Systematic Survey on Energy Conservation Using Blockchain for Sustainable Computing Challenges and Roadmaps

IF 3.9 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
S. Radha Rammohan, Komalavalli Chakravarthi, Nipun Sharma, Swati Sharma, Mallika Natarajan
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Abstract

This article proposes a comprehensive analysis of architectures that use blockchain technology to solve important aspects of computing sustainability, with an emphasis on scalability, resource utilization, transparency, and energy conservation. The research focuses on analyzing various structure which embraces decentralization and consensus principles, to redefine the computer infrastructure environment. The study highlights the technology that aids in improving scalability and resource utilization by decentralizing data storage and processing, relieving the load on centralized servers, and lowering the environmental effect of large-scale data centers. This study's findings are significant in uncovering best practices and optimizing the environmental impact of blockchain technology by evaluating blockchain indicators such as scalability, resource utilization, transparency, and energy saving within the framework of sustainable computing. The project intends to assist in the development of resource-efficient solutions, address scalability issues, and promote openness and accountability by evaluating the performance of various blockchain implementations. The findings help to promote the larger goal of connecting technical improvements, notably in blockchain, with global environmental goals. The research reveals that energy conservation is an important aspect of sustainability, and the different frameworks including techniques for optimizing energy consumption based on carbon footprint concerns, decentralization, and consensus methods are intended to prioritize energy-efficient nodes and promote environmentally friendly practices, resulting in a greener computing ecosystem.

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来源期刊
CiteScore
5.30
自引率
16.10%
发文量
163
审稿时长
5 months
期刊介绍: The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.
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