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Article
Computer Science, Theory & Methods
Andrei Paleyes et al.
Summary: In recent years, machine learning has transitioned from a field of academic research interest to a field capable of solving real-world business problems. However, the deployment of machine learning models in production systems can present a number of issues and concerns. This survey reviews published reports of deploying machine learning solutions in various use cases, industries, and applications and extracts practical considerations corresponding to stages of the machine learning deployment workflow.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Firas Al-Doghman et al.
Summary: The paradigm of edge computing has created new possibilities for the Internet of Things (IoT), expanding cloud services to the network edge. This allows for the design of distributed architectures and the enhancement of decision-making applications. Edge computing faces challenges related to security and privacy, but advancements in artificial intelligence and machine learning provide opportunities for precise models and intelligent applications at the network edge. This study presents a comprehensive survey on securing edge computing-based AI microservices, highlighting key requirements and proposing a secure edge computing framework.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Review
Engineering, Electrical & Electronic
Faiga Alawad et al.
Summary: The concept of Value of Information (VoI) has gained increasing interest in Wireless Sensor Network (WSN) and Internet of Things (IoT) applications. This article categorizes application use cases, examines the use of VoI, explores different approaches to defining VoI, and provides a comprehensive discussion of specific methods used to determine VoI.
IEEE SENSORS JOURNAL
(2022)
Review
Computer Science, Theory & Methods
Daniel Rosendo et al.
Summary: The increasing demand for data analytics and machine learning has led to the rapid development of edge analytics and complex infrastructures that connect edge devices to cloud systems. Thorough experimental analysis is needed to evaluate the impact of various factors and ensure experiment reproducibility. This review surveys the state-of-the-art libraries, frameworks, and testbeds for machine learning and data analytics, and discusses the challenges and future directions in this field.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Review
Computer Science, Information Systems
Anders Eivind Braten et al.
Summary: This study provides a comprehensive review of autonomous device management for large-scale deployments of constrained devices in the IoT field, covering various aspects such as management tasks, operational environment, network topology, resource constraints, scalability, and management categories. It identifies common patterns for autonomous management and presents a generalized model that unifies previous insights, offering best practices for designing and implementing solutions around adaptation mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Information Systems
Ivan Alfonso et al.
Summary: In recent years, the relevance of the Internet of Things (IoT) has increased significantly, becoming a key component in industrial processes and daily life activities. IoT systems are affected by changes in their operating environments, which can impact Quality of Service (QoS). Various self-adaptation strategies have been proposed in the literature to address these changes, but there is a lack of comprehensive understanding of how different proposals for adaptation can be combined to cope with simultaneous events of different types. This paper provides a comprehensive view of the interplay of dynamic events in IoT adaptation, their impact on QoS, and alternative adaptation strategies, based on a systematic literature review and research agenda for the near future.
JOURNAL OF INTERNET SERVICES AND APPLICATIONS
(2021)
Review
Computer Science, Information Systems
Jing Zhang et al.
Summary: This article discusses the importance of integrating artificial intelligence into the Internet of Things, and how AI can make IoT faster, smarter, greener, and safer. Additionally, it summarizes the AIoT architecture, four research perspectives, and some promising applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Yulei Wu
Summary: The Internet of Things is widely utilized in various critical sectors, requiring efficient data processing. AI-powered cloud-edge orchestration provides crucial computing support for IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
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Computer Science, Information Systems
Soraya Sinche et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2020)
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Rehan Ahmed et al.
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
(2019)
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Computer Science, Information Systems
George Kousiouris et al.
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Computer Science, Information Systems
Wael Ayoub et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2019)
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Gopika Premsankar et al.
IEEE INTERNET OF THINGS JOURNAL
(2018)
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Engineering, Electrical & Electronic
Muhammad Alam et al.
IEEE COMMUNICATIONS MAGAZINE
(2018)
Review
Green & Sustainable Science & Technology
Faisal Karim Shaikh et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2016)
Proceedings Paper
Computer Science, Software Engineering
Henry Muccini et al.
PROCEEDINGS OF 2016 IEEE/ACM 11TH INTERNATIONAL SYMPOSIUM ON SOFTWARE ENGINEERING FOR ADAPTIVE AND SELF-MANAGING SYSTEMS (SEAMS)
(2016)
Article
Computer Science, Artificial Intelligence
Ali Borji et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2013)
