Mobile Edge Computing: A Survey
Open accessAbstract
Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless, and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors toward mobile subscribers, enterprises, and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultralow latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.
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The integration of edge computing and deep learning enables the deep penetration of computing intelligence into every corner of a city, forming a smart city that can provide more efficient, economic, energy-saving, and convenient services.
“The integration of edge computing and deep learning enables the deep penetration of computing intelligence into every corner of a city, forming a smart city that can provide more efficient, economic, energy-saving, and convenient services [115], [116].”
From Deep learning for edge computing applications: A State-of-the-Art survey (2020) · cites this paper as [115]
Cites
The NIST Definition of Cloud Computing
Mell, P., & Grance, T. (2011) · doi:10.6028/nist.sp.800-145 · Cited by 15,338 · see citing works
Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630 · see citing works
Heart Disease and Stroke Statistics—2014 Update
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Blaha, M. J., Dai, S., Ford, E. S., Fox, C. S., Franco, S., et al. (2013) · Circulation · doi:10.1161/01.cir.0000441139.02102.80 · Cited by 5,207 · see citing works
Recent advances in augmented reality
Azuma, R. T., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001) · IEEE Computer Graphics and Applications · doi:10.1109/38.963459 · Cited by 4,170 · see citing works
The case for vm-based cloudlets in mobile computing
Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.82 · Cited by 3,660 · see citing works
Heidenreich, P. A., Trogdon, J. G., Khavjou, O. A., Butler, J., Dracup, K., Ezekowitz, M. D., Finkelstein, E. A., Hong, Y., Johnston, S. C., Khera, A., et al. (2011) · Circulation · doi:10.1161/cir.0b013e31820a55f5 · Cited by 3,208 · see citing works
Efficient multi-user computation offloading for mobile-edge cloud computing
Chen, X., Jiao, L., Li, W., & Fu, X. (2016) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2015.2487344 · Cited by 2,675 · see citing works
A survey of mobile cloud computing: architecture, applications, and approaches
Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2013) · Wireless Communications and Mobile Computing · doi:10.1002/wcm.1203 · Cited by 2,391 · see citing works
Cloud computing for mobile users: can offloading computation save energy?
Kumar, K., & Lu, Y.-H. (2010) · Computer · doi:10.1109/mc.2010.98 · Cited by 1,493 · see citing works
Yi, S., Li, C., & Li, Q. (2015) · doi:10.1145/2757384.2757397 · Cited by 1,358 · see citing works
Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges
Roman, R., Lopez, J., & Mambo, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2016.11.009 · Cited by 1,338 · see citing works
Non-interactive Verifiable Computing: Outsourcing Computation to Untrusted Workers
Gennaro, R., Gentry, C., & Parno, B. J. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-14623-7_25 · Cited by 1,156 · see citing works
The Fog Computing Paradigm: Scenarios and Security Issues
Stojmenovic, I., & Wen, S. (2014) · Annals of Computer Science and Information Systems · doi:10.15439/2014f503 · Cited by 1,037 · see citing works
Augmented Reality: An Overview and Five Directions for AR in Education
Yuen, S. C.-Y., Yaoyuneyong, G., & Johnson, E. (2011) · Journal of Educational Technology Development and Exchange · doi:10.18785/jetde.0401.10 · Cited by 1,002 · see citing works
Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing
Sardellitti, S., Scutari, G., & Barbarossa, S. (2015) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2015.2448520 · Cited by 889 · see citing works
A Survey of Computation Offloading for Mobile Systems
Kumar, K., Liu, J., Lu, Y.-H., & Bhargava, B. (2012) · Mobile Networks and Applications · doi:10.1007/s11036-012-0368-0 · Cited by 847 · see citing works
Fog Computing: Platform and Applications
Yi, S., Hao, Z., Qin, Z., & Li, Q. (2015) · 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb) · doi:10.1109/hotweb.2015.22 · Cited by 829 · see citing works
EPPA: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications
Lu, R., Liang, X., Li, X., Lin, X., & Shen, X. (2012) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2012.86 · Cited by 769 · see citing works
Singh, S., & Singh, N. (2012) · International Conference on Communication, Information & Computing Technology · doi:10.1109/iccict.2012.6398180 · Cited by 757 · see citing works
Talking to Strangers: Authentication in Ad-Hoc Wireless Networks.
Balfanz, D., Smetters, D. K., Stewart, P. A., & Wong, H. C. (2002) · Cited by 633 · see citing works
Fog Computing: principles, architectures, and applications
Dastjerdi, A. V., Gupta, H., Calheiros, R. N., Ghosh, S., & Buyya, R. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805395-9.00004-6 · Cited by 620 · see citing works
A survey on mobile edge computing
Ahmed, A., & Ahmed, E. (2016) · International Conference on Intelligent Systems and Control · doi:10.1109/isco.2016.7727082 · Cited by 611 · see citing works
Network virtualization and software defined networking for cloud computing: a survey
Jain, R. K., & Paul, S. (2013) · IEEE Communications Magazine · doi:10.1109/mcom.2013.6658648 · Cited by 544 · see citing works
Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data
Wang, C., Cao, N., Ren, K., & Lou, W. (2011) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2011.282 · Cited by 530 · see citing works
Security and Privacy Issues of Fog Computing: A Survey
Yi, S., Qin, Z., & Li, Q. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-21837-3_67 · Cited by 529 · see citing works
Mobile fog: a programming model for large-scale applications on the internet of things
Hong, K., Lillethun, D., Ramachandran, U., Ottenwälder, B., & Koldehofe, B. (2013) · Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing · doi:10.1145/2491266.2491270 · Cited by 486 · see citing works
Cloud radio access network (C-RAN): a primer
Wu, J. H., Zhang, Z., Yu, H. W., & Wen, Y. (2015) · IEEE Network · doi:10.1109/mnet.2015.7018201 · Cited by 477 · see citing works
The Mobile Data Challenge: Big Data for Mobile Computing Research
Laurila, J. K., Gática-Pérez, D., Aad, I., et al. (2012) · TUbilio (Technical University of Darmstadt) · Cited by 420 · see citing works
An overview of Fog computing and its security issues
Stojmenović, I., Wen, S., Huang, X., & Luan, T. H. (2015) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.3485 · Cited by 408 · see citing works
Fog Computing May Help to Save Energy in Cloud Computing
Jalali, F., Hinton, K., Ayre, R., Alpcan, T., & Tucker, R. S. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2545559 · Cited by 408 · see citing works
Fog Computing: Focusing on Mobile Users at the Edge
Luan, T. H., Gao, L., Li, Z., Xiang, Y., Wei, G., & Sun, L. (2015) · arXiv · doi:10.48550/arxiv.1502.01815 · Cited by 398 · see citing works
Verbelen, T., Simoens, P., Turck, F. D., & Dhoedt, B. (2012) · Mobile Cloud Computing & Services · doi:10.1145/2307849.2307858 · Cited by 354 · see citing works
Mobile Edge Computing: Opportunities, solutions, and challenges
Ahmed, E., & Rehmani, M. H. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.09.015 · Cited by 353 · see citing works
Attacking software-defined networks
Shin, S., & Gu, G. (2013) · doi:10.1145/2491185.2491220 · Cited by 320 · see citing works
(2014) · Cited by 296 · see citing works
Femto clouds: leveraging mobile devices to provide cloud service at the edge
Habak, K., Ammar, M., Harras, K. A., & Zegura, E. (2015) · 2015 IEEE 8th International Conference on Cloud Computing · doi:10.1109/cloud.2015.12 · Cited by 291 · see citing works
Mobile big data analytics using deep learning and apache spark
Alsheikh, M. A., Niyato, D. T., Lin, S., Tan, H.-P., & Han, Z. (2016) · IEEE Network · doi:10.1109/mnet.2016.7474340 · Cited by 273 · see citing works
User-defined gestures for augmented reality
Piumsomboon, T., Clark, A., Billinghurst, M., et al. (2013) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2468356.2468527 · Cited by 241 · see citing works
Protecting consumer privacy from electric load monitoring
McLaughlin, S., McDaniel, P. D., & Aiello, W. A. (2011) · Proceedings of the ACM Conference on Computer and Communications Security · doi:10.1145/2046707.2046720 · Cited by 241 · see citing works
Data storage auditing service in cloud computing: challenges, methods and opportunities
Yang, K., & Jia, X. (2011) · World Wide Web · doi:10.1007/s11280-011-0138-0 · Cited by 232 · see citing works
Mobile edge computing: progress and challenges
Li, H., Shou, G., Hu, Y., & Guo, Z. (2016) · 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) · doi:10.1109/mobilecloud.2016.16 · Cited by 226 · see citing works
The future of mobile cloud computing: Integrating cloudlets and Mobile Edge Computing
Jararweh, Y., Doulat, A., Alqudah, O., Ahmed, E., Al‐Ayyoub, M., & Benkhelifa, E. (2016) · doi:10.1109/ict.2016.7500486 · Cited by 226 · see citing works
Internet of Things: Principles and Paradigms
Buyya, R., & Dastjerdi, A. V. (2016) · Cited by 222 · see citing works
FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation
Cao, Y. K., Chen, S., Hou, P., & Brown, D. E. (2015) · IEEE International Conference on Networking, Architecture and Storage (NAS) · doi:10.1109/nas.2015.7255196 · Cited by 199 · see citing works
Online user survey on current mobile augmented reality applications
Olsson, T., & Salo, M. (2011) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar.2011.6092372 · Cited by 186 · see citing works
Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues
Kai, K., Wang, C., & Tao, L. (2016) · 中国邮电高校学报：英文版 · doi:10.1016/s1005-8885(16)60021-3 · Cited by 178 · see citing works
Vehicular delay-tolerant networks for smart grid data management using mobile edge computing
Kumar, N., Zeadally, S., & Rodrigues, J. J. P. C. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7588230 · Cited by 178 · see citing works
A Reference Model of Information Assurance & Security
Cherdantseva, Y., & Hilton, J. (2013) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1109/ares.2013.72 · Cited by 174 · see citing works
Fog computing architecture to enable consumer centric internet of things services
Datta, S. K., Bonnet, C., & Haerri, J. (2015) · 2015 International Symposium on Consumer Electronics (ISCE) · doi:10.1109/isce.2015.7177778 · Cited by 172 · see citing works
Fog Computing: Issues and Challenges in Security and Forensics
Wang, Y., Uehara, T., & Sasaki, R. (2015) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2015.173 · Cited by 164 · see citing works
Enabling Real-Time Context-Aware Collaboration through 5G and Mobile Edge Computing
Nunna, S., Κουσαρίδας, Α., Ibrahim, M. S., Dillinger, M., Thüemmler, C., Feußner, H., & Schneider, A. (2015) · International Conference on Information Technology: New Generations · doi:10.1109/itng.2015.155 · Cited by 158 · see citing works
Adaptive Computation Offloading from Mobile Devices into the Cloud
Kovachev, D., Yu, T., & Klamma, R. (2012) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa.2012.115 · Cited by 152 · see citing works
Adaptive Multi-Resource Allocation for Cloudlet-Based Mobile Cloud Computing System
Liu, Y., Lee, M. J., & Zheng, Y. (2015) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2015.2504091 · Cited by 152 · see citing works
Application optimization in mobile cloud computing: Motivation, taxonomies, and open challenges
Ahmed, E., Gani, A., Sookhak, M., Hamid, S. H. A., & Xia, F. (2015) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2015.02.003 · Cited by 149 · see citing works
Smart Items, Fog and Cloud Computing as Enablers of Servitization in Healthcare
Stantchev, V., Barnawi, A., Ghulam, S., SCHUBERT, J., & Tamm, G. (2015) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 148 · see citing works
Zhao, T., Zhou, S., Guo, X., Yun, Z., & Niu, Z. (2015) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/glocomw.2015.7414063 · Cited by 147 · see citing works
All your clouds are belong to us
Somorovsky, J., Heiderich, M., Jensen, M., et al. (2011) · doi:10.1145/2046660.2046664 · Cited by 142 · see citing works
Seamless application execution in mobile cloud computing: Motivation, taxonomy, and open challenges
Ahmed, E., Gani, A., Khan, M. K., Buyya, R., & Khan, S. U. (2015) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2015.03.001 · Cited by 131 · see citing works
A Timing-Based Scheme for Rogue AP Detection
Han, H., Sheng, B., Tan, C. C., et al. (2011) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2011.125 · Cited by 130 · see citing works
Delay constrained offloading for Mobile Edge Computing in cloud-enabled vehicular networks
Zhang, K., Mao, Y., Leng, S., Vinel, A. V., & Zhang, Y. (2016) · International Workshop on Resilient Networks Design and Modeling (RNDM) · doi:10.1109/rndm.2016.7608300 · Cited by 127 · see citing works
Self-citationAn open ecosystem for mobile-cloud convergence
Satyanarayanan, M., Schuster, R., Ebling, M. R., Fettweis, G. P., Flinck, H., Joshi, K., & Sabnani, K. K. (2015) · IEEE Communications Magazine · doi:10.1109/mcom.2015.7060484 · Cited by 126 · see citing works
A review on remote data auditing in single cloud server: Taxonomy and open issues
Sookhak, M., Talebian, H., Ahmed, E., Gani, A., & Khan, M. K. (2014) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2014.04.011 · Cited by 121 · see citing works
Computing at the mobile edge: designing elastic android applications for computation offloading
Orsini, G., Bade, D., & Lamersdorf, W. (2015) · 2015 8th IFIP Wireless and Mobile Networking Conference (WMNC) · doi:10.1109/wmnc.2015.10 · Cited by 112 · see citing works
Recovery for overloaded mobile edge computing
Satria, D., Park, D., & Jo, M. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2016.06.024 · Cited by 112 · see citing works
Help your mobile applications with fog computing
Hassan, M. A., Xiao, M., Wei, Q., & Chen, S. (2015) · IEEE International Conference on Sensing, Communication, and Networking (SECON) · doi:10.1109/seconw.2015.7328146 · Cited by 110 · see citing works
4G as a Next Generation Wireless Network
Khan, A. H., Qadeer, M. A., Ansari, J. A., et al. (2009) · International Conference on Future Computer and Communication · doi:10.1109/icfcc.2009.108 · Cited by 106 · see citing works
Network-centric performance analysis of runtime application migration in mobile cloud computing
Ahmed, E., Akhunzada, A., Whaiduzzaman, M., Gani, A., Hamid, S. H. A., & Buyya, R. (2014) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2014.07.001 · Cited by 106 · see citing works
A survey of security issues in hardware virtualization
Pék, G., Buttyán, L., & Bencsáth, B. (2013) · ACM Computing Surveys · doi:10.1145/2480741.2480757 · Cited by 93 · see citing works
MobiShare: Flexible privacy-preserving location sharing in mobile online social networks
Wei, W., Xu, F., & Li, Q. (2012) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2012.6195664 · Cited by 93 · see citing works
A Survey of Cloudlet Based Mobile Computing
Pang, Z., Sun, L., Wang, Z., Tian, E., & Yang, S. (2015) · doi:10.1109/ccbd.2015.54 · Cited by 91 · see citing works
Heterogeneous Cellular Networks
(2013) · Wiley eBooks · doi:10.1002/9781118555262 · Cited by 88 · see citing works
Sdmec: software defined system for mobile edge computing
Jararweh, Y., Doulat, A., Darabseh, A., Alsmirat, M., Al-Ayyoub, M., & Benkhelifa, E. (2016) · 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW) · doi:10.1109/ic2ew.2016.45 · Cited by 85 · see citing works
When mobile terminals meet the cloud: computation offloading as the bridge
Ma, X., Zhao, Y., Zhang, L., Wang, H., & Peng, L. (2013) · IEEE Network · doi:10.1109/mnet.2013.6616112 · Cited by 84 · see citing works
Sathyan, J., Narayanan, A., Narayan, N., et al. (2012) · CRC Press eBooks · doi:10.1201/b12692-25 · Cited by 83 · see citing works
Heterogeneous Cellular Networks
(2020) · Springer eBooks · doi:10.1007/978-3-319-78262-1_300257 · Cited by 78 · see citing works
Alzahrani, A. I., Alalwan, N., & Sarrab, M. (2014) · Euro American Conference on Telematics and Information Systems · doi:10.1145/2590651.2590670 · Cited by 76 · see citing works
Efficient Exploitation of Mobile Edge Computing for Virtualized 5G in EPC Architectures
Cau, E., Corici, M., Bellavista, P., et al. (2016) · IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) · doi:10.1109/mobilecloud.2016.24 · Cited by 75 · see citing works
Replisom: Disciplined Tiny Memory Replication for Massive IoT Devices in LTE Edge Cloud
Abdelwahab, S., Hamdaoui, B., Guizani, M., & Znati, T. F. (2015) · IEEE Internet of Things Journal · doi:10.1109/jiot.2015.2497263 · Cited by 72 · see citing works
5G and the Fog — Survey of related technologies and research directions
Kitanov, S., Monteiro, E., & Janevski, T. (2016) · IEEE Mediterranean Electrotechnical Conference (MELECON) · doi:10.1109/melcon.2016.7495388 · Cited by 61 · see citing works
Performance study of wireless sensor and actuator networks in forest fire scenarios
Kułakowski, P., Calle, E., & Marzo, J. L. (2012) · International Journal of Communication Systems · doi:10.1002/dac.2311 · Cited by 57 · see citing works
ME-VoLTE: Network functions for energy-efficient video transcoding at the mobile edge
Beck, M. T., Feld, S., Fichtner, A., Linnhoff–Popien, C., & Schimper, T. (2015) · International Conference on Intelligence in Next Generation Networks · doi:10.1109/icin.2015.7073804 · Cited by 55 · see citing works
Access control for SDN controllers
Klaedtke, F., Karame, G., Bifulco, R., et al. (2014) · doi:10.1145/2620728.2620773 · Cited by 53 · see citing works
Takahashi, N., Tanaka, H., & Kawamura, R. (2015) · IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) · doi:10.1109/mobilecloud.2015.23 · Cited by 49 · see citing works
De, D. (2016) · Chapman & Hall/CRC eBooks · doi:10.1201/b19208-9 · Cited by 49 · see citing works
Mobile edge clouds for Information-Centric IoT services
Borgia, E., Bruno, R., Conti, M., Mascitti, D., & Passarella, A. (2016) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc.2016.7543776 · Cited by 47 · see citing works
Opportunistic Peer-to-Peer Mobile Cloud Computing at the Tactical Edge
Gao, W. (2014) · IEEE Military Communications Conference (MILCOM) · doi:10.1109/milcom.2014.265 · Cited by 45 · see citing works
A survey on smart grid metering infrastructures: Threats and solutions
Mahmud, R., Vallakati, R., Mukherjee, A., Ranganathan, P., & Nejadpak, A. (2015) · IEEE International Conference on Electro Information Technology · doi:10.1109/eit.2015.7293374 · Cited by 40 · see citing works
5GTN: A test network for 5G application development and testing
Piri, E., Ruuska, P., Kanstrén, T., Mäkelä, J., Korva, J., Hekkala, A., Pouttu, A., Liinamaa, O., Latva‐aho, M., Vierimaa, K., et al. (2016) · European Conference on Networks and Communications · doi:10.1109/eucnc.2016.7561054 · Cited by 37 · see citing works
From IoT big data to IoT big services
Taherkordi, A., Eliassen, F., & Horn, G. (2017) · ACM Symposium on Applied Computing · doi:10.1145/3019612.3019700 · Cited by 37 · see citing works
Self-citationManaging mobile cloud computing considering objective and subjective perspectives
Marotta, M. A., Faganello, L. R., Schimuneck, M., Granville, L. Z., Rochol, J., & Both, C. B. (2015) · Computer Networks · doi:10.1016/j.comnet.2015.09.040 · Cited by 36 · see citing works
Cloudlets Authentication in NFC-Based Mobile Computing
Bouzefrane, S., Mostefa, A. F. B., Houacine, F., & Cagnon, H. (2014) · IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) · doi:10.1109/mobilecloud.2014.46 · Cited by 35 · see citing works
Multi-objective optimization model for seamless application execution in mobile cloud computing
Ahmed, E., Khan, S., Yaqoob, I., Gani, A., & Salim, F. (2013) · International Conference on Information and Communication Technologies · doi:10.1109/icict.2013.6732790 · Cited by 22 · see citing works
Case of ARM emulation optimization for offloading mechanisms in Mobile Cloud Computing
Shuja, J., Gani, A., Naveed, A., Ahmed, E., & Hsu, C. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.05.037 · Cited by 22 · see citing works
Swetha, G. R., Prathima, S., & Kalaivani, S. (2018) · Cited by 18 · see citing works
Extended Privacy in Crowdsourced Location-Based Services Using Mobile Cloud Computing
Abdo, J. B., Bourgeau, T., Demerjian, J., & Chaouchi, H. (2016) · Mobile Information Systems · doi:10.1155/2016/7867206 · Cited by 17 · see citing works
A cloudlet architecture using mobile devices
El-Barbary, A. E.-H. G., El-Sayed, L. A. A., Aly, H. H., et al. (2015) · doi:10.1109/aiccsa.2015.7507145 · Cited by 13 · see citing works
Performance Metrics of Local Cloud Computing Architectures
Brummett, T., Sheinidashtegol, P., Sarkar, D., et al. (2015) · IEEE International Conference on Cyber Security and Cloud Computing (CSCloud) · doi:10.1109/cscloud.2015.61 · Cited by 10 · see citing works
Data-Centric IoT Services Provisioning in Fog-Cloud Computing Systems
Taherkordi, A., & Eliassen, F. (2017) · ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI) · doi:10.1145/3054977.3057295 · Cited by 9 · see citing works
Self-citationMisra, R., Panda, B., & Tiwary, M. (2016) · International Conference on Information and Communication Technology for Competitive Strategies (ICTCS) · doi:10.1145/2905055.2905099 · Cited by 7 · see citing works
Poster Abstract: Data-centric IoT Services Provisioning in Fog-Cloud Computing Systems
Taherkordi, A., & Eliassen, F. (2017) · The Internet of Things · Cited by 6 · see citing works
Self-citationPerformance for Radio Access Network in mobile backhaul network
Park, C.-K. (2012) · 한국인터넷방송통신학회 논문지 · doi:10.7236/jiwit.2012.12.6.297 · Cited by 3 · see citing works
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Lim, W. Y. B., Luong, N. C., Hoang, D. T., Jiao, Y., Liang, Y.-C., Yang, Q., Niyato, D., & Miao, C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2986024 · Cited by 2,565 · see citing works
All one needs to know about fog computing and related edge computing paradigms: A complete survey
Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2019.02.009 · Cited by 1,368 · see citing works
Blockchain for internet of things: a survey
Dai, H.-N., Zheng, Z., & Zhang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2920987 · Cited by 1,246 · see citing works
Self-citationZhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039359 · Cited by 774 · see citing works
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Imteaj, A., Thakker, U., Wang, S., Li, J., & Amini, M. H. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3095077 · Cited by 774 · see citing works
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, S. J., Sharma, S. K., Wyne, S., Patwary, M. N., & Asaduzzaman, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909490 · Cited by 658 · see citing works
Yin, X., Zhu, Y., & Hu, J. (2022) · ACM Computing Surveys · doi:10.1145/3460427 · Cited by 638 · see citing works
Enabling technologies for fog computing in healthcare IoT systems
Mutlag, A. A., Abd Ghani, M. K., Arunkumar, N., Mohammed, M. A., & Mohd, O. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.07.049 · Cited by 590 · see citing works
Resource Scheduling in Edge Computing: A Survey
Luo, Q., Hu, S., Li, C., Li, G., & Shi, W. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3106401 · Cited by 588 · see citing works
“The three-tier architecture is a widely popular and accepted paradigm by many existing works [7], [10], [24], [26], [30].”
BackgroundData security and privacy-preserving in edge computing paradigm: survey and open issues
Zhang, J., Chen, B., Zhao, Y., Cheng, X., & Hu, F. (2018) · IEEE Access · doi:10.1109/access.2018.2820162 · Cited by 514 · see citing works
Survey on Multi-Access Edge Computing Security and Privacy
Ranaweera, P., Jurcut, A. D., & Liyanage, M. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3062546 · Cited by 356 · see citing works
A Survey on Task Offloading in Multi-access Edge Computing
Islam, A., Debnath, A., Ghose, M., & Chakraborty, S. (2021) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2021.102225 · Cited by 271 · see citing works
Deep learning for edge computing applications: A State-of-the-Art survey
Wang, F., Zhang, M., Wang, X., Ma, X., & Liu, J. (2020) · IEEE Access · doi:10.1109/access.2020.2982411 · Cited by 259 · see citing works
Edge computing: current trends, research challenges and future directions
Carvalho, G., Cabral, B., Pereira, V., & Bernardino, J. (2021) · Computing · doi:10.1007/s00607-020-00896-5 · Cited by 223 · see citing works
Learning-Based Privacy-Aware Offloading for Healthcare IoT With Energy Harvesting
Min, M., Wan, X., Xiao, L., Chen, Y., Xia, M., Wu, D., & Dai, H. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2875926 · Cited by 213 · see citing works
Ahmad, S., Shakeel, I., Mehfuz, S., & Ahmad, J. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2023.100568 · Cited by 197 · see citing works
Deep Reinforcement Learning based Resource Allocation in Low Latency Edge Computing Networks
Yang, T., Hu, Y., Gursoy, M. C., Schmeink, A., & Mathar, R. (2018) · 2018 15th International Symposium on Wireless Communication Systems (ISWCS) · doi:10.1109/iswcs.2018.8491089 · Cited by 156 · see citing works
Zhang, W., Zhang, Z., Zeadally, S., Chao, H.-C., & Leung, V. C. M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2897001 · Cited by 114 · see citing works
Software-Defined Networking Enhanced Edge Computing: A Network-Centric Survey
Wang, A., Zha, Z., Guo, Y., & Chen, S. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2924377 · Cited by 63 · see citing works
EasiEdge: A Novel Global Deep Neural Networks Pruning Method for Efficient Edge Computing
Yu, F., Cui, L., Wang, P., Han, C., Huang, R., & Huang, X. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3034925 · Cited by 58 · see citing works
Zhang, D., Yu, F. R., & Yang, R. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3110591 · Cited by 45 · see citing works
Liu, B., Luo, Z., Chen, H., & Li, C. (2022) · IEEE Access · doi:10.1109/access.2022.3176106 · Cited by 36 · see citing works
Distributed Online Learning of Fog Computing Under Nonuniform Device Cardinality
Ren, C., Lyu, X., Ni, W., Tian, H., & Liu, R. P. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2867481 · Cited by 22 · see citing works
Mobile-kube: mobility-aware and energy-efficient service orchestration on kubernetes edge servers
Ghafouri, S., Karami, A., Bakhtiarvan, D. B., Bigdeli, A. S., Gill, S. S., & Doyle, J. (2022) · 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC) · doi:10.1109/ucc56403.2022.00019 · Cited by 20 · see citing works
Optimal Computational Power Allocation in Multi-Access Mobile Edge Computing for Blockchain
Wu, Y., Chen, X., Shi, J., Ni, K., Qian, L., Huang, L., & Zhang, K. (2018) · Sensors · doi:10.3390/s18103472 · Cited by 20 · see citing works
Li, Y., & Li, L. (2024) · 2024 7th World Conference on Computing and Communication Technologies (WCCCT) · doi:10.1109/wccct60665.2024.10541511 · Cited by 14 · see citing works
Smart Anomaly Detection Using Data-Driven Techniques in IoT Edge: A Survey
Manokaran, J., & Vairavel, G. (2022) · Lecture Notes in Electrical Engineering · doi:10.1007/978-981-16-8862-1_45 · Cited by 13 · see citing works
Quantized Reservoir Computing on Edge Devices for Communication Applications
Liu, S., Liu, L., & Yi, Y. (2020) · 2020 IEEE/ACM Symposium on Edge Computing (SEC) · doi:10.1109/sec50012.2020.00068 · Cited by 5 · see citing works
- Authors
- Abbas, N., Zhang, Y., Taherkordi, A., & Skeie, T.
- Affiliations
- University of Oslo (NO)
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-02
- Volume
- 5
- Issue
- 1
- Pages
- 450-465
- ISSN
- 2327-4662 (ISSN-L)
- OpenAlex
- W2751904527
- Cited by
- 2,474
- References
- 101
- Citations by year
- 2026: 132 · 2025: 217 · 2024: 247 · 2023: 341 · 2022: 420 · 2021: 414 · 2020: 360 · 2019: 235 · 2018: 100 · 2017: 8
- FWCI
- 127.91
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Computer Networks and Communications › Caching and Content Delivery
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- mobile edge computing, 5G network architecture, low-latency services, network edge, cloud computing, wireless networks
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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