The Advantage of Computation Offloading in Multi-Access Edge Computing

被引:0
作者
Singh, Raghubir [1 ,2 ]
Armour, Simon [1 ,2 ]
Khan, Aftab [3 ]
Sooriyabandara, Mahesh [3 ]
Oikonomou, George [1 ,2 ]
机构
[1] Univ Bristol, Commun Syst & Networks Res Grp, Bristol, Avon, England
[2] Univ Bristol, Dept Elect & Elect Engn, Bristol, Avon, England
[3] Toshiba Res Europe Ltd, Telecommun Res Lab, Bristol, Avon, England
来源
2019 FOURTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC) | 2019年
基金
英国工程与自然科学研究理事会;
关键词
Computation offloading; Multi-Access Edge Computing; task completion time; mobile devices; energy savings;
D O I
10.1109/fmec.2019.8795335
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Computation offloading plays a critical role in reducing task completion time for mobile devices. The advantages of computation offloading to cloud resources in Mobile Cloud Computing have been widely considered. In this paper, we have investigated different scenarios for offloading to less distant Multi-Access Edge Computing (MEC) servers for multiple users with a range of mobile devices and computational tasks. We present detailed simulation data for how offloading can be beneficial in a MEC network with varying quantitative mobile user demand, heterogeneity in mobile device on-board and MEC processor speeds, computational task complexity, communication speeds, link access delays and mobile device user numbers. Unlike previous work where simulations considered only limited communication speeds for offloading, we have extended the range of link speeds and included two types of communication delay. We find that more computationally complex applications are offloaded preferentially (especially with the higher server:mobile device processor speed ratios) while low link speeds and any delays caused by network delays or excessive user numbers degrade any advantages in reduced task completion times offered by offloading. Additionally, significant savings in energy usage by mobile devices are guaranteed except at very low link speeds.
引用
收藏
页码:289 / 294
页数:6
相关论文
共 26 条
[1]  
Bahl Victor., 2015, MICROSOFT DEVICES NE
[2]  
Balan RK, 2007, MOBISYS '07: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS, AND SERVICES, P272
[3]   Decentralized Computation Offloading Game for Mobile Cloud Computing [J].
Chen, Xu .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2015, 26 (04) :974-983
[4]  
Chun BG, 2011, EUROSYS 11: PROCEEDINGS OF THE EUROSYS 2011 CONFERENCE, P301
[5]  
Clinch S, 2012, INT CONF PERVAS COMP, P122, DOI 10.1109/PerCom.2012.6199858
[6]  
Cuervo E., 2010, P 8 MOBISYS NEW YORK, P49, DOI [10.1145/1814433.1814441, DOI 10.1145/1814433.1814441]
[7]  
ETSI, 2018, LONG TERM EVOLUTION
[8]   Balancing performance, energy, and quality in pervasive computing [J].
Flinn, J ;
Park, SY ;
Satyanarayanan, M .
22ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS, PROCEEDINGS, 2002, :217-226
[9]   A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain [J].
Guo, Hao ;
Li, Congdong ;
Zhang, Ying ;
Zhang, Chunnan ;
Wang, Yu .
COMPLEXITY, 2018,
[10]   Computation Offloading for Multi-Access Mobile Edge Computing in Ultra-Dense Networks [J].
Guo, Hongzhi ;
Liu, Jiajia ;
Zhang, Jie .
IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (08) :14-19