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Microgrid technology is poised to transform the electricity industry. In the context of commercial/domestic buildings and data centers, where most loads are native direct current, DC microgrids are in fact a natural choice. Voltage stability and current/power‐sharing between sources within a DC microgrid have been studied extensively in recent years. DC voltage droop control is known to have its drawbacks in that current or power‐sharing is relatively poor. To eliminate this drawback, some have proposed to add a communication‐based consensus control in addition to the primary voltage droop control loop. The current sharing performance is improved, however, the voltage deviation inherent in droop control requires a further, slower control to achieve voltage quality control. To overcome this complication, and reduction in response time, a low latency communication‐based control technique that achieves proportional current sharing without significant voltage deviations is proposed in this work. The stability of the proposed control technique is compared to state‐of‐the‐art using eigenvalue and transient analyses. The negative impact of communication delays on proposed control is discussed in detail.

Cloud computing is a commercial and economic paradigm that has gained traction since 2006 and is presently the most significant technology in IT sector. From the notion of cloud computing to its energy efficiency, cloud has been the subject of much discussion. The energy consumption of data centres alone will rise from 200 TWh in 2016 to 2967 TWh in 2030. The data centres require a lot of power to provide services, which increases CO2 emissions. In this survey paper, software-based technologies that can be used for building green data centers and include power management at individual software level has been discussed. The paper discusses the energy efficiency in containers and problem-solving approaches used for reducing power consumption in data centers. Further, the paper also gives details about the impact of data centers on environment that includes the e-waste and the various standards opted by different countries for giving rating to the data centers. This article goes beyond just demonstrating new green cloud computing possibilities. Instead, it focuses the attention and resources of academia and society on a critical issue: long-term technological advancement. The article covers the new technologies that can be applied at the individual software level that includes techniques applied at virtualization level, operating system level and application level. It clearly defines different measures at each level to reduce the energy consumption that clearly adds value to the current environmental problem of pollution reduction. This article also addresses the difficulties, concerns, and needs that cloud data centres and cloud organisations must grasp, as well as some of the factors and case studies that influence green cloud usage.

Learn how IT leaders are adapting to the new reality of life during and after COVID-19 COVID-19 has caused fundamental shifts in attitudes around remote and office work. And in The New Normal in IT: How the Global Pandemic Changed Information Technology Forever, internationally renowned IT executive Gregory S. Smith explains how and why companies today are shedding corporate office locations and reducing office footprints. You'll learn about how companies realized the value of information technology and a distributed workforce and what that means for IT professionals going forward. The book offers insightful lessons regarding: * How to best take advantage of remote collaboration and hybrid remote/office workforces * How to implement updated risk mitigation strategies and disaster recovery planning and testing to shield your organization from worst case scenarios * How today's CIOs and CTOs adapt their IT governance frameworks to meet new challenges, including cybersecurity risks The New Normal in IT is an indispensable resource for IT professionals, executives, graduate technology management students, and managers in any industry. It's also a must-read for anyone interested in the impact that COVID-19 had, and continues to have, on the information technology industry.

In recent years, data and computing resources are typically distributed in the devices of end users, various regions or organizations. Because of laws or regulations, the distributed data and computing resources cannot be aggregated or directly shared among different regions or organizations for machine learning tasks. Federated learning emerges as an efficient approach to exploit distributed data and computing resources, so as to collaboratively train machine learning models. At the same time, federated learning obeys the laws and regulations and ensures data security and data privacy. In this paper, we provide a comprehensive survey of existing works for federated learning. First, we propose a functional architecture of federated learning systems and a taxonomy of related techniques. Second, we explain the federated learning systems from four aspects: diverse types of parallelism, aggregation algorithms, data communication, and the security of federated learning systems. Third, we present four widely used federated systems based on the functional architecture. Finally, we summarize the limitations and propose future research directions.

The rapid development of internet of things (IoT) gadgets and the increase in the rate of sending requests from these devices to cloud data centers resulted in congestion and consequently service provisioning delays in the cloud data centers. Accordingly, fog computing emerged as a new computing model to address this challenge. In fogging, services are provisioned at the edge of the network using devices with computing and storage capabilities, which are located through the way to connect IoT devices to cloud data centers. Fog computing aims to alleviate the computing load in data centers and cut the delay of requests down, notably real-time and delay-sensitive requests. To achieve these goals, vitally important challenges such as scheduling requests, balancing the load, and reducing energy consumption, which affects performance and reliability in the edge-fog-cloud computing architecture, should be considered into account. In this paper, a reinforcement learning fog scheduling algorithm is proposed to address these challenges. The experimental results indicate that the proposed algorithm raises the load balance and diminishes the response time compared to the existing scheduling algorithms. Additionally, the proposed algorithm outperforms other approaches in terms of the number of used devices.

[...] studies are inherently dependent on the completeness of a global tropical cyclone best-track dataset. [...] NOAA's National Climatic Data Center (NCDC), in concert with the World Data Center for Meteorology- Asheville, has developed a comprehensive dataset through the collection of global tropical cyclone best-track data.

Traditional data centers are shifted toward the cloud computing paradigm. These data centers support the increasing demand for computational and data storage that consumes a massive amount of energy at a huge cost to the cloud service provider and the environment. Considerable energy is wasted to constantly operate idle virtual machines (VMs) on hosts during periods of low load. Dynamic consolidation of VMs from overloaded or underloaded hosts is an effective strategy for improving energy consumption and resource utilization in cloud data centers. The dynamic consolidation of VM from an overloaded host directly influences the service level agreements (SLAs), utilization of resources, and quality of service (QoS) delivered by the system. We proposed an algorithm, namely, GradCent , based on the Stochastic Gradient Descent technique. This algorithm is used to develop an upper CPU utilization threshold for detecting overloaded hosts by using a real CPU workload. Moreover, we proposed a dynamic VM selection algorithm called Minimum Size Utilization ( MSU ) for selecting the VMs from an overloaded host for VM consolidation. GradCent and MSU maintain the trade-off between energy consumption minimization and QoS maximization under specified SLA goal. We used the CloudSim simulations with real-world workload traces from more than a thousand PlanetLab VMs. The proposed algorithms minimized energy consumption and SLA violation by 23% and 27.5% on average, compared with baseline schemes, respectively.

In the last few years, the appealing features of cloud computing have been fueling the integration of cloud environments in the industry, which has been consequently motivating the research on related technologies by both the industry and the academia. The possibility of paying-as-you-go mixed with an on-demand elastic operation is changing the enterprise computing model, shifting on-premises infrastructures to off-premises data centers, accessed over the Internet and managed by cloud hosting providers. Regardless of its advantages, the transition to this computing paradigm raises security concerns, which are the subject of several studies. Besides of the issues derived from Web technologies and the Internet, clouds introduce new issues that should be cleared out first in order to further allow the number of cloud deployments to increase. This paper surveys the works on cloud security issues, making a comprehensive review of the literature on the subject. It addresses several key topics, namely vulnerabilities, threats, and attacks, proposing a taxonomy for their classification. It also contains a thorough review of the main concepts concerning the security state of cloud environments and discusses several open research topics.

At year's end, the Arkansas Public Service Commission is weighing nearly a dozen proposed power rate increases, and it's widely expected to approve some form of most of them. Entergy also wants to raise rates about $2.85 per month for typical residential customers to finance a $1.6 billion natural gas-burning plant in Redfield, the proposed Jefferson Power Station. Lauren Waldrip, director of the Arkansas Advanced Energy Association, said insufficient resource planning contributed to the power plant pinch. | | £ \"Our utilities have been very clear that Arkansas does not have enough generation to meet today's news, and that shortfall exists regardless of data center growth.\"