Efficient management of resources in Cloud/Fog computing environments

The explosion of end user devices connected to the Internet experienced in the last few years has motivated the necessity to move computing and storage closer to them. This fact has led to coining the paradigm of fog computing. Fog computing, and the likes such as edge or mist computing, allows for bandwidth savings and reducing latencies to/from the cloud, and can be used as an extension of the cloud for a wide range of latency-sensitive applications. Thus, fog computing can be described as an intermediate layer between end user devices and the cloud.

There are different strategies to implement this layer, from integrating computing capabilities within network equipment to establish micro-datacenters close to the things, or to harness low-cost devices such as Single-Board Computers (SBC) (e.g. Raspberry Pi). In any case, there is usually limited storage and computing capabilities, especially when compared to the virtually infinite resource availability of cloud platforms. Also, different applications with different requirements will coexist. Each of these applications should be isolated from the others for security reasons but also to provide them with their required Quality of Service (QoS). Light virtualization technologies such as containers can be harnessed to this end. As a result, orchestration to track and manage the life cycle of containers becomes a key element within the fog layer. Previous work of the people involved in this research topic on resource management in Grids and Cloud environments has evolved into the current research efforts in fog environments. Strategies such as reservation in advance, predictions and estimations on system performance are harnessed to achieve the pursued goals.  Moreover, the research team addresses the management of decentralized fog systems based on the use of blockchain technology to make the system more resilient to failures and attacks.


  • Orchestration of virtualized computational resources in fog architectures using blockchain technology.

  • Efficient support for intelligence applications at the edge by integrating hardware accelerators.

Relevant Publications:

  • Carmen Carrión, Kubernetes Scheduling: Taxonomy, ongoing issues and challenges. ACM Computing Surveys. Just Accepted (May 2022). https://doi.org/10.1145/3539606 Impact Index: JCR 2021: 14.324 (Q1 in “COMPUTER SCIENCE, THEORY & METHODS).
  • Carlos Núñez-Gómez; Blanca Caminero; Carmen Carrión. HIDRA: A Distributed Blockchain-Based Architecture for Fog/Edge Computing Environments. IEEE Access. 9, pp. 75231 – 75251. IEEE, 2021. DOI: 10.1109/ACCESS.2021.3082197 Impact Index: JCR 2021: 3.476 (Q2 en “COMPUTER SCIENCE, THEORY & METHODS”, Q2 en “ENGINEERING, ELECTRICAL & ELECTRONIC” y Q2 en “TELECOMMUNICATIONS”).
  • Giovanny Mondragón-Ruiz; Alonso Tenorio-Trigoso; Manuel Castillo-Cara; M. Blanca Caminero; M. Carmen Carrión. An Experimental Study of Fog and Cloud Computing in CEP-based Real-Time IoT Applications. Journal of Cloud Computing-Advances Systems and Applications. 10 – 1, pp. 1 – 17. Springer Open, 07/06/2021. DOI: 10.1186/s13677-021-00245-7 Impact Index: JCR 2021: 3.418 (Q2 en “COMPUTER SCIENCE, INFORMATION SYSTEMS”).
  • Alonso Tenorio ;Manuel Castillo-Cara; M. Blanca Caminero; M. Carmen Carrión.  An Analysis of Computational Resources of Event-Driven Streaming Data Flow for Internet of Things: A case study. The Computer Journal. 2021. DOI: 10.1093/comjnl/bxab143 Impact Index: JCR 2021: 1.762 (Q3 en “COMPUTER SCIENCE, THEORY & METHODS”).
  • Selome K. Tesfatsion; Julio Proaño; Blanca Caminero; Luis Tomás; Carmen Carrion; Johan Tordsson. Power and Performance Optimization in FPGA-accelerated Clouds. Concurrency and Computation: Practice and Experience. 30 – 18, pp. 0 – 12. John Wiley & Sons Ltd, 2018. DOI: https://doi.org/10.1002/cpe.4526

Relevant Projects:

  • Techniques to improve the architecture of servers, applications and services.
    We develop research on chip-multicore architecture and on-chip networks, aiming at increasing performance, reducing power consumption, increasing reliability by means of providing fault-tolerance support, increasing flexibility through virtualization techniques, and reducing silicon area.
  • Enhancement of the architecture of servers, services and applications.TIN2012-38341-C04-04 (MINECO). 2013-2016.

PhD Thesis:

  • Julio Proaño, “Proposals for Efficient Management of FPGAs within Cloud Computing Environments”, May 2017.
  • Francisco J. Conejero, “QoS improvement within distributed environments through the use of SLAs”, October 2014.
  • Luis Tomás, “Improving Quality of Service in Grids Through Meta-Scheduling in Advance”, February 2012.
  • Agustín C. Caminero, “Proposals for Enhancing the Provision of Quality of Service in Grids”, May 2009.


Carmen Carrión, PhD
Associate Professor
Phone number: +34 967 592 00 – Ext. 2414
Email: carmen.carrion@uclm.es iD icon dblp.icon.18x18
  Mª Blanca Caminero, PhD
Associate Professor
Phone number: +34 967 592 00 – Ext. 2411
Email: mariablanca.caminero@uclm.es iD icon dblp.icon.18x18
Personal web: blog.uclm.es/mariablancacaminero
Carlos Núñez Gómez
PhD student
Email: Carlos.Nunez@uclm.es
Research: Blockchain technologies in Fog Computing environments