Guest Editors
Dr. Mahmoud Shafik, University of Derby, UK.
Dr. Sumarga Kumar Sah Tyagi, Zhongyuan University of Technology, China.
Dr. Shiva Raj Pokhrel, Deakin University, Australia.
Summary
Internet of Things (IoT) is an ecosystem of connected physical objects that are accessible through the Internet. IoT involves the creation of smart communication environment between smart homes, smart transportation, and smart healthcare systems with the help of several devices in a network that enables transmission of data within these devices such as WSN (Wireless Sensor Network), RFID (Radio Frequency Identification), cloud services, NFC (Near Field Communication), gateways, data storage and analytics, and visualization elements. All the computation, control, system-latency, robustness, reliability, performance, and energy-efficiency of the system, in the IoT ecosystem are dictated by its architectures and algorithms. Because in the IoT ecosystem, the algorithms and architectures are solely responsible to collect data, interconnect each other and the Internet, processing, and taking decisions without human interaction. Therefore, super-fast computing with ultra-low latency has always been crucial issues faced by the rapid development of the Internet of Things (IoT).
Intelligent supercomputing architectures and algorithms (ISAA), with a focus on performance-QoS tradeoff, is an emerging technological trend of great significance. These algorithms, supported by appropriate architectures, can significantly enhance sustainability for advanced IoTs with regard to latency and computing resources, without compromising the offered quality of service (QoS).
However, the exponentially increasing use of sensors and actuators for IoT applications, that generate huge data and overarching through cloud computation, will significantly deteriorate the supercomputing efficiency. Thus, ameliorates the performance of ultra-fast computing via ISAA is a key challenge facing researchers in academia and industry.
Due to the growing use of artificial intelligence (AI) in this domain, several computing architecture and algorithms, especially, smart algorithms and architecture (SAA), are entering a more mature phase, with exciting applications in various IoT applications. Moreover, information sharing, ultra-fast computing, and intelligent decision-making capabilities help recent SAA play an important role in improving not only supercomputing efficiency but also the performance of the IoT ecosystem. However, it is essential to investigate the trade-off between the performance for ISAA, and the requirements of IoT applications. Moreover, it is crucial to evaluate the performance concerning computing resource optimization, the response time, reliability, and QoS regarding ISAA.
With this motivation, this special issue solicits the submissions of high-quality and unpublished articles that aim to address the open technical problems and challenges concerning supercomputing architecture and algorithms, considering the constraints of computing-efficiency, intelligence, and QoS. In particular, we seek submissions, which efficiently integrate novel AI approaches into several vorticial of the IoT ecosystem, focusing on the system performance evaluation and comparison with existing smart architecture and algorithms. Both theoretical and experimental studies for typical artificially intelligent supercomputing scenarios are encouraged.
Keywords
Intelligent supercomputing architecture for IoT.
Machine learning approaches for computing-efficient algorithms for IoT.
AI-based supercomputing modeling and analysis IoT.
Smart algorithm design and deployments for IoT.
Quality of service in smart IoT.
Energy-efficient supercomputing algorithms for IoT applications.
AI-based evolutionary algorithms for IoT applications.
Security, Privacy, and Trust in supercomputing models for IoT.
Anomaly detection in supercomputing framework for IoT.
Intelligent algorithm designs and implementations for smart IoT.
Big data analytics using supercomputing for IoT applications.
Intelligent supercomputing architecture for IoT Cloud.
Experimental test-beds and results for AI-based supercomputing architecture.
Framework designs for intelligent supercomputing algorithms for IoT.
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