Introduction

This chapter starts with a high-level characterization of data center energy before moving to a discussion of power, energy, and sustainability in warehouse-scale computers (WSCs). We discuss the economic and environmental importance of energy efficiency, and define metrics like PUE (Power Usage Effectiveness) and SPUE (Server PUE) that help assess and improve data center and server infrastructure efficiency. We also explore the concept of energy-proportional computing and techniques for enhancing the energy efficiency of computing resources. We then discuss data center power provisioning strategies, including oversubscription and energy storage, and conclude with a discussion of environmental sustainability and a high-level characterization of data center energy usage of the internet and cryptocurrency mining.

A market-oriented incentive mechanism for emergency demand response in colocation data centers

The volume and processing needs of spacecraft data is growing exponentially due to technological advances. This data needs to be processed, stored, and queried. It is often made available to communities that will add further value through additional processing for their communities to create benefit for European citizens and industry. Operators need to achieve this yet must continuously strive to improve efficiency and lower operational costs. Can the cloud provide solutions that address these objectivities? Cloud-based computing promises significant advantages to the space industry including improved expenditure control, reduced operational complexity, improved time to market, the encouragement of innovation by scientists and the ability to deliver new solutions that were not previously feasible. Control of expenditure is achieved by reducing capital spending, providing predictable costs matched to actual research activity, eliminating technical refreshes and delivering high utilisation. Operational complexity is decreased through simplified pricing models and SLA agreements across participating organisations. The reduced need for capital investment means that investment decisions are far easier to justify, and that initiatives can succeed (or fail) quickly and cheaply – with no long term financial commitment for the program; further, cloud computing allows the rapid scaling out of resources to respond to un-anticipated demands. A cloud infrastructure provides rapid access to computing services and leading-edge architectures in which scientists can innovate freely. Finally, cloud computing encourages cross-organisational collaboration and provides an environment where divisible calculation-intensive problems can be run in a fraction of the time that a traditional data centre would take. Today's economic climate is adding further pressure to mission management to reduce costs yet maintain quality, security, system trust and efficiency. Logica with experience from a number of space cloud initiatives will in this paper cut through the hype of cloud and provide clarity to operations and development teams on what, how and where cloud can be considered. The paper will examine some use cases of potential usage in operations processing, data archiving and operations consolidation.

Energy efficiency and economics of rice cultivation systems under subtropical Eastern Himalaya

Energy-efficient buildings are essential to reduce greenhouse gas emissions. However, improved energy efficiency may also bring about a rise in construction costs. If design variables can be prioritized according to their cost efficiencies, energy-efficient buildings can be designed more cost-efficiently. The aim of this study is to analyze the cost efficiencies of design variables related to energy efficiency of the apartment complex. After making 78 alternatives for 29 target items, each alternative's increased amount of construction cost and decreased amount of energy cost against the baseline model were then estimated using actual price data and the assessment methods of the Building Energy Efficiency Rating System that has been implemented in Korea, respectively. The life cycle cost, net present value, internal rate of return, and payback period of each alternative were shown as cost efficiency indexes. The order of priority of each alternative was presented and very cost-efficient alternatives were suggested.

Research background and purpose The main purpose of the article is to analyze the share of renewable energy sources in Poland's energy mix and to assess the management of the cost-effectiveness of their use, with particular emphasis on their impact on energy production costs, energy system stability and CO₂ reduction. Design/methodology/approach To achieve the purpose of the article, the author used a triangulation of research methods, which included a literature and regulatory review, scenario modeling and three analyses: statistical data, cost and energy efficiency. By using the above methods, the study will allow a comprehensive assessment of the role of renewable energy sources in the Polish power system and their impact on its cost efficiency. Findings The share of RES in Poland is growing, but still remains lower than in many EU countries, despite the fact that the cost of producing energy from renewable sources is steadily falling, making it increasingly cost-effective. Key barriers are the lack of developed storage infrastructure and legal restrictions for onshore wind farms. Value added and limitations The article provides up-to-date and detailed data on the structure of renewable energy consumption, taking into account the latest trends, regulations and technologies. A unique contribution is the analysis of various RES technologies in terms of their profitability and impact on energy prices, which provides practical conclusions for policy makers and investors, as well as the author's interdisciplinary approach - combining economic, legal, technological and social aspects. In conclusion, the value of the article stems from its timeliness, comprehensive approach and the possibility to use the results to shape energy policy and investment strategies in Poland.

High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer

Data centres in contemporary times are essential as the supply of data increases. Data centres are areas where computing systems are concentrated for facilitating data processing, transfer and storage. At present, traditional data centres have moved more towards the cloud model—thereby making the processing, storage and harnessing of data more manageable and more accessible via the utility and subscription-based model of computing services. From the administrative point of view, cloud data centres are complex systems and hard to grasp and require large amounts of time to analyse different aspects of the cloud data centre such as maintenance and resource management. For a cloud data centre admin, this could be a challenging problem and a highly time-consuming task. Accordingly, there is a need to improve the useability of cloud data centre monitoring and management tools, and the digital twin could fulfil this need. This book chapter’s primary objective is to construct a digital twin—a 3D visualisation and monitoring tool—of a cloud data centre managed by OpenStack, the well-known open-source cloud computing infrastructure software. To evaluate our proposed tool, we garner feedback on the digital twin’s useability compared to the OpenStack dashboard. The input will be received from cloud data centre experts as they test the digital twin and answer various questions in an interview. The study results show that our proposed digital twin will help data centre admins better monitor and manage their data centres. It will also facilitate further research and implementation of the digital twin of data centres to improve usability.KeywordsCloud data centreDigital twinOpenStackVisualisationMonitoringResource management

Recent research trends exhibit a growing imbalance between the demands of tenants' software applications and the provisioning of hardware resources. Misalignment of demand and supply gradually hinders workloads from being efficiently mapped to fixed-sized server nodes in traditional data centers. The incurred resource holes not only lower infrastructure utilization but also cripple the capability of a data center for hosting large-sized workloads. This deficiency motivates the development of a new rack-wide architecture referred to as the composable system. The composable system transforms traditional server racks of static capacity into a dynamic compute platform. Specifically, this novel architecture aims to link up all compute components that are traditionally distributed on traditional server boards, such as central processing unit (CPU), random access memory (RAM), storage devices, and other application-specific processors. By doing so, a logically giant compute platform is created and this platform is more resistant against the variety of workload demands by breaking the resource boundaries among traditional server boards. In this paper, we introduce the concepts of this reconfigurable architecture and design a framework of the composable system for cloud data centers. We then develop mathematical models to describe the resource usage patterns on this platform and enumerate some types of workloads that commonly appear in data centers. From the simulations, we show that the composable system sustains nearly up to 1.6 times stronger workload intensity than that of traditional systems and it is insensitive to the distribution of workload demands. This demonstrates that this composable system is indeed an effective solution to support cloud data center services.

The capability of the data center network largely decides the performance of cloud computing. However, the number of servers in the data center network becomes increasingly huge, because of the continuous growth of the application requirements. The performance improvement of cloud computing faces great challenges of how to connect a large number of servers in building a data center network with promising performance. Traditional tree-based data center networks have issues of bandwidth bottleneck, failure of single switch, etc. Recently proposed data center networks such as DCell, FiConn, and BCube, have larger bandwidth and better fault-tolerance with respect to traditional tree-based data center networks. Nonetheless, for DCell and FiConn, the fault-tolerant length of path between servers increases in case of failure of switches; BCube requires higher performance in switches when its scale is enlarged. Based on the above considerations, we propose a new server-centric data center network, called BCDC, based on crossed cube with excellent performance. Then, we study the connectivity of BCDC networks. Furthermore, we propose communication algorithms and fault-tolerant routing algorithm of BCDC networks. Moreover, we analyze the performance and time complexities of the proposed algorithms in BCDC networks. Our research will provide the basis for design and implementation of a new family of data center networks.

[Excerpt] Cloud computing is a new way of delivering computing services. The flexibility, scalability, and cost-effectiveness of cloud computing provides tremendous business opportunities to customers. The related customer expectation, however, poses daunting challenges to cloud service providers, whether they are traditional data centers or fresh players in the arena. These practical challenges raise new research questions to communities that are either computer science oriented or service science oriented. Performance analysis and service management are required to be knitted together for the success of the end game.

Cloud data center has become a trend and mainstream, and the first phase of the main data center of National Railway Group has been completed, and the main data center also adopts cloud computing technology. Compared with traditional data centers, cloud data centers bring great convenience of unified and flexible resource scheduling to railroads, but also bring many new security risks. Therefore, the study of security architecture and key technologies for cloud data centers becomes an important requirement for securing railroad cloud data centers. While cloud computing brings convenience to railroads, it also brings new security risks. By studying the information security model, we construct a cloud security architecture that meets the actual situation of railroads. In terms of responsibility, according to the level protection responsibility sharing model should be divided into cloud-based security protection and cloud platform foundation protection; in terms of construction, according to the sliding scale model, it should overlap and evolve, and gradually complete the security construction in several stages of infrastructure security, deep defense, active defense and threat intelligence.

In the current work, we formulate a dynamic spectrum assignment (DSA) technique to allocate the experimental licensed 95 GHz Tera-Hertz spectrum to the mobile service providers (MSPs) in India in view of achieving high spectrum usage. For a fixed term of renewal (ToR), the formulated DSA technique compares the number of consumers of an MSP with all the remaining MSPs and then assigns the spectrum accordingly. The DSA then updates the assigned spectrum to an MSP at every ToR in accordance with variation in the amount of consumers compared to the previous ToR. The DSA technique is formulated such that it finds the optimal spectrum amount required by every MSP during each ToR. Also, the mean capacity (MC), spectral efficiency (SE), energy efficiency (EE), and cost efficiency (CE) are derived for each MSP. The aforementioned metrics are used to compare the performance of DSA with the static spectrum assignment (SSA) method, which assigns the spectrum to any MSP without accounting for the actual requirement by the consumer. We conduct extensive simulations considering a specific scenario with four MSPs, and the results demonstrate that the DSA technique is able to meet the demands of the 6G wireless systems as it is able to reuse the available spectrum for every MSP for a fewer number of cells of approximately 38% reduced amount of buildings. Further, the results also demonstrate that, in comparison to the traditional static spectrum assignment (SSA) method, DSA improves the MC and SE by 20% and the EE and CE by 25%.

The present situation of current data center network is described, and the existing problems in the data center network is analyzed, according to practical engineering experience, analyzing the switch virtualization and the load equipment bypass deployment model, providing some actual experience for solving existing technological problems in traditional data center.

CoMap: An efficient virtual network re-mapping strategy based on coalitional matching theory