Articles on Cloud & Pervasive Computing 

Fog / Edge Computing 

  1. Limei Peng, Ahmad R. Dhaini, Pin-Han Ho, « Toward integrated Cloud–Fog networks for efficient IoT provisioning: Key challenges and solutions », Future Generation Computer Systems, vol. 88, Nov. 2018, pp. 606-613.
    File: FGCS-vol88-2018-CloudFogIoT-Peng
  2. Richard Olaniyan, Olamilekan Fadahunsi, Muthucumaru Maheswaran, Mohamed Faten Zhani, « Opportunistic Edge Computing: Concepts, opportunities and research challenges », Future Generation Computer Systems, vol. 89, Dec. 2018, pp. 633-645.
    File: FGCS-vol89-2018-Edge-Olaniyan
  3. Yifei Zhang, Hongming Cai, Boyi Xu, Athanasios T. Vasilakos, Chengxi Huang,« Data driven business rule generation based on fog computing », Future Generation Computer Systems, vol. 89, Dec. 2018, pp.494-505.
    File: FGCS-vol89-2018-DataDrivenFog-Zhang
  4. Marcus Gomes, Miguel L. Pardal,« Cloud vs Fog: assessment of alternative deployments for a latency-sensitive IoT application », 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018), Procedia Computer Science, vol. 130, 2018, pp. 488-495.
    File : ANT2018-ProcediaCS-vol130-CloudFogLatency-Gomes.pdf
  5. M. Villari, M. Fazio, S. Dustdar, O. Rana, R. Ranjan, « Osmotic Computing: A New Paradigm for Edge/Cloud Integration », IEEE Cloud Computing, vol. 3 issue 6, 2016, pp. 76-83.
    File: IEEECloudCompVol3n6-2016-OsmoticComputing-Fog-Villari.pdf

Fog / IoT

  1. Ola Salman ; Imad Elhajj ; Ayman Kayssi ; Ali Chehab, « Edge Computing Enabling the Internet of Things », IEEE 2nd World Forum on Internet of Things (WF-IoT 2015), 14-16 Dec. 2015, Milan, Italy, pp. 603-608.
    File: WF-IoT2015-fog-IoT-Salman.pdf 
  2. Zhenyu Wen ; Renyu Yang ; Peter Garraghan ; Tao Lin ; Jie Xu ; Michael Rovatsos, « Fog Orchestration for Internet of Things Services », IEEE Internet Computing, vol. 21, no. 2, Mar.-Apr. 2017, pp. 16-24.
    File: IEEEIntComp-vol21n2-2017-FogIoT-Wen.pdf
  3. Hanan Elazhary, «Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions », Journal of Network and Computer Applications, vol. 128, Feb. 2019, pp. 105-140
    File: JNCA-vol128-2019-IoTMobilCloudEdgeSurvey-Elazhary.pdf

Cloud Adoption / Choosing Cloud Providers

  1. Ang Li ; Xiaowei Yang ; Srikanth Kandula ; Ming Zhang, « Comparing Public-Cloud Providers », IEEE Internet Computing, vol. 15, no. 2, March-April 2011, pp. 50-53.
    File: IEEEInternetComp-vol15n2-2011-CompartingCloudProviders-Yang.pdf 
  2. Takayuki Kushida ; Gopal S. Pingali, « Industry Cloud - Effective Adoption of Cloud Computing for Industry Solutions », IEEE 7th International Conference on Cloud Computing, Anchorage, US, 2014, pp. 753-760.
    File: ICCC2014-MultiCloudIndustry-Kushida.pdf
  3. Yuan Feng ; Baochun Li ; Bo Li, « Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers », IEEE Transactions on Computers, vol. 63, no. 1, Jan. 2014, pp. 59-73.
    File: IEEETransOnComp-vol63n1-2014-CloudCompetition-Feng.pdf 

Multi-Tenant Cloud

  1. Bhaskar Prasad Rimal ; Martin Maier, « Workflow Scheduling in Multi-Tenant Cloud Computing Environments », IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 1, Jan. 2017, pp. 290-304.
    File: IeeeTPDS-Vol28n1-2017-MultiCloud-Rimal
  2. David Shue, Michael J. Freedman, Anees Shaikh. « Performance isolation and fairness for multi-tenant cloud storage ». 10th USENIX conference on Operating Systems Design and Implementation (OSDI’12), 2012, USENIX Association, Berkeley, CA, USA, pp. 349-362.
    File: osdi12-MultiCloudStorage-Shue.pdf 
  3. Zhiming Shen, Sethuraman Subbiah, Xiaohui Gu, John Wilkes, « CloudScale: elastic resource scaling for multi-tenant cloud systems », 2nd ACM Symposium on Cloud Computing (SOCC ’11), 2011, ACM, New York, NY, USA, Article 5, 14 pages.
    File: SoCC2011-MultiCloudElasticity-Shen.pdf

Cloud Management / Cloud Providers 

  1. Marcus Carvalho, Daniel A. Menascé, Francisco Brasileiro, « Capacity planning for IaaS cloud providers offering multiple service classes », Future Generation Computer Systems, vol. 77, Dec. 2017, pp.97-111.
    File: FGCS-vol77-CapacityPlanningIaaS-Carvalho.pdf
  2. Emanuel Ferreira Coutinho, Flávio Rubens de Carvalho Sousa, Paulo Antonio Leal Rego, Danielo Gonçalves Gomes, José Neuman de Souza, « Elasticity in cloud computing: a survey », Annals of Telecommunications, vol. 70, issue 7-8, 2014, pp. 289–309. 
    File: AnnTelecom-Vol70n7-8-2014-CloudElasticity-Coutinho.pdf
  3. Anton Beloglazov Rajkumar Buyya, « Energy Efficient Allocation of Virtual Machines in Cloud Data Centers », 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGRID 2010),17-20 May 2010, Melbourne, Australia, pp. 577-578. 
    File: CCGrid2010-EnergyEfficientVMAllocation-Beloglazov.pdf 
  4. Alireza Khoshkbarforoushha ; Meisong Wang ; Rajiv Ranjan ; Lizhe Wang ; Leila Alem, Samee U. Khan, Boualem Benatallah, « Dimensions for Evaluating Cloud Resource Orchestration Frameworks », IEEE Computer, vol 49, n° 2, Feb 2016, pp. 24 - 33. 
    File: IEEEComputer_Feb2016-CloudResourceOrch-Kosh.pdf

Containers / Performance 

  1. Bowen Ruan, Hang Huang, Song Wu, Hai Jin, « A Performance Study of Containers in Cloud Environment », In: Wang G., Han Y., Martínez Pérez G. (eds) Advances in Services Computing. APSCC 2016. Lecture Notes in Computer Science, vol 10065, Springer, pp. 343-356. 
    File: APSCC2016-PerfContainersCloud-Ruan.pdf
  2. Zhanibek Kozhirbayev, Richard O. Sinnott, « A performance comparison of container-based technologies for the Cloud », Future Generation Computer Systems, vol. 68, 2017, pp. 175-182.
    File: FGCS-vol68-2017-PerfContainer-Kozhirbayev.pdf

Microservices / Architecture

  1. Dharmendra Shadija ; Mo Rezai ; Richard Hill, « Towards an understanding of microservices », 23rd International Conference on Automation and Computing (ICAC 2017), Huddersfield, 2017, pp. 1-6.
    File: ICAC2017-MicroSrvSOA-Shadija.pdf
  2. Hugo H. O. S. da Silva, Glauco de Figueiredo Carneiro, Miguel P. Monteiro, « Towards a Roadmap for the Migration of Legacy Software Systems to a Microservice based Architecture »,  9th International Conference on Cloud Computing and Services Science (CLOSER 2019), Heraklion, Greece, May 2-4, 2019, pp. 37-47
    File: Closer2019-MigrationLegacyMicroSrv-Silva.pdf
  3. Davide Taibi, Kari Systä, « From Monolithic Systems to Microservices: A Decomposition Framework based on Process Mining », 9th International Conference on Cloud Computing and Services Science (CLOSER 2019), Heraklion, Greece, May 2-4, 2019, pp. 153-164.
    File:  CLOSER2019-MicroSrvProcMining-Taibi.pdf
  4. Armin Balalaie, Abbas Heydarnoori, Pooyan Jamshidi, « Migrating to Cloud-Native Architectures Using Microservices: An Experience Report », In: Celesti A., Leitner P. (eds) Advances in Service-Oriented and Cloud Computing. ESOCC 2015. Communications in Computer and Information Science, vol 567, Springer. pp. 201-215
    File:  CloudWay_2015_paper_2.pdf  
  5. Maxime Belair, Laniepce Sylvie, Jean-Marc Menaud, « Container interaction with host OS for enhanced security : a survey » COMPAS 2019 - Conférence d'informatique en Parallélisme, Architecture et Système, Jun 2019, Anglet, France. Available at: (Nov. 2019)
    File: COMPAS2019_paper_21.pdf
  6. Daniel Müssig, Robert Stricker, Jörg Lässig, Jens Heider, « Highly Scalable Microservice-based Enterprise Architecture for Smart Ecosystems in Hybrid Cloud Environments », 19th International Conference on Enterprise Information Systems, Volume 3, Porto, Portugal, April 26-29, 2017,SciTePress, pp. 454-459
    File: ICEIS_2017_Vol3_MicroSrvEAHybridCloud-Mussig.pdf
  7. Florian Rademacher, Sabine Sachweh, Albert Zündorf, «  A modeling method for systematic architecture reconstruction of microservice-based software systems », In: Nurcan S., Reinhartz-Berger I., Soffer P., Zdravkovic J. (eds), Enterprise, Business-Process and Information Systems Modeling, BPMDS 2020, EMMSAD 2020. Lecture Notes in Business Information Processing, vol 387. Springer, 2020, pp. 311-326.

EdgeIA / Machine Learning

  1. P. Zhang, H. Sun, J. Situ, C. Jiang and D. Xie, "Federated Transfer Learning for IIoT Devices With Low Computing Power Based on Blockchain and Edge Computing," IEEE Access, vol. 9, pp. 98630-98638, 2021, doi: 10.1109/ACCESS.2021.3095078. Available at:
    File: IEEEAccess-vol9-2021-FederatedLearningIoTBlockchainEdge-Zhang.pdf
  2. A. Aljulayfi, K. Djemame, « A Machine Learning based Context-aware Prediction Framework for Edge Computing Environments », 11th International Conference on Cloud Computing and Services Science - CLOSER 2021, pp 143-150. DOI: 10.5220/0010379001430150. Available at:
    File: CLOSER2021-ML-CtxPrediction-Edge-Aljulayfi.pdf 
  3. Farshad Firouzi, Bahar Farahani, Alexander Marinšek, "The convergence and interplay of edge, fog, and cloud in the AI-driven Internet of Things (IoT)", Information Systems, 2021,ISSN 0306-4379, DOI:
    File: InformationSystems-2021-EdgeCloud-IA-IoT-Firouzi.pdf
  4. S. Singh, R. Sulthana, T. Shewale, V. Chamola, A. Benslimane, B. Sikdar, "Machine Learning Assisted Security and Privacy Provisioning for Edge Computing: A Survey », IEEE Internet of Things Journal, 2021, doi: 10.1109/JIOT.2021.3098051.
    File: IEEEIoTJournal-2021-ML-EdgeSecurityPrivacy-Singh.pdf
  5. S. Zhu, K. Ota ,M. Dong, "Green AI for IIoT: Energy Efficient Intelligent Edge Computing for Industrial Internet of Things," IEEE Transactions on Green Communications and Networking, 2021, doi: 10.1109/TGCN.2021.3100622.
    File: IEEETransGreenCommNet-GreenAI-IoT-EnergyEfficient-Edge-Zhu.pdf
  6. F. M. Rueda, S. Lüdtke, M. Schröder, K. Yordanova, T. Kirste, G.A. Fink, “Combining Symbolic Reasoning and Deep Learning for Human Activity Recognition”. CoMoRea 2019, IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2019, pp. 22-27
    File: Comorea2019-PerComWorkshops2019-AR-DeepLearning-Rueda.pdf

Vehicular Networks / VANETS 

  1. Dorsaf Zekri, Bruno Defude, Thierry Delot. « Building, sharing and exploiting spatio-temporal aggregates in vehicular networks ». Mobile Information Systems, vol. 10, n° 3, Hindawi/IOS Press, 2014, pp.259 - 285. Available at: (Nov. 2019)
    File: MIS-vol10n3-2014-VehicularNets-Didelot 
  2. Koosha Paridel, Ansar-Ul-Haque Yasar, Yves Vanrompay, Davy Preuveneers, Yolande Berbers, « Teamwork on the road: Efficient collaboration in VANETs with context-based grouping », International Conference on Ambient Systems, Networks and Technologies (ANT-2011), Procedia Computer Science, vol. 5, 2011, Elsevier, pp. 48-57.
    File: ANT2011-Procedia-Vol5-VANETCtxDistrib-Paridel.pdf
  3. K. Hammoudi, H. Benhabiles, M. Kasraoui, N. Ajam, F. Dornaika, K. Radhakrishnan, K. Bandi, Q. Cai, S. Liu, « Developing Vision-based and Cooperative Vehicular Embedded Systems for Enhancing Road Monitoring Services », 6th International Conference on Ambient Systems, Networks and Technologies (ANT 2015), Procedia Computer Science, vol. 52, 2015, pp. 389-395.
    File: ANT2015-Procedia-vol52-VehicularRoadMonitoring-Hammoudi.pdf
  4. Paulo H. L. Rettore ; André B. Campolina ; Leandro A. Villas ; Antonio A. F. Loureiro, « A method of eco-driving based on intra-vehicular sensor data », 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, 2017, pp. 1122-1127.
    File: ISCC2017-p1118-EcoDrivingVehicularSensorData-rettore.pdf
  5. Rico Auerswald, Roman Busse, Markus Dod, Richard Fritzsche, Alexander Jungmann, Michael Klöppel-Gersdorf, Josef F. Krems, Sven Lorenz, Franziska Schmalfuß, Sabine Springer, Severin Strobl, « Cooperative Driving in Mixed Traffic with Heterogeneous Communications and Cloud Infrastructure », 5th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2019), Heraklion, Crete, Greece, May 3-5, 2019, pp. 95-105.
    File: VEHITS2019-VehicularCloud-Auerswald.pdf