Managing Guest Editor
Mohammad Mehedi Hassan (Managing Guest Editor), King Saud University, Riyadh Saudi Arabia (firstname.lastname@example.org)
Md. Rafiul Hassan, King Fahd University of Petroleum & Minerals, Saudi Arabia (email@example.com)
Victor Hugo C. de Albuquerque, Universidade de Fortaleza, Brazil, (firstname.lastname@example.org)
Witold Pedrycz (IEEE Fellow), University of Alberta, Canada (email@example.com)
Aims and Scope
Intelligent edge, i.e. the integration of edge computing with digital technologies such as artificial intelligence (AI), machine learning (ML), data analytics, big data and cloud computing, is seen as a major step towards the new revolution in the Internet-of-things (IoT) domain. Intelligent edge can be used for intelligently investigating, collecting, storing and processing the large amounts of IoT data to maximize the potential of data analytics and decision making in real time with minimum delay. In addition, intelligent edge system will not only reduce bandwidth consumption and improve response time, but can also cope with unpredictable and imprecise issues such as mobility, security, and reliability.
Many of the technologies that can enable the transformation towards intelligent edge system fall within the domain of soft computing (SC), where the aim is to achieve tractability, robustness and low-cost solutions. It has been anticipated that by 2025, edge device shipments driven by artificial intelligence and SC techniques will rise from 161.4 million units to 26 billion units globally. In terms of unit quantities, the top AI and SC driven edge devices will include smartphones, PC/tablets, intelligent speakers, automotive sensors, head-mounted displays, robots for businesses and consumers, drones, and security cameras.
Soft computing methodologies can use a combination of heuristics, approximation models, stochastic and non-deterministic algorithmic behavior to address various challenges in edge computing such as data accumulation, mobility, Interoperability and security. Edge-based SC can provide more prominent privacy and security in IoT network by processing the data at the source. Moreover, edge-based SC can be exceptionally flexible and adaptable. Smart devices can help to develop location-specific or industry-specific requirements ranging from medical monitoring to energy management. Furthermore, edge-based SC can offer superior experiences for customers. SC can help companies to build trust and relationship with their clients by allowing responsiveness through different services, e.g. location-aware services, or rerouting travel plans in the case of delays.
Topics of Interest
This special issue targets an audience of researchers, academics and industries from different communities to share and exchange new ideas, approaches, theories and practice of using Soft Computing techniques to resolve the challenging issues associated with the leveraging of intelligent edge paradigm in IoT environment. Therefore, the suggested topics of interest for this special issue include, but are not limited to:
Novel network architecture and optimization method for SC applications in edge paradigm
SC for efficient Big data analysis and diagnosis in edge computing
Nature-inspired hybrid SC methods for intelligence edge paradigm
SC for mobility, interoperability and context management in edge computing
SC-based networking and communication protocols for edge computing
Container based approach to implement SC in edge systems
Novel deep-learning approaches for edge computing applications and services
SC-enabled computation offloading in edge computing paradigm
SC for trust, security and privacy management in edge system
Swarm Intelligence based algorithms for edge system
Benchmarking SC and ML workloads and/or frameworks on the edge
Evolutionary algorithms for QoS/ QoE management in edge platform
SC for autonomic resource management in edge computing
Software and simulation platform for SC in edge paradigm
SC for cognitive edge computing systems
Opens for submission: 1st August, 2020.
Deadline for paper submission: 15th December, 2020.
Notification of results: 2-3 months after submission.
Final acceptance: August 30, 2021
Paper submissions for the special issue should follow the submission format and guidelines for regular papers and submitted at https://ees.elsevier.com/asoc. All the papers will be peer-reviewed following Applied Soft Computing reviewing procedures. Guest editors will make an initial assessment of the suitability and scope of all submissions. Papers will be evaluated based on their originality, presentation, relevance and contributions, as well as their suitability to the special issue. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review. Authors should select “VSI: SC for Intelligent Edge” when they reach the “Article Type” step in the submission process. The submitted papers must propose original research that has not been published nor currently under review in other venues.