Heterogeneous Data-Centric Adaptive Edge-IoT-Based Technologies in Business Applications

Dear Colleagues,

This Special Issue will publish papers focusing on the business application dimensions of adaptive edge–IoT-based technologies. IoT and edge computing applications have been driving innovations and competitiveness in many business establishments the world over. The technology is slowly becoming a mainstay of contemporary business innovations. This Special Issue (SI) focuses on the whole array of research directions on edge computing with a special interest in data-centric technologies as applied in business environments.

Edge computing enables remote computational tasks in a connected mesh network where location and access transparency is guaranteed, enabling the execution of computing applications and data storage at endpoints. Edge computing has resulted in the optimal usage of network resources such as bandwidth and latency, thereby contributing to the commercial cost-effective computation of organizational data or information resources. This SI is an opportunity for both established and emerging researchers to share their practice or research experiences with multi-dimensional perspectives on fog computing with a focus on its applicability to business. 

Many researchers around the world have studied different aspects of edge computing in light of the rapid development of the Internet of Everything (IoE). Some have focused on the design of technology solutions, some have looked at the design and deployment principles, coming up with different frameworks, and others have considered the institutional and policy dimensions within their different business environments. In order to understand the applicability of fog computing in real environments, developing mathematical models for edge computing will open up opportunities that will challenge edge innovation spaces and stereotypes. Lightweight, loosely coupled technology designs are desired so as to achieve dynamic scalability in edge computing. 

Despite the inventory of existing work in fog computing, the editor still believes that a lot of groundbreaking research can be achieved, especially in the areas of designing topologies and information architectures to enable and its applicability in business. There is very limited seminal work on applications of fog computing worldwide. Although not focusing ultimately on fog computing, only Prof Yang Yang of Shanghai Institute of Fog Computing Technology (SHIFT) and Prof Satyanarayanan, a professor at Carnegie Mellon University, have noticeable track records in far-reaching fog computing research and its applications in business. Other notable contributors include the Chinese Academy of Sciences, Huawei, and the Shenyang Institute of Automation who proposed the Edge Computing Reference Frame 3.0. Another reference model is EdgeX Foundry architecture, which would make sense once applied in defined contextual settings. In addition to the aforementioned innovations, Open Space architecture has emerged as a promising design reference point emanating from collective effort of researchers. Other influential personalities in edge computing include David Linthicum (Deloitte), Jeff Bar (AWS), Sandy Carter (AWS), Ashley Willis (Microsoft Azure), Joe Speed (Apex.AI), and others.

Given the above, I would like to open up publication opportunities in the different aspects of edge computing focusing on its applicability to business. Although not exhaustive, the following will be considered:

• Business process automation
• Smart Mobility and IoT applications
• IoT applications in business
• The Intelligent Edge and its applications
• End nodes mobility management
• Machine learning for Edge
• Adaptive and resistive Edge
• Hybrid mathematical modeling of IoT applications (e.g., Markov Chains, Fault Tree, Petri Nets)
• Smart health systems (e.g., In-hospital patient monitoring)
• Data-driven agriculture
• Complex networks and agent-based models
• Vehicle-to-vehicle communications (IoCV, IoV, V2X, VANET)
• Geolocation-aware data distribution
• Mobility and Resource Management
• Edge Network Expandability and Scalability
• Fog computing augmentation architecture
• Hybrid models for info-centric IoT
• Open distributed Smart Edge
• Design of vehicular computing models and architectures
• Dynamic urban surveillance
• IoT predictive data analytics
• Architectural specifications for design of multi-channel sensor distributed networks.

Prof. Dr. Kelvin Joseph Bwalya
Guest Editor

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• edge computing in business
• IoT mathematical modeling
• mobility and supply chain
• IoT
• predictive maintenance
• autonomous vehicles