Introduction to the Special Issue on Real-Time Computing in the IoT-to-Edge-to-Cloud Continuum
Article No.: 1, Pages 1 - 2
The edge computing paradigm is becoming increasingly popular as it facilitates real-time computation, reduces energy consumption and carbon footprint, and fosters security and privacy preservation by processing the data closer to its origin, thereby drastically reducing the amount of data sent to the cloud. However, some computations still need to occur in the cloud, thus connecting the IoT, the edge, and the cloud and originating the so-called IoT-to-Edge-to-Cloud Compute Continuum. Many edge applications tightly interact with the surrounding environment and are required to deliver a result (e.g., perform actuation or send a message through a 5G network) within a well-defined deadline. Therefore, a key requirement in edge computing is the need to ensure predictability when communicating across the IoT-to-Edge-to-Cloud Compute Continuum while also efficiently utilizing the system resources.
This special issue received 15 submissions, including extended versions of best-selected papers from the 1st International Workshop on Real-time And intelliGent Edge computing (RAGE) 2022, and other high-quality submissions worldwide. All the submissions were reviewed by at least three expert reviewers in the subject area of each article.
The selected articles cover two broad sub-topics related to real-time computing in the IoT-to-Edge-to-Cloud Continuum: allocation and orchestration of software components and vehicular networks.
The first five articles belong to the first category.
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The article Distributed Task Offloading and Resource Purchasing in MEC: Hierarchical Game Theoretical Approaches by Chen et al. studies the problem of multi-user task offloading in mobile edge computing systems.
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The article Multi-Criteria Optimization of Real-Time DAGs on Heterogeneous Platforms under P-EDF by Cucinotta et al. addresses the problem of optimizing the placement of real-time embedded applications on heterogeneous platforms under energy efficiency constraints.
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The article Hierarchical Resource Orchestration Framework for Real-Time Containers by Struhàr et al. proposes an approach for resource allocation and adaptive re-dimensioning of real-time containers.
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The article Criticality-Aware Monitoring and Orchestration for Containerized Industry 4.0 Environments by Barletta et al. presents an orchestration system for Industry 4.0 environments that enables the support for real-time and mixed-criticality workloads.
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The article PArtNNer: Platform-agnostic Adaptive Edge-Cloud DNN Partitioning for minimizing End-to-End Latency by Ghosh et al. addresses the problem of deciding whether to run the inference of deep neural networks (DNNs) entirely at the edge, at the cloud, or by partitioning the DNN inference between the two.
The second category consists of three articles.
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The article Secure and Lightweight Blockchain-based Truthful Data Trading for Real-Time Vehicular Crowdsensing by Xu et al. proposes a secure blockchain-based data trading system for vehicular crowdsensing.
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The article Deadline-Aware Task Offloading for Vehicular Edge Computing Networks using Traffic Lights Data by Oza et al. presents a new offloading mechanism to capture time and location-specific requirements for vehicular applications.
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The article Minimal-Overlap Centrality for Multi-Gateway Designation in Real-Time Wireless Sensor Networks by Gutierrez Gaitan et al. presents a novel centrality-driven single- and multi-gateway designation framework for real-time wireless sensor networks with improved real-time performance.
We would like to thank all the authors for submitting their excellent work to this special issue and the reviewers for providing their valuable feedback. We thank the Editor-in-Chief of ACM Transactions on Embedded Computing Systems, Tulika Mitra, and the Special Issue Editors Andreas Gerstlauer and Hiren Patel, for their guidance throughout the organization of the special issue. Finally, we also thank all the editorial assistants, especially Arriane Bustillo, for their support in managing the reviewing process.
Daniel Casini
Scuola Superiore Sant'Anna, Italy
Dakshina Dasari
Robert Bosch GmbH, Germany
Matthias Becker
KTH Royal Institute of Technology, Sweden
Giorgio Buttazzo
Scuola Superiore Sant'Anna, Italy
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January 2024
406 pages
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Association for Computing Machinery
New York, NY, United States
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Published: 10 January 2024
Published in TECS Volume 23, Issue 1
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