Research on the cooperative offloading strategy of sensory data based on delay and energy constraints

Peiyan YUAN; Saike SHAO; Ran WEI; Junna ZHANG; Xiaoyan ZHAO

doi:10.11959/j.issn.2096-3750.2023.00324

您当前的位置：

首页 >

文章列表页 >

Research on the cooperative offloading strategy of sensory data based on delay and energy constraints

Theory and Technology | 更新时间：2024-08-16

- Research on the cooperative offloading strategy of sensory data based on delay and energy constraints
- Chinese Journal on Internet of Things Vol. 7, Issue 1, Pages: 109-117(2023)
- 作者机构：
  
  1. 河南师范大学计算机与信息工程学院，河南新乡 453007
  2. 河南师范大学教学资源与教育质量评估大数据河南省工程实验室，河南新乡 453007
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2023.00324
  CLC： TP391
- Online First：2023-03，
  
  Published：30 March 2023
- 稿件说明：
移动端阅览
Peiyan YUAN, Saike SHAO, Ran WEI, et al. Research on the cooperative offloading strategy of sensory data based on delay and energy constraints[J]. Chinese Journal on Internet of Things, 2023, 7(1): 109-117.
DOI：

Peiyan YUAN, Saike SHAO, Ran WEI, et al. Research on the cooperative offloading strategy of sensory data based on delay and energy constraints[J]. Chinese Journal on Internet of Things, 2023, 7(1): 109-117. DOI： 10.11959/j.issn.2096-3750.2023.00324.

摘要

研究了物联网感知数据边缘卸载问题，即多个边缘节点相互协作，将原本需要发送给云中心的感知数据全部或部分卸载，以保护数据隐私与提升用户体验。在协作卸载过程中，感知数据传输以及边缘节点之间的信息交互会消耗系统资源，产生协作代价。如何在保持较低协作代价的基础上提高感知数据的卸载比例是一个具有挑战性的问题。首先，将该问题表述为一个满足网络时延和系统能耗约束的感知数据卸载比例和协作规模联合优化问题。其次，提出了一种基于约束投影和变量分裂的分布式交替方向乘子法（ADMM

alternating direction method of multipliers）进行求解。最后，使用MATLAB进行仿真实验，数值结果表明，与分布式优化算法（DOA

distributed optimization algorithm）、公平合作算法（FCA

fairness cooperation algorithm）和多子任务到多服务器卸载方案（MTMS

multi-subtasks-to-multi-servers offloading scheme）相比，所提方法在网络时延和能耗上均有较大优化。

Abstract

The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center

which protects data privacy and improves user experience.In the process of cooperative offloading

the transmission of the sensing data and the information exchange among edge servers will consume system resources

resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently

a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally

simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA)

the distributed optimization algorithm (DOA)

and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.

关键词

Keywords

references

PAN J L , MCELHANNON J . Future edge cloud and edge computing for Internet of Things applications [J ] . IEEE Internet of Things Journal , 2018 , 5 ( 1 ): 439 - 449 .

HU Y C , PATEL M , SABELLA D , et al . Mobile edge computing—a key technology towards 5G [J ] . ETSI white paper , 2015 , 11 ( 11 ): 1 - 16 .

MAO Y Y , YOU C S , ZHANG J , et al . A survey on mobile edge computing:the communication perspective [J ] . IEEE Communications Surveys ＆ Tutorials , 2017 , 19 ( 4 ): 2322 - 2358 .

CHEN M Z , CHALLITA U , SAAD W , et al . Artificial neural networks-based machine learning for wireless networks:a tutorial [EB ] . 2017 .

DENG S G , XIANG Z Z , TAHERI J , et al . Optimal application deployment in resource constrained distributed edges [J ] . IEEE Transactions on Mobile Computing , 2021 , 20 ( 5 ): 1907 - 1923 .

ZHAO H L , DENG S G , LIU Z J , et al . Distributed redundancy scheduling for microservice-based applications at the edge [J ] . 2021 IEEE World Congress on Services (SERVICES) , 2021 :1.

DU J B , ZHAO L Q , FENG J , et al . Computation offloading and resource allocation in mixed fog/cloud computing systems with Min-max fairness guarantee [J ] . IEEE Transactions on Communications , 2018 , 66 ( 4 ): 1594 - 1608 .

CHEN M H , LIANG B , DONG M . Multi-user multi-task offloading and resource allocation in mobile cloud systems [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 10 ): 6790 - 6805 .

CHEN M H , DONG M , LIANG B . Resource sharing of a computing access point for multi-user mobile cloud offloading with delay constraints [J ] . IEEE Transactions on Mobile Computing , 2018 , 17 ( 12 ): 2868 - 2881 .

DU J B , ZHAO L Q , CHU X L , et al . Enabling low-latency applications in LTE-A based mixed fog/cloud computing systems [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 2 ): 1757 - 1771 .

LIU C F , BENNIS M , DEBBAH M , et al . Dynamic task offloading and resource allocation for ultra-reliable low-latency edge computing [J ] . IEEE Transactions on Communications , 2019 , 67 ( 6 ): 4132 - 4150 .

XING H , LIU L , XU J , et al . Joint task assignment and resource allocation for D2D-enabled mobile-edge computing [J ] . IEEE Transactions on Communications , 2019 , 67 ( 6 ): 4193 - 4207 .

TRAN T X , POMPILI D . Joint task offloading and resource allocation for multi-server mobile-edge computing networks [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 1 ): 856 - 868 .

WANG K , YIN H , QUAN W , et al . Enabling collaborative edge computing for software defined vehicular networks [J ] . IEEE Network , 2018 , 32 ( 5 ): 112 - 117 .

SAHNI Y , CAO J N , YANG L , et al . Multi-hop multi-task partial computation offloading in collaborative edge computing [J ] . IEEE Transactions on Parallel and Distributed Systems , 2021 , 32 ( 5 ): 1133 - 1145 .

DENG S G , ZHANG C , LI C , et al . Burst load evacuation based on dispatching and scheduling in distributed edge networks [J ] . IEEE Transactions on Parallel and Distributed Systems , 2021 , 32 ( 8 ): 1918 - 1932 .

SAEED A , AMMAR M , HARRAS K A , et al . Vision:the case for symbiosis in the Internet of Things [C ] // MCS '15:Proceedings of the 6th International Workshop on Mobile Cloud Computing and Services . 2015 : 23 - 27 .

TRAN T X , HAJISAMI A , PANDEY P , et al . Collaborative mobile edge computing in 5G networks:new paradigms,scenarios,and challenges [J ] . IEEE Communications Magazine , 2017 , 55 ( 4 ): 54 - 61 .

CHEN L X , XU J . Socially trusted collaborative edge computing in ultra dense networks [C ] // SEC '17:Proceedings of the Second ACM/IEEE Symposium on Edge Computing . 2017 : 1 - 11 .

CHI G X , WANG Y M , LIU X , et al . Latency-optimal task offloading for mobile-edge computing system in 5G heterogeneous networks [C ] // Proceedings of 2018 IEEE 87th Vehicular Technology Conference . Piscataway:IEEE Press , 2018 : 1 - 5 .

REN J K , YU G D , CAI Y L , et al . Latency optimization for resource allocation in mobile-edge computation offloading [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 8 ): 5506 - 5519 .

XIAO Y , KRUNZ M . QoE and power efficiency tradeoff for fog computing networks with fog node cooperation [C ] // Proceedings of IEEE INFOCOM 2017 - IEEE Conference on Computer Communications . Piscataway:IEEE Press , 2017 : 1 - 9 .

YUAN P Y , et al . Caching hit ratio maximization in mobile edge computing with node cooperation [J ] . Computer Networks , 2021 ,200:108507.

WANG Q , CHEN S G . Latency-minimum offloading decision and resource allocation for fog-enabled Internet of Things networks [J ] . Transactions on Emerging Telecommunications Technologies , 2020 , 31 ( 12 ): e3880 .

XING H , LIU L , XU J , et al . Joint task assignment and wireless resource allocation for cooperative mobile-edge computing [C ] // Proceedings of 2018 IEEE International Conference on Communications . Piscataway:IEEE Press , 2018 : 1 - 6 .

CHEN M , HAO Y X . Task offloading for mobile edge computing in software defined ultra-dense network [J ] . IEEE Journal on Selected Areas in Communications , 2018 , 36 ( 3 ): 587 - 597 .

VU T T , NGUYEN D N , HOANG D T , et al . Optimal energy efficiency with delay constraints for multi-layer cooperative fog computing networks [J ] . IEEE Transactions on Communications , 2021 , 69 ( 6 ): 3911 - 3929 .

HUANG X G , CUI Y F , CHEN Q B , et al . Joint task offloading and QoS-aware resource allocation in fog-enabled Internet-of-things networks [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 8 ): 7194 - 7206 .

LAN X L , CAI L , CHEN Q C . Execution latency and energy consumption tradeoff in mobile-edge computing systems [C ] // Proceedings of 2019 IEEE/CIC International Conference on Communications in China (ICCC) . Piscataway:IEEE Press , 2019 : 123 - 128 .

DONG Y F , GUO S T , LIU J D , et al . Energy-efficient fair cooperation fog computing in mobile edge networks for smart city [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 5 ): 7543 - 7554 .

WANG J , WU W B , LIAO Z F , et al . An energy-efficient off-loading scheme for low latency in collaborative edge computing [J ] . IEEE Access , 2019 , 7 : 149182 - 149190 .

Views

236

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

⁰