Journal
Discover Internet of Things
Discover Internet of Things is an open access journal publishing research across all fields relevant to the Internet of Things (IoT), providing cutting-edge findings to researchers,...
Pervasive Edge Computing (PEC) is an emerging paradigm that seems to be imperative to conclude the convergence of the Edge Computing and Internet of Things to support pervasive applications very close to end users. IoT has pervaded our daily life by making things, interconnected through the Internet, smarter, distributed and more autonomous. The emerging development of intelligent & pervasive applications in IoT has now started to gain significant attention. Cloud provides many benefits to IoT devices, including high-performance computing, a storage infrastructure, processing, and analysis of large-scale data giving to IoT the opportunity to be robust, smart, and self-configuring. The forthcoming emergence of PEC extends the capabilities of the ‘legacy’ IoT, its potentials, the number of devices and the volumes of data. However, Cloud technologies face some accessibility challenges when providing services to end-users. For instance, mobile clients can move among different places, yet require Cloud services with minimum cost and short response time. The unstable connection between Cloud and mobile devices is expected to prevent providers from achieving the optimal performance. To cope with these limitations, we aspire that Edge Computing converged with IoT environments materializes the desired PEC ubiquitous intelligence in real eco-systems. We then need additional effort to establish and deliver the convergence of Edge and IoT in formatting the future PEC. PEC is envisioned to involve numerous autonomous & distributed computing and AI-driven entities capable of understanding their internal status (context), the status of their environment and peers (collaborative context) and take timely optimized actions to efficiently serve modern pervasive applications.
Keywords: Theoretical Foundation of Pervasive Edge Computing; Computational Intelligence & IoT; Distributed AI in IoT; Intelligent Data & Tasks Management in IoT; Bio-inspired Computing & IoT; Collective Intelligence & IoT; Context-aware IoT
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Christos Anagnostopoulos
Dr. Christos Anagnostopoulos, University of Glasgow, UK Dr Anagnostopoulos is an Associate Professor in Distributed Computing & Data Engineering Systems, School of Computing Science, University of Glasgow, UK. His research expertise is at the intersection of large-scale distributed computing systems and statistical machine learning at the Edge. -
Kostas Kolomvatsos
Dr. Kostas Kolomvatsos, University of Thessaly, Greece Dr Kolomvatsos is an Assistant Professor in the Department of Computer Science & Telecommunications, University of Thessaly, Greece. He is the founder of the Intelligent Pervasive Systems, University of Thessaly. His research interests are in the definition of Intelligent Systems adopting Machine Learning, Computational Intelligence and Soft Computing for Pervasive Computing, Distributed Systems, Internet of Things, and Edge/Cloud Computing.
