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Register a new userSoftware-Defined Edge Computing: A New Architecture Paradigm to Support IoT Data Analysis
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Added by
Di Wu
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their generated data such as time-dependency. Therefore, it is desirable to reshape the current IoT architectures by exploring their inherent nature of communication and computing to support smart IoT data process and analysis. We introduce in this paper features of IoT data, trends of IoT network architectures, some problems in IoT data analysis, and their solutions. Specifically, we view that software-defined edge computing is a promising architecture to support the unique needs of IoT data analysis. We further present an experiment on data anomaly detection in this architecture, and the comparison between two architectures for ECG diagnosis. Results show that our method is effective and feasible.
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Based on software-defined principles, we propose a holistic architecture for Cyberphysical Systems (CPS) and Internet of Things (IoT) applications, and highlight the merits pertaining to scalability, flexibility, robustness, interoperability, and cyber security. Our design especially capitalizes on the computational units possessed by smart agents, which may be utilized for decentralized control and in-network data processing. We characterize the data flow, communication flow, and control flow that assimilate a set of components such as sensors, actuators, controllers, and coordinators in a systemic programmable fashion. We specifically aim for distributed and decentralized decision-making by spreading the control over several hierarchical layers. In addition, we propose a middleware layer to encapsulate units and services for time-critical operations in highly dynamic environments. We further enlist a multitude of vulnerabilities to cyberattacks, and integrate software-defined solutions for enabling resilience, detection, and recovery. In this purview, several controllers cooperate to identify and respond to security threats and abnormal situations in a self-adjusting manner. Last, we illustrate numerical simulations in support of the virtues of a software-defined design for CPS and IoT.
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