Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing
To satisfy the delay constraint, the computation tasks can be offloaded to some computing servers, referred to as offloading destinations. Different to most of existing works which usually consider only a single type of offloading destinations, in this paper, we study the hybrid computation offloadi...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8023966/ |
| _version_ | 1818876816408969216 |
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| author | Xianling Meng Wei Wang Zhaoyang Zhang |
| author_facet | Xianling Meng Wei Wang Zhaoyang Zhang |
| author_sort | Xianling Meng |
| collection | DOAJ |
| description | To satisfy the delay constraint, the computation tasks can be offloaded to some computing servers, referred to as offloading destinations. Different to most of existing works which usually consider only a single type of offloading destinations, in this paper, we study the hybrid computation offloading problem considering diverse computation and communication capabilities of two types of offloading destinations, i.e., cloud computing servers and fog computing servers. The aim is to minimize the total energy consumption for both communication and computation while completing the computation tasks within a given delay constraint. It is quite challenging because the delay cannot be easily formulated as an explicit expression but depends on the embedded communication-computation scheduling problem for the computation offloading to different destinations. To solve the computation offloading problem, we first define a new concept named computation energy efficiency and divide the problem into four subproblems according to the computation energy efficiency of different types of computation offloading and the maximum tolerable delay. For each subproblem, we give a closed-form computation offloading solution with the analysis of communicationcomputation scheduling under the delay constraint. The numerical results show that the proposed hybrid computation offloading solution achieves lower energy consumption than the conventional single-type computation offloading under the delay constraint. |
| first_indexed | 2024-12-19T13:48:24Z |
| format | Article |
| id | doaj.art-2aba619ca5e0461da0309626bb558ea7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:48:24Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2aba619ca5e0461da0309626bb558ea72022-12-21T20:18:49ZengIEEEIEEE Access2169-35362017-01-015213552136710.1109/ACCESS.2017.27481408023966Delay-Constrained Hybrid Computation Offloading With Cloud and Fog ComputingXianling Meng0Wei Wang1https://orcid.org/0000-0003-2153-9075Zhaoyang Zhang2College of Information Science and Electronic Engineering, Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Zhejiang University, Hangzhou, ChinaCollege of Information Science and Electronic Engineering, Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Zhejiang University, Hangzhou, ChinaCollege of Information Science and Electronic Engineering, Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Zhejiang University, Hangzhou, ChinaTo satisfy the delay constraint, the computation tasks can be offloaded to some computing servers, referred to as offloading destinations. Different to most of existing works which usually consider only a single type of offloading destinations, in this paper, we study the hybrid computation offloading problem considering diverse computation and communication capabilities of two types of offloading destinations, i.e., cloud computing servers and fog computing servers. The aim is to minimize the total energy consumption for both communication and computation while completing the computation tasks within a given delay constraint. It is quite challenging because the delay cannot be easily formulated as an explicit expression but depends on the embedded communication-computation scheduling problem for the computation offloading to different destinations. To solve the computation offloading problem, we first define a new concept named computation energy efficiency and divide the problem into four subproblems according to the computation energy efficiency of different types of computation offloading and the maximum tolerable delay. For each subproblem, we give a closed-form computation offloading solution with the analysis of communicationcomputation scheduling under the delay constraint. The numerical results show that the proposed hybrid computation offloading solution achieves lower energy consumption than the conventional single-type computation offloading under the delay constraint.https://ieeexplore.ieee.org/document/8023966/Cloud computingcomputation offloadingdelay optimizationwireless communications |
| spellingShingle | Xianling Meng Wei Wang Zhaoyang Zhang Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing IEEE Access Cloud computing computation offloading delay optimization wireless communications |
| title | Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing |
| title_full | Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing |
| title_fullStr | Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing |
| title_full_unstemmed | Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing |
| title_short | Delay-Constrained Hybrid Computation Offloading With Cloud and Fog Computing |
| title_sort | delay constrained hybrid computation offloading with cloud and fog computing |
| topic | Cloud computing computation offloading delay optimization wireless communications |
| url | https://ieeexplore.ieee.org/document/8023966/ |
| work_keys_str_mv | AT xianlingmeng delayconstrainedhybridcomputationoffloadingwithcloudandfogcomputing AT weiwang delayconstrainedhybridcomputationoffloadingwithcloudandfogcomputing AT zhaoyangzhang delayconstrainedhybridcomputationoffloadingwithcloudandfogcomputing |