Editorial: Scalable and Dynamic Big Data Processing and Service Provision in Edge Cloud Environments


  • In-Young Ko Korea Advanced Institute of Science and Technology, South Korea
  • Abhishek Srivastava Indian Institute of Technology Indore, India
  • Michael Mrissa InnoRenew CoE, University of Primorska, Slovenia


Scalable and Dynamic Big Data Processing, Service Provision in Edge Cloud Environments


Owing to the exponential growth of connected devices and the large amounts of data produced by such devices, clouds are becoming a bottleneck and cause latency while collecting and processing data and providing associated services [1]. The concept of edge computing has been suggested to solve this scalability problem by moving data centers and computing resources close to the data sources [2]. Locally deployed data centers and computing resources form an edge cloud or a fog that can collect and process big data in a distributed and scalable manner [3]. Recently, low-latency and reliable communication technologies such as 5G have enabled more effective realization of edge cloud environments [4].
Edge clouds are especially useful for efficient, reliable, and secure data collection and processing for smart cities and smart factories [5]. Figure 1 shows an overview of big data-driven service provision in a smart city environment. In this environment, edge devices such as cars and sensors on roads collect data and accumulate them in nearby edge clouds. Then, the services running on an edge cloud process them locally and provide localized service capabilities to nearby users. Such services can be dynamically deployed to edge clouds according to user needs and various environmental contexts.


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Shaukat Ali, Ferruccio Damiani, Schahram Dustdar, Marialuisa Sanseverino, Mirko Viroli, and Danny Weyns. Big data from the cloud to

the edge: the aggregate computing solution. In Proceedings of the 13th European Conference on Software Architecture – Volume 2 (ECSA ’19), Association for Computing Machinery, New York, NY, USA, 177–180, 2019.

Ejaz Ahmed, Arif Ahmed, Ibrar Yaqoob, Junaid Shuja, Abdullah Gani, Muhammad Imran, and Muhammad Shoaib. Bringing computation closer toward the user network: Is edge computing the solution? IEEE Communications Magazine, 55(11):138–144, 2017.

Ashkan Yousefpour, Caleb Fung, Tam Nguyen, Krishna Kadiyala, Fatemeh Jalali, Amirreza Niakanlahiji, Jian Kong, Jason P. Jue. All one needs

to know about fog computing and related edge computing paradigms: A complete survey. Journal of Systems Architecture, Volume 98, Pages

–330, 2019.

Anselme Ndikumana, Nguyen H. Tran, Tai Manh Ho, Zhu Han, Walid Saad, Dusit Niyato, and Choong Seon Hong. Joint Communication,

Computation, Caching, and Control in Big Data Multi-Access Edge Computing IEEE Transactions on Mobile Computing, 19(6):1359–1374,

Nouha Kherraf, Sanaa Sharafeddine, Chadi M. Assi, and Ali Ghrayeb. Latency and Reliability-Aware Workload Assignment in IoT Networks

With Mobile Edge Clouds. IEEE Transactions on Network and Service Management, 16(4):1435–1449, 2019.




How to Cite

Ko, I.-Y. ., Srivastava, A. ., & Mrissa, M. . (2021). Editorial: Scalable and Dynamic Big Data Processing and Service Provision in Edge Cloud Environments. Journal of Web Engineering, 21(01), v-ix. Retrieved from https://journals.riverpublishers.com/index.php/JWE/article/view/12523