Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization Method Article Swipe
Kuanishbay Sadatdiynov
,
Laizhong Cui
,
Joshua Zhexue Huang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1824328/v1
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1824328/v1
The rapid development of IoT-based services has resulted in an exponen- tial increase in the number of connected smart mobile devices (SMDs). Processing the massive data generated by the large number of SMDs is becoming a big problem for mobile devices, servers, and wireless com- munication channels. A Multi-access Edge Computing (MEC) paradigm partially mitigates this problem by deploying edge server nodes at the edge of wireless networks nearby SMDs, but the challenge still remains due to the limited computation capacity of MEC servers and the band- width of wireless channels. In addition, the dependency of tasks generated by applications on SMDs increases the complexity of the problem. In this paper, we propose a constrained multiobjective computation offload- ing optimization solution to resolve the problem of task dependency under limited resources. This solution improves the Quality of Ser- vice (QoS) through minimizing the latency, energy consumption, and rate of task failure caused by limited resources. We propose a two- staged hybrid computation offloading optimization method to solve the problem. In the first stage, the computation offloading decisions are made based on the preferences of tasks. Then, in the second stage, global optimal solutions are found using the modified Non-Dominated Sorting Genetic Algorithm (NSGA-III). The overall efficiency of the proposed method is increased owing to the preference-based algorithm reinforcing the NSGA-III algorithm by generating a better initial population. The results of extensive experiments show that the efficiency of the proposed method is significantly better than the existing methods.
Related Topics
Concepts
Computer science
Mobile edge computing
Server
Optimization problem
Distributed computing
Computation offloading
Wireless
Genetic algorithm
Edge computing
Population
Mobile device
Enhanced Data Rates for GSM Evolution
Computer network
Algorithm
Artificial intelligence
Telecommunications
Operating system
Demography
Machine learning
Sociology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-1824328/v1
- https://www.researchsquare.com/article/rs-1824328/latest.pdf
- OA Status
- green
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285491723
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4285491723Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-1824328/v1Digital Object Identifier
- Title
-
Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization MethodWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-15Full publication date if available
- Authors
-
Kuanishbay Sadatdiynov, Laizhong Cui, Joshua Zhexue HuangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-1824328/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-1824328/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-1824328/latest.pdfDirect OA link when available
- Concepts
-
Computer science, Mobile edge computing, Server, Optimization problem, Distributed computing, Computation offloading, Wireless, Genetic algorithm, Edge computing, Population, Mobile device, Enhanced Data Rates for GSM Evolution, Computer network, Algorithm, Artificial intelligence, Telecommunications, Operating system, Demography, Machine learning, SociologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
42Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3132679163, https://openalex.org/W3030475315, https://openalex.org/W3106445841, https://openalex.org/W3042924535, https://openalex.org/W2905357302, https://openalex.org/W2909977353, https://openalex.org/W3082230639, https://openalex.org/W3185944238, https://openalex.org/W2792526074, https://openalex.org/W2907935659, https://openalex.org/W2997234356, https://openalex.org/W2917153503, https://openalex.org/W2904534804, https://openalex.org/W2889735101, https://openalex.org/W3037781631, https://openalex.org/W3159162481, https://openalex.org/W4288400169, https://openalex.org/W3033881824, https://openalex.org/W4214890174, https://openalex.org/W2343896184, https://openalex.org/W2970120675, https://openalex.org/W2970982242, https://openalex.org/W3176011594, https://openalex.org/W4221103247, https://openalex.org/W2800305275, https://openalex.org/W2082081352, https://openalex.org/W2974654731, https://openalex.org/W2126105956, https://openalex.org/W2022485595, https://openalex.org/W2911353037, https://openalex.org/W2400861403, https://openalex.org/W221263235, https://openalex.org/W2024008934, https://openalex.org/W2739742920, https://openalex.org/W2085507535, https://openalex.org/W2674963269, https://openalex.org/W3008388905, https://openalex.org/W3036516176, https://openalex.org/W4221077449, https://openalex.org/W4292544546, https://openalex.org/W2909473479, https://openalex.org/W2594560857 |
| referenced_works_count | 42 |
| abstract_inverted_index.A | 48 |
| abstract_inverted_index.a | 36, 114, 158, 224 |
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| abstract_inverted_index.challenge | 73 |
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