Article
Computer Science, Information Systems
Liang Li, Dian Shi, Ronghui Hou, Xuanheng Li, Jie Wang, Hui Li, Miao Pan
Summary: This research investigates the service provisioning problem under service demand uncertainty in a cooperative edge computing system, and proposes a holistic solution to maximize the deploying profits of service providers through two-timescale decisions. The algorithm integrates Benders decomposition and alternating direction method of multipliers to address resource rental and workload assignment while protecting data privacy. Extensive simulations based on real-world data sets validate the efficacy of the proposed scheme.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Claudio Savaglio, Giancarlo Fortino
Summary: EdgeMiningSim is a simulation-driven methodology inspired by software engineering principles to support IoT Data Mining. It provides domain experts with descriptive or predictive models to take effective actions in constrained and dynamic IoT scenarios.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Zhengong Cai, Guozheng Yang, Shaoyong Xu, Cheng Zang, Jiajun Chen, Pingping Hang, Bowei Yang
Summary: This article introduces the advantages of blockchain technology and the development of Blockchain-as-a-Service (BaaS) as well as its limitations. To address the limitations of existing BaaS systems, a novel cloud-edge collaborative BaaS paradigm is proposed, which aims to enhance the availability of blockchain systems through redundant node candidates, leader election, and edge network self-healing components.
Article
Computer Science, Information Systems
Gabriele Morabito, Christian Sicari, Armando Ruggeri, Antonio Celesti, Lorenzo Carnevale
Summary: Nowadays, many Cloud companies adopt serverless computation based on the Function as a Service (FaaS) paradigm. Complex systems may now be viewed as a graph of serverless functions distributed over the Cloud and Edge layers. This work relies on Osmotic Computing principles to enhance the security and execution time of serverless applications.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Heng Qi, Junxiao Wang, Wenxin Li, Yuxin Wang, Tie Qiu
Summary: The article introduces a method of designing a lightweight traffic classification service in Industrial Internet of Things using hash mechanism and blockchain consensus mechanism. Through extension hashing and voting-based consensus algorithm to achieve efficient and accurate traffic classification, adapting to edge computing paradigm, improves classification accuracy, and reduces time cost and memory usage.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Theory & Methods
Shivananda R. Poojara, Chinmaya Kumar Dehury, Pelle Jakovits, Satish Narayana Srirama
Summary: With the growth of IoT devices, the need for efficient data processing and analytics is increasing. This study explores the benefits of using Serverless data pipelines for IoT data analytics and evaluates different approaches for designing such pipelines. The results reveal the suitability of different design methods for different types of applications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Engineering, Manufacturing
Saeed Farahani, Vinayak Khade, Shouvik Basu, Srikanth Pilla
Summary: Injection molding is a common process in the plastics industry, and the implementation of predictive maintenance systems can help reduce costs and improve product quality and production efficiency.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Engineering, Electrical & Electronic
Jianli Pan, Jianyu Wang, Ismail AlQerm, Yuanni Liu, Zhicheng Yang
Summary: Integrating IoT and edge computing in Edge-IoT systems, with machine intelligence, can enable a wide range of applications. The ORCA project aims to empower IoT asset owners to effectively manage their assets and address challenges associated with traditional methods.
IEEE COMMUNICATIONS MAGAZINE
(2021)
Article
Computer Science, Information Systems
Dapeng Wu, Meiyu Sun, Puning Zhang, Yanli Tu, Zhigang Yang, Ruyan Wang
Summary: Demand-oriented data service can conveniently and quickly provide physical entity information for IoT users. Traditional cloud-oriented data service architecture is not suitable for state time-varying and privacy-sensitive entity data in IoT. Edge-based architecture lacks global service function but can alleviate problems with cloud services. Existing demand-oriented data service ignores the characteristics of thousands of people have thousands of faces and the implicit intents of users, resulting in limited service quality and weak user experience. To solve these problems, a personalized secure demand-oriented data service scheme is proposed.
IEEE INTERNET OF THINGS JOURNAL
(2023)
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)
Article
Chemistry, Analytical
Hikmat Yar, Ali Shariq Imran, Zulfiqar Ahmad Khan, Muhammad Sajjad, Zenun Kastrati
Summary: Smart home applications have become popular due to IoT technology, making homes more convenient, efficient, and secure. Our research proposes a cost-effective solution for smart home automation using Raspberry Pi, allowing remote and automatic control of home appliances while ensuring customer privacy.
Article
Computer Science, Theory & Methods
Linghe Kong, Jinlin Tan, Junqin Huang, Guihai Chen, Shuaitian Wang, Xi Jin, Peng Zeng, Muhammad Khan, Sajal K. Das
Summary: The Internet of Things is impacting connectivity globally, with an increasing number of IoT devices bringing benefits to daily life. However, the influx of devices poses challenges for cloud-based computing, leading researchers to explore edge computing as a decentralized model for processing data nearer to devices. This survey aims to analyze the impact of edge computing on IoT, highlight the necessity for investigation in this area, and categorize recent advances and challenges in edge computing-driven IoT.
ACM COMPUTING SURVEYS
(2023)
Review
Computer Science, Interdisciplinary Applications
Rohit Kumar, Neha Agrawal
Summary: Cloud computing is transforming traditional computing methods through various forms and architectural types, such as Edge and Fog computing. These extensions of the basic cloud computing model promise improved network performance. Industrial applications rely on cloud resources to process a large volume of power-sensitive Industrial IoT (IIoT) data, which requires careful analysis to enhance system performance. This paper explores the Edge-Fog-Cloud architectural frameworks, compares their advantages and disadvantages, and delves into the scientific side of multi-dimensional IIoT data. It also highlights the current state-of-the-art and implementation challenges.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2023)
Article
Computer Science, Information Systems
Junjie Xie, Chen Qian, Deke Guo, Xin Li, Ge Wang, Honghui Chen
Summary: Mobile edge computing is a new paradigm that places computing and storage resources at the edge of the Internet. Efficient data placement and retrieval services are crucial for the collaborative edge clouds in mobile edge computing. The existing methods like distributed hash tables (DHTs) are insufficient for efficient data placement and retrieval. This article proposes GRED, a novel data placement and retrieval service that achieves load balance, routing path lengths, and forwarding table sizes efficiently. GRED utilizes programmable switches to support a virtual-space based DHT with only one overlay hop, allowing easy data location implementation and efficient load balancing.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Chuntao Ding, Ao Zhou, Yunxin Liu, Rong N. Chang, Ching-Hsien Hsu, Shangguang Wang
Summary: This article presents a cloud-edge collaboration framework for delivering cognitive services with long-lasting, fast response, and high accuracy properties. The framework deploys shallow models on edge servers and deep models on cloud servers, enabling collaboration between the models to improve performance and accuracy.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)