Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems
To improve the operational efficiency of smart city, smart devices extract informative status updates from sampled image and video data to intelligently monitor the surroundings. Mobile edge computing (MEC) is considered as an emerging technology to provide energy-constrained devices with enhanced c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9007675/ |
| _version_ | 1818663884185141248 |
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| author | Long Liu Xiaoqi Qin Zhi Zhang Ping Zhang |
| author_facet | Long Liu Xiaoqi Qin Zhi Zhang Ping Zhang |
| author_sort | Long Liu |
| collection | DOAJ |
| description | To improve the operational efficiency of smart city, smart devices extract informative status updates from sampled image and video data to intelligently monitor the surroundings. Mobile edge computing (MEC) is considered as an emerging technology to provide energy-constrained devices with enhanced computation capability by offloading tasks to nearby servers. In such circumstance, the freshness of obtained status updates is critical to system performance, which can be characterized by the concept of age of information (AoI). Due to resource contention among multiple devices, the problem of how to maintain the timeliness of task executing is not trivial. In this paper, we are interested in minimizing the age of obtained status updates by jointly optimizing task generation, computation offloading as well as communication and computational resource allocation under the average energy constraint at each device. To tackle the time couplings of task generation and computation offloading decisions, we leverage the Lyapunov optimization technique to convert the long-term stochastic optimization problem into a per-time slot deterministic optimization problem. In each time slot, an online algorithm is proposed to determine the task offloading and computation offloading strategy. Moreover, we theoretically prove that the proposed algorithm can be arbitrarily close to the optimal performance with the gap of O (1/V). Simulation results show that our proposed scheme achieves better performance when compared with existing schemes. |
| first_indexed | 2024-12-17T05:23:56Z |
| format | Article |
| id | doaj.art-899a808524e54edcad00b0c818d9265f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T05:23:56Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-899a808524e54edcad00b0c818d9265f2022-12-21T22:01:56ZengIEEEIEEE Access2169-35362020-01-018382483826110.1109/ACCESS.2020.29760489007675Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC SystemsLong Liu0https://orcid.org/0000-0002-7899-1700Xiaoqi Qin1https://orcid.org/0000-0003-0602-476XZhi Zhang2https://orcid.org/0000-0001-8672-6766Ping Zhang3https://orcid.org/0000-0002-0269-104XState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaTo improve the operational efficiency of smart city, smart devices extract informative status updates from sampled image and video data to intelligently monitor the surroundings. Mobile edge computing (MEC) is considered as an emerging technology to provide energy-constrained devices with enhanced computation capability by offloading tasks to nearby servers. In such circumstance, the freshness of obtained status updates is critical to system performance, which can be characterized by the concept of age of information (AoI). Due to resource contention among multiple devices, the problem of how to maintain the timeliness of task executing is not trivial. In this paper, we are interested in minimizing the age of obtained status updates by jointly optimizing task generation, computation offloading as well as communication and computational resource allocation under the average energy constraint at each device. To tackle the time couplings of task generation and computation offloading decisions, we leverage the Lyapunov optimization technique to convert the long-term stochastic optimization problem into a per-time slot deterministic optimization problem. In each time slot, an online algorithm is proposed to determine the task offloading and computation offloading strategy. Moreover, we theoretically prove that the proposed algorithm can be arbitrarily close to the optimal performance with the gap of O (1/V). Simulation results show that our proposed scheme achieves better performance when compared with existing schemes.https://ieeexplore.ieee.org/document/9007675/Mobile edge computingage of informationtask offloadingresource allocationLyapunov optimization |
| spellingShingle | Long Liu Xiaoqi Qin Zhi Zhang Ping Zhang Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems IEEE Access Mobile edge computing age of information task offloading resource allocation Lyapunov optimization |
| title | Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems |
| title_full | Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems |
| title_fullStr | Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems |
| title_full_unstemmed | Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems |
| title_short | Joint Task Offloading and Resource Allocation for Obtaining Fresh Status Updates in Multi-Device MEC Systems |
| title_sort | joint task offloading and resource allocation for obtaining fresh status updates in multi device mec systems |
| topic | Mobile edge computing age of information task offloading resource allocation Lyapunov optimization |
| url | https://ieeexplore.ieee.org/document/9007675/ |
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