Journal Article10.1007/S11277-015-3093-8
Efficient Resource Management Scheme for Storage Processing in Cloud Infrastructure with Internet of Things
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TL;DR: An efficient resource management scheme (ERMS) is proposed that efficiently manages IoT resources using cloud infrastructure satisfying the high availability, expansion, and high processing amount requirements.
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Abstract: Recently, research on cloud-integrated Internet of Things where an Internet of Things (IoT) is converged with a cloud environment has been actively pursued. An IoT operates through interaction among many composition elements, such as actuators and sensors. At present, IoTs are used in diverse areas (for example, traffic control and safety, energy savings, process control, communications systems, distributed robots, and other important applications). In daily life, IoTs should provide services of high reliability corresponding with various physical elements. In order to guarantee highly reliable IoT services, optimized modeling, simulation, and resource management technologies integrating physical elements and computing elements are required. For such reasons, many systems are being developed where autonomic computing technologies are applied that sense any internal errors or external environmental changes occurring during system operation and where systems adapt or evolve themselves. In an IoT environment composed of large-scale nodes, autonomic computing requires a high processing amount and efficient storage processing of computing in order to process sensing data efficiently. In addition, due to the heterogeneous composition of IoT environments, separate middleware is required to share collected information. Accordingly, this paper proposed an efficient resource management scheme (ERMS) that efficiently manages IoT resources using cloud infrastructure satisfying the high availability, expansion, and high processing amount requirements. ERMS provides a XML-based standard sensing data storage scheme in order to store and process heterogeneous IoT sensing data in the cloud infrastructure. In addition, ERMS provides classification techniques to efficiently store and process distributed IoT data.
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A Review of Internet of Things—Resource Allocation
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TL;DR: The key techniques, state-of-the-art, challenges, and trend associated with the IoT resource allocation, and its impact on the enterprise architecture are identified.
121
A survey study on Internet of Things resource management
Abishi Chowdhury,Shital A. Raut +1 more
TL;DR: There is still a lot of scope in improving IoT resource management maintaining the overall quality needed, and the paper considers with such a future direction of research in this field.
74
A new technology perspective of the Metaverse: Its essence, framework and challenges
Feifei Shi,Huansheng Ning,Xiaohong Zhang,Rongyang Li,Qiaohui Tian,Shiming Zhang,Youliang Zheng,Ye Guo,Mahmoud Daneshmand +8 more
Abstract: The Metaverse depicts a parallel digitalized world where virtuality and reality are fused. It has economic and social systems like those in the real world and provides intelligent services and applications. In this paper, we introduce the Metaverse from a new technology perspective, including its essence, corresponding technical framework, and potential technical challenges. Specifically, we analyze the essence of the Metaverse from its etymology and point out breakthroughs promising to be made in time, space, and contents of the Metaverse by citing Maslow's Hierarchy of Needs. Subsequently, we conclude four pillars of the Metaverse, named ubiquitous connections, space convergence, virtuality and reality interaction, and human-centered communication, and establish a corresponding technical framework. Additionally, we envision open issues and challenges of the Metaverse in the technical aspect. The work proposes a new technology perspective of the Metaverse and will provide further guidance for its technology development in the future. © 2022 Published by Elsevier Ltd.
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