A Research Perspective on Fog Computing

State-of-the-art applications are typically deployed on top of cloud services which offer the illusion of infinite resources, elastic scalability, and a simple pay-per-use billing model. While this is very convenient for developers, it also comes with relatively high access latency for end users. Future application domains such as the Internet of Things, autonomous driving, or future 5G mobile apps, however, require low latency access which is typically achieved by moving computation towards the edge of the network. This natural extension of the cloud towards the edge is typically referred to as Fog Computing and has lately found a lot of attention. However, Fog Computing as a deployment platform has not yet found widespread adoption; this, we believe, could be helped through a consistent use of the service-oriented computing paradigm for fog infrastructure services. Based on this motivation, this paper describes the concept of Fog Computing in detail, discusses the main obstacles for Fog Computing adoption, and derives open research challenges.

[1]  Yogesh L. Simmhan,et al.  Demystifying Fog Computing: Characterizing Architectures, Applications and Abstractions , 2017, 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC).

[2]  Raluca Diaconu,et al.  Big ideas paper: Policy-driven middleware for a legally-compliant Internet of Things , 2016, Middleware.

[3]  David Bermbach,et al.  Benchmarking Eventual Consistency: Lessons Learned from Long-Term Experimental Studies , 2014, 2014 IEEE International Conference on Cloud Engineering.

[4]  Rajkumar Buyya,et al.  Fog Computing: Helping the Internet of Things Realize Its Potential , 2016, Computer.

[5]  Weisong Shi,et al.  The Promise of Edge Computing , 2016, Computer.

[6]  Randy H. Katz,et al.  Above the Clouds: A Berkeley View of Cloud Computing , 2009 .

[7]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.

[8]  Ivan Stojmenovic,et al.  An overview of Fog computing and its security issues , 2016, Concurr. Comput. Pract. Exp..

[9]  David Bermbach,et al.  Benchmarking Web API Quality , 2016, ICWE.

[10]  Prashant J. Shenoy,et al.  SpotLight: An Information Service for the Cloud , 2016, 2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS).

[11]  David Bermbach,et al.  Cloud Service Benchmarking - Measuring Quality of Cloud Services from a Client Perspective , 2017 .

[12]  David Bermbach,et al.  Pick your choice in HBase: Security or performance , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[13]  Stefan Tai.  Continuous, Trustless, and Fair: Changing Priorities in Services Computing , 2016, ESOCC Workshops.

[14]  Manuel Díaz,et al.  State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing , 2016, J. Netw. Comput. Appl..

[15]  Kim-Kwang Raymond Choo,et al.  Challenges of Connecting Edge and Cloud Computing: A Security and Forensic Perspective , 2017, IEEE Cloud Computing.

[16]  Andrzej Kamiński,et al.  Nowe zagrożenia dla działalności przedsiębiorstw w świetle rozporządzenia Parlamentu Europejskiego o ochronie danych osobowych (RODO) , 2017 .

[17]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[18]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[19]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[20]  David Bermbach,et al.  Evidence-based security configurations for cloud datastores , 2017, SAC.