A Review on the Recent Advances in Battery Development and Energy Storage Technologies

Journal of Renewable Energy, Год журнала: 2024, Номер 2024, С. 1 - 35

Опубликована: Май 8, 2024

Energy storage is a more sustainable choice to meet net-zero carbon foot print and decarbonization of the environment in pursuit an energy independent future, green transition, uptake. The journey reduced greenhouse gas emissions, increased grid stability reliability, improved access security are result innovation systems. Renewable sources fundamentally intermittent, which means they rely on availability natural resources like sun wind rather than continuously producing energy. Due its ability address inherent intermittency renewable sources, manage peak demand, enhance make it possible integrate small-scale systems into grid, essential for continued development decentralization generation. Accordingly, effective system has been prompted by demand unlimited supply energy, primarily through harnessing solar, chemical, mechanical Nonetheless, order achieve transition mitigate climate risks resulting from use fossil-based fuels, robust necessary. Herein, need better, devices such as batteries, supercapacitors, bio-batteries critically reviewed. their low maintenance needs, supercapacitors facilities, most notably Moreover, possess charging discharging cycles, high power density, requirements, extended lifespan, environmentally friendly. On other hand, combining aluminum with nonaqueous charge materials conductive polymers each material’s unique capabilities could be crucial batteries. In general, density key component battery development, scientists constantly developing new methods technologies existing batteries proficient safe. This will design that powerful lighter range applications. When there imbalance between (ESS) offer way increasing effectiveness electrical They also play central role enhancing reliability excellence networks can deployed off-grid localities.

Язык: Английский

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A new approach to reduce energy consumption in priority live migration of services based on green cloud computing

Cluster Computing, Год журнала: 2025, Номер 28(3)

Опубликована: Янв. 22, 2025

Язык: Английский

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Enhancement in performance of cloud computing task scheduling using optimization strategies

Cluster Computing, Год журнала: 2024, Номер 27(5), С. 6265 - 6288

Опубликована: Фев. 27, 2024

Язык: Английский

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An Efficient Task Scheduling for Cloud Computing Platforms Using Energy Management Algorithm: A Comparative Analysis of Workflow Execution Time

IEEE Access, Год журнала: 2024, Номер 12, С. 34208 - 34221

Опубликована: Янв. 1, 2024

Cloud computing platform offers numerous applications and resources such as data storage, databases, network building. However, efficient task scheduling is crucial for maximizing the overall execution time. In this study, workflows are used datasets to compare algorithms, including Shortest Job First, First Come, Served, (DVFS) Energy Management Algorithms (EMA). To facilitate comparison, number of virtual machines in Visual Studio Net framework environment increased. The experimental findings indicate that increasing reduces Makespan. Moreover, Algorithm (EMA) outperforms by 2.79% CyberShake process surpasses Serve algorithm 12.28%. Additionally, EMA produces 21.88% better results than both algorithms combined. For Montage process, performs 4.50% 25.75% superior policy. Finally, we ran simulations determine performance suggested mechanism contrasted it with widely energy-efficient techniques. simulation demonstrate structural design may successfully reduce amount give suitable cloud.

Язык: Английский

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An energy-efficient task scheduling method for heterogeneous cloud computing systems using capuchin search and inverted ant colony optimization algorithm

The Journal of Supercomputing, Год журнала: 2023, Номер 80(6), С. 7812 - 7848

Опубликована: Ноя. 10, 2023

Язык: Английский

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A cluster-oriented task assignment optimization for green high-performance computing center operations

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110929 - 110929

Опубликована: Янв. 1, 2025

Язык: Английский

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The Application of Virtual Machine Placement Using Fuzzy Grouping Genetic Algorithm

Journal of Advances in Information Technology, Год журнала: 2025, Номер 16(2), С. 189 - 197

Опубликована: Янв. 1, 2025

Язык: Английский

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Deep learning BiLSTM and Branch-and-Bound based multi-objective virtual machine allocation and migration with profit, energy, and SLA constraints

Sustainable Computing Informatics and Systems, Год журнала: 2025, Номер 46, С. 101128 - 101128

Опубликована: Май 5, 2025

Язык: Английский

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Design and Development of a Fog-Assisted Elephant Corridor over a Railway Track

Sustainability, Год журнала: 2023, Номер 15(7), С. 5944 - 5944

Опубликована: Март 29, 2023

Elephants are one of the largest animals on earth and found in forests, grasslands savannahs tropical subtropical regions Asia Africa. A country like India, especially northeastern region, is covered by deep forests home to many elephants. Railroads an effective inexpensive means transporting goods passengers this region. Due poor visibility collisions between trains elephants increasing day day. In last ten years, more than 190 died due train accidents. The most solution collision problem stop immediately. To address sensitive issue, a needed detect monitor near railroad tracks analyze data from camera trap intersection elephant corridors tracks. paper, we have developed fog computing-based framework that not only detects monitors but also improves latency, network utilization execution time. fog-enabled monitoring system informs control existence corridor warning light LED flashes This deployed simulated iFogSim simulator shows improvements utilization, time compared cloud-based infrastructures.

Язык: Английский

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Game theory-based virtual machine migration for energy sustainability in cloud data centers

Applied Energy, Год журнала: 2024, Номер 372, С. 123798 - 123798

Опубликована: Июль 3, 2024

As the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability environments. This paper presents novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs game-theoretic based on particle swarm optimization (PSO) (PSO-GTA). The proposed leverages collaborative competitive dynamics of Game Theory minimize while using renewable energy. In this context, game is represented by swarm, where each player, embodied particles, carries both cooperative elements essential shape collective behavior swarm. PSO integrated refine decisions, improving global convergence VMs hosts. Through extensive simulations performance evaluations, demonstrates significant improvements utilization efficiency, promoting research contributes development environmentally friendly systems, thus ensuring delivery energy-efficient computing. results demonstrate outperforms fuzzy genetic methods terms usage. PSO-GTA algorithm consistently Q-Learning, Pittsburgh KASIA across three simulation scenarios with varying cloudlet dynamics, showcasing its efficiency adaptability, yielding ranging from 0.68% 5.32% over baseline nine simulations.

Язык: Английский

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