Manuscript Topics

Aims: Data-driven computing and edge Computing possesses immense scope of research to overcome today’s scenario problem to ease human lives and benefit society. The issue related to storage and computation occurs because of the rapid advancement in technology. High-speed computing, gigantic storage, powerful computation, energy-efficient and robust information processing techniques are the required features for the progression in technology like IoT (Internet of Things) and smart city service. Edge Computing based on big data is highly potential and feasible to solve the challenging real-time big data IoT systems. IoT devices continuously producing big data to handle big data, providing a high quality of service, and ensuring security and privacy bring significant barriers to the IoT. To solve these challenges, Data-driven Edge Computing (DEC) is used to perform distributed data and storage processing.

For a heterogeneous network, resource allocation and scheduling is a challenging and complex task. By deploying data-driven AI approaches in edge computing to optimize resource allocation, scheduling, routing, and control, we can ease the above difficulties. However, edge computing overcomes the burden of network traffic, scalability, latency, and so on. A well-defined framework, protocols are lacking, security and privacy-related issues, and the data wastage problem need to be solved in edge computing. Efficiently handle big data and information processing problems within a feasible time, AI (Artificial Intelligence)-driven edge computing receives immense interest among academia, research, and industry. Biomedical devices, intelligent healthcare systems, autonomous drones and vehicles, smart-home and environment monitoring, and many applications use IoT and edge computing to enhance the quality of human life and smart city service.

Scope: Data-driven approach such as artificial intelligence empowered edge computing to provide solutions for big data in IoT and bears an enormous scope across various disciplines. This special issue addresses the Data-driven Edge Computing recent progress and development concern to the theoretical and practical for IoT, and Smart City applications. This special issue aims to collect potential works in a new paradigm, frameworks, protocols, innovative solutions to the research issues, and state-of-the-art and hybrid models in edge computing to tackle IoT, big data processing for Smart City. Creative ideas are most welcome to solve the emerging and futuristic challenges.

The focus of the special issue will be on a broad range; the list of possible potential topics includes, but is not limited to, the following:
• Architectures, paradigm, and protocols for Data-Driven edge computing in IoT
• Cloud Computing and Parallel Processing for Smart City
• Intelligent Hybrid Systems for IoT and Smart City
• Challenges, opportunities and future perspectives in Data-driven Edge Computing for Smart City
• The solution to solve complex real-world problems using Edge Computing
• Human-centric Cognitive Informatics
• Data-driven Multimedia Computing for Smart Media Service
• Data-driven Biomedical Applications for Smart HealthCare
• Advances in Parallel and Distributed Data Processing
• AI-based Mobile Edge Computing for Personal IoT Services
• Energy-efficient Edge Computing for IoT and Smart City
• Solution to security and privacy policy issues in Edge Computing and Smart City

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