Call for papers: Parallel programming models for fog and edge computing infrastructures
In recent years, the rapid advancement in distributed computing techniques creates a significant need for parallel processing techniques. Several distributed environments such as grid computing, cloud computing, fog, and edge computing paradigms have greatly enhanced the need for parallel programming. Fog and edge computing techniques offer significant services to cloud computing infrastructures across the edge networks. This creates a perfect platform for the Internet of Things (IoT) and other applications that involve real-time interactions with the emerging source of big data. IoT device data is often evolved across the edge networks. Thus Fog computing acts as a perfect foil for the cloud computing paradigm to determine, which data has to be maintained locally and which has to be shared across the cloud servers. The use of fog computing reduces the amount of data stored across the cloud servers and assist in the provision of efficient cloud computing services. This further results in reduced network bandwidth and response time. From a security perspective, data security is effectively enhanced as the data is kept locally on the edge and not predominantly in cloud space. Also, the use of fog computing has a vital role in minimizing internet and network latencies. Some of the high-end applications of fog computing are smart and secure cities and smart grids, connected vehicles such as cars and real-time data analytics.
The technique of edge computing maintains the data near the network edge where the data was generated instead of placing the data in the cloud. In other words, edge computing can be defined as a distributed, open architecture that enables mobile and IoT technologies to have decentralized data processing capabilities. In the case of Edge computing, the data is processed by the device itself or by the localized server instead of processing it in cloud space. Edge computing plays a vital role in parallel processing models by enabling data stream acceleration, minimizing latency while processing real-time IoT data and provides instantaneous response to smart devices. Edge computing promotes efficient data processing by maintaining the data at source and also enhances security by sharing minimal data in cloud space. Though fog computing and edge computing seem to be the same, we may define fog computing as the computational paradigm which uses edge computing to maintain the data at the network edge especially at the data origin for enhanced data processing and data security.
Since both fog and edge computing are of different senses of distributed computing, parallel programming plays a significant role in emerging applications that use these distributed paradigms effectively. Also, with the impending threats to data integrity and security in the cloud environment, Fog and edge computing will play a significant role in developing highly sophisticated, secure and robust distributed applications in the near future. This special issue on “Parallel programming for Fog and Edge computing” provides a suitable and excellent platform to host novel, innovative and quality ideas and works related to promoting parallel programming usage in Fog and Edge computing. Topics of interest include but are not restricted to:
- Novel fog/edge and cloud computing dependent scientific parallel programming models
- Design and development of scientific programming models for 5G communications between Fog/Edge applications
- Advances in parallel computing paradigms for fog and edge computing infrastructures
- Role of ethical computational intelligence in fog and edge computing systems
- Functional parallel programming models for secure communication between Internet of Things (IoT) dependent fog/edge computing networks
- Programming models, paradigms and tools for Fog/Edge scientific computing
- Tools and environments for parallel programming design and analysis with fog and edge computing infrastructures
- Bio-inspired parallel algorithms for fog/edge computing systems
- Parallel algorithms models and formal verification with respect to fog and edge computing infrastructures for Internet of Things (IoT) applications
- Edge-cloud interactions and enabling parallel programming protocols
- Parallel programming models for distributed data centers, edge data analytics, edge caching
- Parallel programming approaches for performance modelling, analysis and evaluation
- Edge enabled Data optimization and management
- Developing heterogeneous edge systems
Manuscript Submission Deadline Date: 25th August, 2020
Authors Notification Date: 27th October, 2020
Revised Papers Due Date: 28th December, 2020
Final notification Date: 27th February, 2021
Dr. Oscar Sanjuan has a degree in Computer Science from the Pontifical University of Salamanca, where he also earned his Ph.D. in Computer Science Engineering, and he is Ph.D in Computer Science from Oviedo University. He has been Area Director of Software Engineering at the Pontifical University of Salamanca, lecturer and researcher at the University of Oviedo and Assistant Professor at the University Carlos III of Madrid. He has published more than 70 articles in prestigious national and international journals and conferences. He has also given more than 30 seminars and conferences in Europe and Latin America on Software Engineering. His research areas are Software Engineering, Software Agents, and Emerging Development Techniques in Video Game and Entertainment Software. He has translated and collaborated in the revision of multiple Software Engineering books, including: "C ++ Reference Manual" by BjarneStroustrub, "Reference Manual of UML ” by James Rumbaugh,“ Using UML Software Engineering with Objects and Components ” by Perdita Stevens and “ Software Engineering a practical approach ” by Roger S.Pressman among others. He has also been a Technology Advisor for “Vector Information Technologies”, a Spanish company dedicated to the development of highly qualified IT projects in the area of Internet and fleet tracking systems.
Dr. Giuseppe Fenza
Assistant Professor, Department of Business Sciences - Management & Innovation Systems / DISA-MIS, University of Salerno, Fisciano SA, Italy.
Dr.Giuseppe Fenza graduated and received the Ph.D. degree in Computer Sciences, both from the University of Salerno, Italy, in 2004 and 2009, respectively. His main research interest is the application of Computational Intelligence methods to support semantic-enabled solutions and decision making. He has many publications in Fuzzy Decision Making, Knowledge Extraction and Management, Situation and Context Awareness, Semantic Information Retrieval, Service Oriented Architecture, Ontology Engineering and Elicitation. He used the results of the research works in several application domains, like: Medical Diagnosis, Enterprise Knowledge Management, and Social Media Analytics. He is member of IEEE Computational Intelligence Society and IEEE Systems, Man, and Cybernetics Society. Recently, he is working in the field of Time-aware Knowledge Extraction and Context-aware Decision Support Systems and he is publishing some results in microblog summarization, time-aware collaborative filtering, context-aware group decision making, and so on. He passed the National Scientific Qualification Exams as Associate Professor.
Dr. Ruben Gonzalez Crespo
Professor, Department of Engineering, School of Engineering and Technology, Universidad Internacional de la Rioja (UNIR), Logroño, Spain.
Dr. Rubén González has a Ph.D. in Computer Science Engineering. Currently he is Vice Chancellor for Academic Planning and Teaching Staff of the International University of La Rioja. He is also the Founder and Chief Editor of the International Journal of Interactive Multimedia and Artificial Intelligence and Associate Editor of indexed scientific journals. He is an advisor and collaborator of the Ministry of Education, both Spanish and Colombian, in the field of quality education, mainly university. Previously he was Director of the Higher School of Engineering and Technology (ESIT), Director of the UNIR-AENOR Chair and Postgraduate Director at the Pontifical University of Salamanca, as well as in charge of the Chair of Operating Systems at the same university. He founded and directed the GISTI Research Group participating in several competitive research projects. He was a visiting professor for more than eight years at the University of Oviedo. He has published more than 180 articles in indexed journals and prestigious national and international conferences. He has given many seminars and conferences in Europe and Latin America on Project Management, Artificial Intelligence, Industry 4.0 and has received various awards related to his activity. His research focuses on Web Accessibility and Usability, Educational Technology as well as Soft Computing techniques in Artificial Intelligence. Within his Technology Transfer activities, he is an evaluator of international projects for the FECyT, SENACYT and COLCIENCIAS, among others, collaborates in different committees with AENOR, and participates as Principal Investigator in H2020 and national projects.