022.103333_b33) 2021; 21 Heidari (10.1016/j.jnca.2022.103333_b30) 2019; 97 |
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