MEACC: an energy-efficient framework for smart devices using cloud computing systems

Khalid ALSUBHI; Zuhaib IMTIAZ; Ayesha RAANA; M. Usman ASHRAF; Babur HAYAT

doi:10.1631/FITEE.1900198

Your Location：

Home >

Browse articles >

MEACC: an energy-efficient framework for smart devices using cloud computing systems

Regular Papers | Updated：2022-05-19

- MEACC: an energy-efficient framework for smart devices using cloud computing systems
  Enhanced Publication
- MEACC：一种基于云计算的智能设备节能架构
- Frontiers of Information Technology & Electronic Engineering Vol. 21, Issue 6, Pages: 917-930(2020)
- Affiliations：
  
  Department of Computer Science, King Abdulaziz University, Saudi Arabia
  Department of Computer Science, University of Sialkot, Sialkot 51310, Pakistan
  Department of Computer Science, University of Management and Technology, Sialkot 51310, Pakistan
  Department of Computer Science, University of Lahore, Gujrat 50700, Pakistan
- Author bio：
  
  M. Usman ASHRAF, E-mail: usman.ashraf@skt.umt.edu.pk
- Funds：
- DOI：10.1631/FITEE.1900198
  CLC： TP393
- Published：2020-06，
  
  Received：17 April 2019，
  
  Revised：20 May 2020，
- Accepted：
Scan QR Code
KHALID ALSUBHI, ZUHAIB IMTIAZ, AYESHA RAANA, et al. MEACC: an energy-efficient framework for smart devices using cloud computing systems. [J]. Frontiers of information technology & electronic engineering, 2020, 21(6): 917-930.
DOI：

KHALID ALSUBHI, ZUHAIB IMTIAZ, AYESHA RAANA, et al. MEACC: an energy-efficient framework for smart devices using cloud computing systems. [J]. Frontiers of information technology & electronic engineering, 2020, 21(6): 917-930. DOI： 10.1631/FITEE.1900198.

摘要

随着智能设备存储容量快速增长，价格不断降低，以及算力、存储和通信技术的提升，APP应用程序得到快速发展，在全球网络基础设施上耗费的流量亦越来越多。智能设备引领着新兴技术发展，并在其快速演进中发挥至关重要的作用，已成为信息技术时代全天候的基本需求。智能设备运行着广泛的处理密集型APP，APP在智能设备上的大量使用导致其复杂性不断增加，资源大量消耗，包括智能设备的电池电量、处理器、RAM等，阻碍了智能设备正常运行。资源的限制极大增加了用户处理任务的难度，因此合理的资源利用和能效是智能设备的基本考虑因素。本文提出一种基于云计算的移动端能效增强模型(MEACC)，致力于解决智能设备中功耗大、资源利用率低等关键问题。MEACC能有效筛选出需在智能设备上运行或卸载至云端处理的APP。此外，可有效计算出移动端以及云端所需的运行开销，包括通信成本。在作出卸载决定前，MEACC持续监测资源情况。MEACC既能实现负载均衡又能降低功耗，是新兴移动计算领域十分具有前景的应用架构。

Abstract

Rapidly increasing capacities

decreasing costs

and improvements in computational power

storage

and communication technologies have led to the development of many applications that carry increasingly large amounts of traffic on the global networking infrastructure. Smart devices lead to emerging technologies and play a vital role in rapid evolution. Smart devices have become a primary 24/7 need in today's information technology world and include a wide range of supporting processing-intensive applications. Extensive use of many applications on smart devices results in increasing complexity of mobile software applications and consumption of resources at a massive level

including smart device battery power

processor

and RAM

and hinders their normal operation. Appropriate resource utilization and energy efficiency are fundamental considerations for smart devices because limited resources are sporadic and make it more difficult for users to complete their tasks. In this study we propose the model of mobile energy augmentation using cloud computing (MEACC)

a new framework to address the challenges of massive power consumption and inefficient resource utilization in smart devices. MEACC efficiently filters the applications to be executed on a smart device or offloaded to the cloud. Moreover

MEACC efficiently calculates the total execution cost on both the mobile and cloud sides including communication costs for any application to be offloaded. In addition

resources are monitored before making the decision to offload the application. MEACC is a promising model for load balancing and power consumption reduction in emerging mobile computing environments.

关键词

卸载智能设备云计算移动计算能耗

Keywords

OffloadingSmart devicesCloud computingMobile computingPower consumption

references

RN Calheiros, , , R Ranjan, , , A Beloglazov, , , 等. . CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. . Softw Pract Exp, , 2011. . 41((1):):23--50. . DOI:10.1002/spe.995http://doi.org/10.1002/spe.995..

HJ Cao, , , J Cai. . Distributed multiuser computation off- loading for cloudlet-based mobile cloud computing: a game-theoretic machine learning approach. . IEEE Trans Veh Technol, , 2017. . 67((1):):752--764. . DOI:10.1109/TVT.2017.2740724http://doi.org/10.1109/TVT.2017.2740724..

BG Chun, , , S Ihm, , , P Maniatis, , , 等. . CloneCloud: elastic execution between mobile device and cloud. . Proc 6th Conf on Computer Systems, , 2011. . p.301--314. . DOI:10.1145/1966445.1966473http://doi.org/10.1145/1966445.1966473..

M Creeger. . CTO roundtable: cloud computing. . Queue, , 2009. . 7((5):):1DOI:10.1145/1551644.1551646http://doi.org/10.1145/1551644.1551646..

E Cuervo, , , A Balasubramanian, , , DK Cho, , , 等. . MAUI: making smartphones last longer with code offload. . Proc 8th Int Conf on Mobile Systems, Applications, and Services, , 2010. . p.49--62. . DOI:10.1145/1814433.1814441http://doi.org/10.1145/1814433.1814441..

HT Dinh, , , C Lee, , , D Niyato, , , 等. . A survey of mobile cloud computing: architecture, applications, and approaches. . Wirel Commun Mob Comput, , 2013. . 13((18):):1587--1611. . DOI:10.1002/wcm.1203http://doi.org/10.1002/wcm.1203..

MA Elgendy, , , A Shawish, , , MI Moussa. . MCACC: new approach for augmenting the computing capabilities of mobile devices with cloud computing. . Science and Information Conf, , 2014. . p.79--86. . DOI:10.1109/SAI.2014.6918175http://doi.org/10.1109/SAI.2014.6918175..

M Gajbhe, , , SR Sakhare. . Performance augmentation of mobile devices using cloud computing. . Int J Comput Sci Inform Technol, , 2015. . 6((4):):3581--3587. . ..

R Hasan, , , MM Hossain, , , R Khan. . Aura: an IoT based cloud infrastructure for localized mobile computation outsourcing. . Proc 3rd IEEE Int Conf on Mobile Cloud Computing, Services, and Engineering, , 2015. . p.183--188. . DOI:10.1109/MobileCloud.2015.37http://doi.org/10.1109/MobileCloud.2015.37..

H Jadad, , , A Touzene, , , N Alzeidi, , , 等. . Realistic off- loading scheme for mobile cloud computing. . Proc 13th Int Conf on Mobile Web and Intelligent Information Systems, , 2016. . p.81--92. . DOI:10.1007/978-3-319-44215-0_7http://doi.org/10.1007/978-3-319-44215-0_7..

S Kosta, , , A Aucinas, , , P Hui, , , 等. . Thinkair: dynamic resource allocation and parallel execution in the cloud for mobile code offloading. . Proc IEEE INFOCOM, , 2012. . p.945--953. . DOI:10.1109/INFCOM.2012.6195845http://doi.org/10.1109/INFCOM.2012.6195845..

D Kovachev, , , R Klamma. . Framework for computation offloading in mobile cloud computing. . Int Interact Multim Artif Intell, , 2012. . 1((7):):6--15. . ..

FM Liu, , , P Shu, , , H Jin, , , 等. . Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications. . IEEE Wirel Commun, , 2013. . 20((3):):14--22. . DOI:10.1109/MWC.2013.6549279http://doi.org/10.1109/MWC.2013.6549279..

P Mell, , , T Grance. . The NIST Definition of Cloud Computing. . NIST Special Publication 800-145, NIST, Gaithersburg, , 2011. ..

A Mukherjee, , , D De. . A cost-effective location tracking strategy for femtocell based mobile network. . Proc Int Conf on Control, Instrumentation, Energy and Communication, , 2014. . p.533--537. . DOI:10.1109/CIEC.2014.6959146http://doi.org/10.1109/CIEC.2014.6959146..

A Paranjothi, , , MS Khan, , , M Nijim. . Survey on three components of mobile cloud computing: offloading, distribution and privacy. . J Comput Commun, , 2017. . 5((6):):75210DOI:10.4236/jcc.2017.56001http://doi.org/10.4236/jcc.2017.56001..

S Robinson. . Cellphone Energy Gap: Desperately Seeking Solutions. . Strategy Analytics. Technology Report, Chicago, IL, USA, , 2009. ..

M Satyanarayanan, , , V Bahl, , , R Caceres, , , 等. . The case for VM-based cloudlets in mobile computing. . IEEE Perv Comput, , 2009. . 8((4):):14--23. . DOI:10.1109/MPRV.2009.82http://doi.org/10.1109/MPRV.2009.82..

U Sinha, , , M Shekhar. . Comparison of various cloud simulation tools available in cloud computing. . Int J Adv Res Comput Commun Eng, , 2015. . 4((3):):171--176. . DOI:10.17148/IJARCCE.2015.4342http://doi.org/10.17148/IJARCCE.2015.4342..

M Sookhak, , , FR Yu, , , MK Khan, , , 等. . Attribute-based data access control in mobile cloud computing: taxonomy and open issues. . Fut Gener Comput Syst, , 2017. . 72273--287. . DOI:10.1016/j.future.2016.08.018http://doi.org/10.1016/j.future.2016.08.018..

XY Tao, , , K Ota, , , MX Dong, , , 等. . Performance guaranteed computation offloading for mobile-edge cloud computing. . IEEE Wirel Commun Lett, , 2017. . 6((6):):774--777. . DOI:10.1109/LWC.2017.2740927http://doi.org/10.1109/LWC.2017.2740927..

A Zanni, , , SY Yu, , , S Secci, , , 等. . Automated offloading of Android applications for computation/energy optimizations. . IEEE Conf on Computer Communications Workshops, , 2017. . p.990--991. . DOI:10.1109/INFCOMW.2017.8116525http://doi.org/10.1109/INFCOMW.2017.8116525..

L Zhang, , , D Fu, , , JC Liu, , , 等. . On energy-efficient off- loading in mobile cloud for real-time video applications. . IEEE Trans Circ Syst Video Technol, , 2017. . 27((1):):170--181. . DOI:10.1109/TCSVT.2016.2539690http://doi.org/10.1109/TCSVT.2016.2539690..

Q Zhang, , , L Cheng, , , R Boutaba. . Cloud computing: state-of-the-art and research challenges. . J Int Serv Appl, , 2010. . 1((1):):7--18. . DOI:10.1007/s13174-010-0007-6http://doi.org/10.1007/s13174-010-0007-6..

XW Zhang, , , S Jeong, , , A Kunjithapatham, , , 等. . Towards an elastic application model for augmenting computing capabilities of mobile platforms. . Proc 3rd Int Conf on Mobile Wireless Middleware, Operating Systems, and Applications, , 2010. . p.161--174. . DOI:10.1007/978-3-642-17758-3_12http://doi.org/10.1007/978-3-642-17758-3_12..

BW Zhou, , , R Buyya. . Augmentation techniques for mobile cloud computing: a taxonomy, survey, and future directions. . ACM Comput Surv, , 2018. . 51((1):):13DOI:10.1145/3152397http://doi.org/10.1145/3152397..

BW Zhou, , , AV Dastjerdi, , , RN Calheiros, , , 等. . A context sensitive offloading scheme for mobile cloud computing service. . IEEE 8th Int Conf on Cloud Computing, , 2015. . p.869--876. . DOI:10.1109/CLOUD.2015.119http://doi.org/10.1109/CLOUD.2015.119..

D Zissis, , , D Lekkas. . Addressing cloud computing security issues. . Fut Gener Comput Syst, , 2012. . 28((3):):583--592. . DOI:10.1016/j.future.2010.12.006http://doi.org/10.1016/j.future.2010.12.006..

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Technology trends in large-scale high-efficiency network computing

Driftor: mitigating cloud-based side-channel attacks by switching and migrating multi-executor virtual machines

Towards adaptable and tunable cloud-based map-matching strategy for GPS trajectories#

Data center network architecture in cloud computing:review, taxonomy, and open research issues

Related Author

Yusheng XIA

Yujing LIU

Congxi SONG

Na ZHAO

Ziling WEI

Jijun CAO

Yi DAI

Baokang ZHAO

Related Institution

School of Computer, National University of Defense Technology

Academy of Military Science

National Digital Switching System Engineering & Technological Research Center

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

Institute of Mathematics and Computer Science, University of Sindh, Jamshoro

Address：Zhejiang University Press, 148 Tianmushan Road, Hangzhou, China Postal code：310028
Tel：+86-571-88273162 Email：fitee@zju.edu.cn
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰