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Cognitive Cloud: The Definition

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Distributed Computing and Artificial Intelligence, 19th International Conference (DCAI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 583))

Abstract

Cognitive Cloud has drawn increasing attention from practitioners, academics, and funding agencies and has been adopted progressively. However, the concept remains mired in various definitions with different studies providing contrasting descriptions. Therefore, to understand the concept of cognitive cloud and to provide its definition, in this work we conduct a systematic mapping study of the literature investigating 24 papers proposing five main definitions. The main outcome of this work is a complete definition that merges all the common aspects of cognitive cloud, enabling practitioners and researchers to better understand what cognitive cloud is.

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Notes

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    IEEEXplore Digital Library https://ieeexplore.ieee.org/.

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Author information

Authors and Affiliations

  1. Tampere University, Tampere, Finland

    Sergio Moreschini, Fabiano Pecorelli, Xiaozhou Li, Sonia Naz, David Hästbacka & Davide Taibi

  2. Aalborg University, Aalborg, Denmark

    Michele Albano

  3. University of Oulu, Oulu, Finland

    Davide Taibi

Authors
  1. Sergio Moreschini
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  2. Fabiano Pecorelli
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  3. Xiaozhou Li
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  4. Sonia Naz
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  5. Michele Albano
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  6. David Hästbacka
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  7. Davide Taibi
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Corresponding author

Correspondence to Sergio Moreschini .

Editor information

Editors and Affiliations

  1. Hiroshima University, Hiroshima, Japan

    Sigeru Omatu

  2. King Abdulaziz University, Jeddah, Saudi Arabia

    Rashid Mehmood

  3. Kielce University of Technology, Kielce, Poland

    Pawel Sitek

  4. Palazzo Camponeschi, University of L'Aquila, L'Aquila, Italy

    Serafino Cicerone

  5. BISITE, Edificio I+D+i, University of Salamanca, Salamanca, Spain

    Sara Rodríguez

Appendix A: The Selected Papers

Appendix A: The Selected Papers

[SP1]:

Georgakopoulos, A. et al. (2012). Cognitive cloud-oriented wireless networks for the Future Internet. In 2012 WCNCW (pp. 431–435). IEEE.

[SP2]:

Cai, W. et al. (2014). Environment Perception for Cognitive Cloud Gaming. In International Conference on Cloud Computing (pp. 3–13). Springer, Cham.

[SP3]:

Cai, W. et al. (2014). Resource management for cognitive cloud gaming. In 2014 ICC (pp. 3456–3461). IEEE.

[SP4]:

Cordeschi, N. et al. (2015). Reliable adaptive resource management for cognitive cloud vehicular networks. IEEE Trans. on Vehicular Tech., 64(6), 2528–2537.

[SP5]:

Shi, W. (2015). QoE guarantee scheme based on cooperative cognitive cloud and opportunistic weight particle swarm. Electrical and Computer Engineering, 2015.

[SP6]:

Baughman, A. K. et al. (2015). Disruptive innovation: Large scale multimedia data mining. In Multimedia Data Mining and Analytics (pp. 3–28). Springer, Cham.

[SP7]:

Mahmoodi, S. E. et al. (2016). A time-adaptive heuristic for cognitive cloud offloading in multi-RAT enabled wireless devices. IEEE Transactions on Cognitive Communications and Networking, 2(2), 194–207.

[SP8]:

Chiang, M., et al. (2016). Fog and IoT: An overview of research opportunities. IEEE Internet of things journal, 3(6), 854–864.

[SP9]:

Mahmoodi, S. E. et al. (2018). Cognitive Cloud Offloading Using Multiple Radios. In Spectrum-Aware Mobile Computing (pp. 23–33). Springer, Cham.

[SP10]:

Wu, X. et al. (2018). Phase-compensation-based cooperative spectrum sensing algorithm for cognitive cloud networks. In 2018 ICOIN (pp. 755–759). IEEE.

[SP11]:

Wang, L. et al. (2018). Cooperative Spectrum Sensing Algorithm Based on Phase Compensation in Cognitive Cloud Networks. ICUFN (pp. 143–147).

[SP12]:

Huang, H. et al. (2018). On the Performance of Cognitive Cloud Radio Access Networks in the Presence of Hardware Impairment. In APSIPA ASC (427–431).

[SP13]:

Marshall, T. E. et al. (2018). Cloud-based intelligent accounting applications: accounting task automation using IBM watson cognitive computing. Journal of Emerging Technologies in Accounting, 15(1), 199–215.

[SP14]:

Jann, J. et al. (2018). IBM POWER9 system software. IBM Journal of Research and Development, 62(4/5), 6–1.

[SP15]:

Kloeckner, K. et al. (2018). Building a cognitive platform for the managed IT services lifecycle. IBM Journal of Research and Development, 62(1), 8–1.

[SP16]:

Mahmoodi, S. E. et al. (2019). Time-Adaptive and Cognitive Cloud Offloading Using Multiple Radios. In Spectrum-Aware Mobile Computing (pp. 49–66).

[SP17]:

Garai, Á. et al. (2019). Revolutionizing healthcare with IoT and cognitive, cloud-based telemedicine. Acta Polytechnica Hungarica, 16(2), 163–181.

[SP18]:

Amato, F. et al. (2019). A federation of cognitive cloud services for trusting data sources. In CISIS (pp. 1022–1031).

[SP19]:

Ferrer, A. J. et al. (2021). Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms. In CCGrid (pp. 634–641).

[SP20]:

Campolo, C. et al. (2021). Virtualizing AI at the distributed edge towards intelligent IoT applications. Journal of Sensor and Actuator Networks, 10(1), 13.

[SP21]:

Vermesan, O. et al. (2021). Internet of Vehicles-System of Systems Distributed Intelligence for Mobility Applications. In Intelligent Technologies for Internet of Vehicles (pp. 93–147). Springer, Cham.

[SP22]:

Kretsis, A. et al. (2021). SERRANO: Transparent Application Deployment in a Secure, Accelerated and Cognitive Cloud Continuum. In MeditCom (pp. 55–60)

[SP23]:

Bacciu, D. et al. (2021). TEACHING-Trustworthy autonomous cyber-physical applications through human-centred intelligence. In 2021 COINS (pp. 1–6).

[SP24]:

Zhang, H. et al. (2021). Knowledge-based systems for blockchain-based cognitive cloud computing model for security purposes. International Journal of Modeling, Simulation, and Scientific Computing, 2241002.

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Moreschini, S. et al. (2023). Cognitive Cloud: The Definition. In: Omatu, S., Mehmood, R., Sitek, P., Cicerone, S., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 19th International Conference. DCAI 2022. Lecture Notes in Networks and Systems, vol 583. Springer, Cham. https://doi.org/10.1007/978-3-031-20859-1_22

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