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The New Scientist hosted an Emerging Technologies Summit in London, where business executives and thought leaders gathered to discuss the impact of the latest innovations on various industries. Topics covered included quantum computing, artificial intelligence, and the space industry. Presenters highlighted the positive effects of these technologies, such as the use of generative AI in drug design and testing, the incorporation of AI tools in the creative industries, and the application of quantum key distribution in securing financial information. The event also emphasized the need for ethical and responsible adoption of emerging technologies and the importance of managing and mitigating risks. [Extracted from the article]

This article discusses the risks associated with trusting artificial intelligence (AI) in scientific research. While AI models are increasingly being used in various scientific fields, such as bioengineering, veterinary medicine, and climatology, there are concerns about their limitations and potential biases. The authors argue that humans tend to attribute too much authority and trustworthiness to AI systems, which can lead to problems in research. They highlight the risks of relying on AI tools, such as the potential for cognitive illusions and the loss of diversity in human perspectives. The authors suggest strategies for mitigating these risks, including diversifying research approaches and being transparent about AI funding. They emphasize the importance of human involvement in scientific knowledge production and caution against assuming that AI automatically leads to better science. [Extracted from the article]

Industrial artificial intelligence (AI) has the potential to revolutionize industries and contribute to global sustainability. AI systems can optimize industrial processes for holistic business, social, and environmental outcomes. For example, Siemens has used AI to improve water management by reducing leaks and predicting blockages in sewage systems. AI can also be used to manage the environmental impact of data centers and improve energy efficiency. While there are concerns about the energy requirements of AI, its computing efficiency is improving. To fully realize the benefits of AI, existing infrastructure, data, and sensor networks should be utilized, and interoperability between different technologies is crucial. Overall, AI has the potential to help humanity achieve a smarter and more environmentally friendly future. [Extracted from the article]

This practice limits the ability to recycle usable materials and e-waste, meaning that more new resources must be consumed to create new products, In 2021, we conducted an assessment of why consumers engage in product hibernation instead of recycling and identified the following areas of opportunityR (it should be noted that there are usually multiple factors in a decision to hibernate a product, and that the key factors differ by product, so pursuing all of these areas is critica I to maximize electronic recycling): low handoff-option owareness or convenience. The circular economy has a key role in stopping the disposal of embodied carbon en route to a net-zero world, Every piece of waste represents a new product that will be created from scratch and thus a missed opportunity to cut embodied emissions. Use recycled materials to create new goods and products, as recycled resources generate significantly lower greenhouse-gas emissions than virgin resources during production. [Extracted from the article]

Data centers consume a significant amount of water, but the exact amount is difficult to determine due to limited public data. This can have negative impacts on the communities where they are located, as seen in The Dalles, Oregon. Many data center operators do not monitor their water usage, so it is important for them to use water efficiently. Civil engineers can help manage water consumption through water balance studies and site selection considerations. They also play a role in designing cooling systems and infrastructure, calculating water consumption, and designing water supply and discharge systems. Data centers generate wastewater effluents that must be discharged to the water utility's sewer system, and civil engineers can help design filtration systems and manage water systems. They can also assist water utilities in creating master plans that consider future data center development. Resilience and redundancy are growing concerns for data centers, and some operators are requesting information on water reliability and resilience plans from water utilities. Opportunities exist for civil engineers to minimize water consumption, waste, and energy usage for cooling in data centers. [Extracted from the article]

The article explores the potential impact of AI on the internet and optical networking, posing the question of whether it constitutes a "Eureka!" moment akin to Archimedes' discoveries. It delves into the challenges posed by increased AI-driven internet traffic, the need for upgraded data centers, and the role of electro-optic polymers as a promising technology to enhance optical components, potentially revolutionizing optical networking.

Now physicist James Crutchfield of the University of California, Davis, and graduate student Kyle Ray have proposed a new way to carry out computation that would dissipate only a small fraction of the heat produced by conventional circuits. In ballistic computing, a particle's velocity simply transports it through the device, allowing the particle to ferry information from input to output, Crutchfield says. But Ray and Crutchfield say that it is possible to do better by encoding information in electric currents in a new way: not as pulses of charge but in the momentum of the moving particles. [Extracted from the article]

An interview with Ryan Lafler, president and chief technology officer of Quantum Corrido is presented. When asked about Quantum Corridor get its start, he discussed In October 2023, a transmission between Chicago ORD 10 and Digital Crossroads data centers demonstrated faster speeds fiber networks, for future quantum transmissions. He highlights the project's connectivity capabilities, including 40 terabits per second (Tbps) and key collaborators Ciena and C1 in building the corridor.

This article from New Scientist provides a few interesting scientific findings. Firstly, researchers have discovered that soil bacteria called Myxococcus xanthus consume another type of bacteria, Pseudomonas fluorescens, when the temperature is 32°C (90°F), but the tables turn when the P. fluorescens is raised at 22°C (72°F), leading to the extinction of M. xanthus. Secondly, male Antechinus, a shrew-like marsupial from Australia, sacrifice three hours of sleep per night during their breeding period before dying of exhaustion. Lastly, an International Energy Agency report predicts that the demand for internet services and AI will cause data centers to double their electricity consumption in two years, reaching 1000 terawatt-hours in 2026. [Extracted from the article]

While opponents question this accounting, it's still a far cry from the thousands of jobs Disney promised in the '90s.) One of the central issues with data centers, in the view of John Hennessy, the retired chief historian of Fredericksburg and Spotsylvania National Military Park and an authority on Manassas history, is the lack of third-party, empirical analysis of the industry's long-term impact. BATTLE LINES: For decades, advocates have defended Manassas National Battlefield Park from one threat after another. Past is Prologue Ann Bennett, land use chair for the Sierra Club's Great Falls chapter, calls this recent data center proposal the "fifth battle of Manassas." Now with the specter of a massive data center project looming, they may be facing their biggest fight yet. [Extracted from the article]

The article discusses the significance of a cooling method used in computer data centers known as immersion cooling that could mitigate energy costs and consumption. It examines advances in immersion cooling technology, the advantages of immersion cooling over traditional cooling systems, and the impact upon the measurement rating known as power usage effectiveness (PUE).

In 2007, as an undergraduate psychology student, I sat in my university library, reading the latest report from the Intergovernmental Panel on Climate Change (IPCC). But changing how we do MRI scanning and our conferences is one thing that we can act on, right now - and importantly, only we can change - governments don't know how to reduce the environmental footprint of MRI scans! In the grand scheme of things, the carbon footprint of my MRI scan analyses and my MRI society conference are small. [Extracted from the article]

The author discusses the issue of power consumption in server farms. She mentions the carbon footprint of some of the biggest companies storing data, the management and distribution of electricity in a data center, and discusses processes for using energy more efficiently.

The article discusses the concentration of data centers in rural counties in the American northeast, particularly in Northern Virginia, which has been nicknamed "Data Centre Alley." The region is home to the largest concentration of data centers in the world, due to factors such as proximity to federal government services and affordable land. However, there are concerns about the environmental impact of these data centers, including noise, visual blight, energy consumption, strain on the power grid, and water usage. One controversial project, the Prince William Digital Gateway, has raised concerns about its impact on the environment and a nearby national park. The article suggests that the expansion of data centers in the USA could serve as a warning for other countries, such as the UK. [Extracted from the article]

Planet-scale applications are driving the exponential growth of the Cloud, and datacenter specialization is the key enabler of this trend. GPU- and FPGA-based clouds have already been deployed to accelerate compute-intensive workloads. ASIC-based clouds are a natural evolution as cloud services expand across the planet. ASIC Clouds are purpose-built datacenters comprised of large arrays of ASIC accelerators that optimize the total cost of ownership (TCO) of large, high-volume scale-out computations. On the surface, ASIC Clouds may seem improbable due to high NREs and ASIC inflexibility, but large-scale ASIC Clouds have already been deployed for the Bitcoin cryptocurrency system. This paper distills lessons from these Bitcoin ASIC Clouds and applies them to other large scale workloads such as YouTube-style video-transcoding and Deep Learning, showing superior TCO versus CPU and GPU. It derives Pareto-optimal ASIC Cloud servers based on accelerator properties, by jointly optimizing ASIC architecture, DRAM, motherboard, power delivery, cooling, and operating voltage. Finally, the authors examine the impact of ASIC NRE and when it makes sense to build an ASIC Cloud. [ABSTRACT FROM AUTHOR]

• On the basis of power efficiently and safe operating environment, a data-driven control framework is proposed for for the modelling and managing the thermal environment of air-cooled data centers. • An sub-space model predictive control based technique is proposed for regulating the power allocation of the server racks and the supply temperature of cold air. • A reasonable event-triggered law is designed to solve the problem of the low computational efficiency of the conventional sub-space control method. This paper presents a data-driven predictive control method for optimizing the energy consumption of air-cooled data centers with unknown system model parameters. First, based on the measurable data of the studied system, the subspace predictive control (SPC) method is adopted to improve the energy use efficiency of the data center by regulating the power allocation of the server racks and the supply temperature of cold air, while ensuring the safe operating environment of the electronic equipment. Furthermore, a reasonable event-triggered law is designed to solve the problem of the low computational efficiency of the conventional SPC method. The simulation results illustrate that the designed event-triggered law can improve the computational efficiency of the algorithm while maintaining the control performance of the algorithm, which verifies its application prospect in practice. [ABSTRACT FROM AUTHOR]

Surprising seismic activity on Mars The most powerful quake we have recorded on Mars was produced by tectonic forces from within its crust, not a meteor impact. The magnitude-4.7 quake was detected by NASA's InSight lander in 2022 and hints Mars is more seismically active than we thought (Geophysical Research Letters, doi.org/gsv8cs). Keep servers warm to save energy Data centres could save up to 56 per cent of the energy used on cooling by running at 41°C (106°F) rather than at 22°C (72°F), without significantly affecting performance (Cell Reports Physical Science, doi.org/ kz9v). [Extracted from the article]

Views Book Blood in the Machine Brian Merchant Little Brown NOBODY likes being described as someone who mindlessly opposes technology and is doomed to irrelevance. Instead of naively raging against all machines, the 19th-century Luddites were motivated by clear-eyed recognition of how some local entrepreneurs - whom Merchant describes as the "first tech titans" - deployed water-and steam-powered technologies such as power looms to churn out lower-quality yarn and cloth, replacing skilled artisan weavers with low-paid factory workforces doing dull and dangerous tasks. Those entrepreneurs knowingly chose to adopt automation for the sake of maximising business profits while destroying the "flexible and family-oriented" cottage industry lifestyle that had sustained hundreds of thousands of weavers and their families. [Extracted from the article]

Such estimates may be overblown, but evidence of rising power consumption from AI is all around. According to one analysis, if Google chose to shift to an entirely AI-powered search business, its electricity consumption could rival that of some countries (see page 11). [Extracted from the article]

The article takes a look at test system technology developments for aerospace and defense applications. It discusses the challenge for test and measurement equipment involving precision-guided munitions of the U.S. military. Test equipment include the 5560 3U VPX Xilinx Versal HBM adaptive compute acceleration platform (ACAP) processor from Mercury Systems, Tectronix 2 Series Mixed Signal Oscilloscope (MSO), Marvin Test Solutions MTS-3060A SmartCan and AnritsuSignal Quality Analyzer-R MO1900A.

The article discusses the use of Google's tensor processing units (TPUs) to improve performance per watt of deep neural networks in the company's datacenters, with better energy efficiency than central processing units (CPUs) and graphics processing units (GPUs) in similar technologies.

Chinese researchers have developed a DVD-sized disc with a storage capacity of 200 terabytes by storing data in three dimensions. The data is recorded in dots that are 54 nanometers wide, allowing for a higher data density than Blu-ray discs or modern hard drives. The researchers believe that this new optical disc could be used in large data centers, potentially reducing their size from a stadium to a room. The disc is made of a new light-sensitive material called AIE-DDPR, and the researchers are working on improving the writing speed and energy consumption of the method. [Extracted from the article]

Instead, it seems to me that it will be more practical to make silicon-based AIs mimic biological brains than to turn biological brains in vats into AIs. Perhaps we should be worrying about the welfare of future AIs just as much as we do about how AIs will affect human welfare in the future. So the idea is that living brains, or at least living brain tissue, could be much more efficient than silicon-based AI for some tasks. [Extracted from the article]

With the privacy protection increasingly being concerned, Data centralization often heavily causes a big risk of privacy protection, gradually, there is a prevailing trend to enhance the security performance by means of data decentralization, above all, for health care internet of things (IoT) data. Meanwhile, Federated learning has obvious privacy advantages compared to data center training on protecting privacy data. For this reason, a novel framework based on federated learning is presented in this paper, which is suitable for private and decentralized data sets, such as big data in healthy Internet of Things. Specifically, the main work of the puts forward framework includes: (1) Multi-center data collection of healthy Internet of Things. (2) healthy data analysis of Internet of Things. (3) privacy protection method for data of healthy Internet of Things. Finally, related experiments show that the proposed method is feasible, and compared with the traditional methods, it has significantly improved the performance in Quality of Service (QoS) and IoUs indicator. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to analyze the performance of a data center and thermal management by using phase change material (PCM). Numerical studies were conducted for two dimensional model of data center and installation of PCM at different locations. Design/methodology/approach: Finite volume method was used for the unsteady problem, while impacts of air velocity and PCM location on the flow field, thermal pattern variations and phase change dynamics were evaluated. Three different locations of the PCM were considered while air velocity was also varied during the simulation. Thermal field variations and cooling performance of the system for different PCM location scenarios were compared. Findings: It was observed that the installation of the PCM has significant impacts on the vortex formation, thermal field variation within the system and its performance. The left, right and top wall installation of the PCM changed the thermal patterns near the heat cell of the data centre. The phase change process is fast for the upper wall installation of the PCM, while the discrepancy of the melt fraction dynamics between different air flow at this position is minimum. The case where PCM placed in the upper wall at the highest air velocity is the best configuration in terms of heat storage. The utilization of PCM and changing its locations provide an excellent tool for thermal management and cooling performance of data centre. Originality/value: Results of this study can be used for initial design and optimization of cooling systems for thermal management of data centers while the importance of the high-performance computing becomes very crucial for the advanced simulations in different technological applications. [ABSTRACT FROM AUTHOR]

The article focuses on platform innovations with high-resolution sensors and high-performance signal processing embedded computing that are used in military applications. It highlights technological developments in field-programmable gate arrays (FPGA) and general-purpose graphics processing units (GPGPU). Other trends include fusion of traditional sensor interfaces and network-specific interfaces and incorporation of artificial intelligence (AI) and machine learning.

The article summarizes several articles presenting research on the use of distributed cluster scheduling for datacenters. Articles cited include "Large-Scale Cluster Management at Google With Borg" by A. Verma, et al. in the publication "Proceedings of the 10th European Conference on Computer Systems"; "Mesos: A Platform for Fine-Grained Resource Sharing in the Datacenter" by B. Hindman, et al. in the publication "Proceedings of the Usenix Conference on Networked Systems Design and Implementation:; and "Sparrow: Distributed, Low-Latency Scheduling" by K. Ousterhout, et al. in the publication "Proceedings of the Symposium on Operating Systems Principles."

The article offers information about the potential of artificial intelligence with in-package optical I/O. It mentions that in-package optical I/O as the breakthrough technology needed to allow disaggregated system architectures to meet the exploding demands of artificial intelligence and high-performance computing workloads.

The article discusses techniques for Web-scale computing in relation to autonomous operation of server infrastructure. Topics include the nature of Web-scale datacenters, the nature of operations in relation to server staff, and the nature of software for the stateless servers used as Web-scale. The deployment and testing of software at Web-scale is addressed.

Datacenter workloads demand high computational capabilities, flexibility, power efficiency, and low cost. It is challenging to improve all of these factors simultaneously. To advance datacenter capabilities beyond what commodity server designs can provide, we designed and built a composable, reconfigurable hardware fabric based on field programmable gate arrays (FPGA). Each server in the fabric contains one FPGA, and all FPGAs within a 48-server rack are interconnected over a low-latency, high-bandwidth network. We describe a medium-scale deployment of this fabric on a bed of 1632 servers, and measure its effectiveness in accelerating the ranking component of the Bing web search engine. We describe the requirements and architecture of the system, detail the critical engineering challenges and solutions needed to make the system robust in the presence of failures, and measure the performance, power, and resilience of the system. Under high load, the large-scale reconfigurable fabric improves the ranking throughput of each server by 95% at a desirable latency distribution or reduces tail latency by 29% at a fixed throughput. In other words, the reconfigurable fabric enables the same throughput using only half the number of servers. [ABSTRACT FROM AUTHOR]

In this article, various experts on computer science (CS) offer guides relating to the best of CS research. Particular focus is given to how to determine what papers are worth taking the time to read. Additional topics discussed include the ACM (Association for Computing Machinery), how datacenters are changing the way Web servers are designed and the notion of Network Functions Virtualization (NFV).

A retrospective study of 122 patients found that an adult patient developed tumour lysis syndrome while being treated with mogamulizumab for sezary syndrome. The patient eventually died due to the syndrome, which was attributed to the use of mogamulizumab. The study does not provide specific details about the patient's age, sex, dosage, route, or duration of treatment. [Extracted from the article]

The Internet of Things (IoT) is commonly deployed with devices of limited power and computation capability. A centralized IoT architecture provides a simplified management for IoT system but brings redundancy by the unnecessary data traffic with a data center. A decentralized IoT reduces the cost on data traffic and is resilient to the single-point-of-failure. The blockchain technique has attracted a large amount of research, which is redeemed as a perspective of decentralized IoT system infrastructure. It also brings new privacy challenges for that the blockchain is a public ledger of all digital events executed and shared among all participants. The decentralized IoT system relies on the leader election deeply to implement the decentralized communications among the distributed nodes. The conventional leader election must have a centralized authority, contrasting to the decentralization. As an alternative, self-tallying type schemes have been proposed in the literature for decentralized systems. These schemes suffer from adaptive and abortive issues. Also, some additional factors should be considered, such as the availability of candidate nodes. If the candidate node is unavailable after the voting phase due to being offline or ongoing tasks, the next available candidate should be elected. To accommodate such a need, in this paper, we propose a new leader election paradigm called voluntary-tallying leader election, which achieves the core requirements such as ballet secrecy, voter privacy and the additional feature of voluntary-tallying. We formalize the system and security models for this new election paradigm and present a secure and practical construction. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to present development of genetic algorithm (GA)-based framework aimed at minimizing data center cooling energy consumption by optimizing the cooling set-points while ensuring that thermal management criteria are satisfied. Design/methodology/approach: Three key components of the developed framework include an artificial neural network-based model for rapid temperature prediction (Athavale et al., 2018a, 2019), a thermodynamic model for cooling energy estimation and GA-based optimization process. The static optimization framework informs the IT load distribution and cooling set-points in the data center room to simultaneously minimize cooling power consumption while maximizing IT load. The dynamic framework aims to minimize cooling power consumption in the data center during operation by determining most energy-efficient set-points for the cooling infrastructure while preventing temperature overshoots. Findings: Results from static optimization framework indicate that among the three levels (room, rack and row) of IT load distribution granularity, Rack-level distribution consumes the least cooling power. A test case of 7.5 h implementing dynamic optimization demonstrated a reduction in cooling energy consumption between 21%–50% depending on current operation of data center. Research limitations/implications: The temperature prediction model used being data-driven, is specific to the lab configuration considered in this study and cannot be directly applied to other scenarios. However, the overall framework can be generalized. Practical implications: The developed framework can be implemented in data centers to optimize operation of cooling infrastructure and reduce energy consumption. Originality/value: This paper presents a holistic framework for improving energy efficiency of data centers which is of critical value given the high (and increasing) energy consumption by these facilities. [ABSTRACT FROM AUTHOR]

AN UNDERWATER data centre could start operating off the west coast of the US before the end of 2022. Unlike most land-based data centres, the servers in a pod are directly immersed in a special fluid similar to mineral oil that doesn't conduct electricity. "By placing the data centres subsea, we eliminate the electrically driven cooling which is 40 per cent of the power consumption", says Maxie Reynolds, co-founder of Subsea Cloud, the firm behind the project. [Extracted from the article]

Big Tech and civil war enthusiasts are clashing over efforts to build new data centres near historic US battlefields, writes Jeremy Hsu [ABSTRACT FROM AUTHOR]

The article describes the knowledge gained and lessons from developing and operating three software container management systems, the Borg, Omega, and Kubernetes, all from Internet search company Google. Topics discussed are the transformation of the data center from machine-oriented to being an application-oriented infrastructure, things to avoid when developing the systems such as port numbers management, lack of labeling and ownership uncertainty, as well as application configurations.

The article discusses the implications of high-speed non-volatile storage devices, also known as storage class memories (SCM), for the field of computer science. According to the authors, SCMs invalidate the common assumption that input/output (I/O) devices are slower than central processing units (CPUs). It is suggested that SCMs will also improve the relative performance of layers in systems and make much of the existing enterprise datacenter infrastructure obsolete. Horizontal scaling and workload-aware storage are discussed.

The article explores some of the fundamental issues related to cloud computing. Topics discussed include many components of a cloud computer that systematically deal with the failure of those components, a common architectural pattern used to manage transient failures and the use of simple analytic techniques to allow quantitative statements. Also provided are approaches to addressing frequent server-level failures in a data center, including the decomposition of the system into one or more tiers of servers.

Since the power consumption of data centers keeps increasing, a 48-V rack power distribution system replaces the conventional 12-V power bus to reduce the power delivery IR losses. Meanwhile, the 48 V needs conversion into 1 V or lower at the point-of-load for microprocessors. A 48V-to-12V DC-DC converter can serve as a first stage between the huge gap of 48V-to-1V, in a two-stage voltage regulator module (VRM). Thus, this paper presents a 3-phase resonant switched-capacitor (3Φ-ReSC) converter as the first stage of the VRM. Different from the reported solutions, 3-phase resonant operation reduces the current stress across each small-size GaN switch, and thus improves the power conversion efficiency. In addition, we also present the theoretical analysis and design procedures for the 3Φ-ReSC converter. We demonstrated the proposed 3Φ-ReSC converter with a 98% peak power efficiency at an output current of about 1 A, with a maximum output current of 10 A. [ABSTRACT FROM AUTHOR]

Zero-shot learning (ZSL) is a successful paradigm for categorizing objects from the previously unseen classes. However, it suffers from severe performance degradation in the generalized ZSL (GZSL) setting, i.e., to recognize the test images that are from both seen and unseen classes. In this article, we present a simple but effective mechanism for GZSL and more open scenarios based on a transfer-increment strategy. On the one hand, a dual-knowledge-source-based generative model is constructed to tackle the missing data problem. Specifically, the local relational knowledge extracted from the label-embedding space and the global relational knowledge, which is the estimated data center in the feature-embedding space, are concurrently considered to synthesize the virtual exemplars. On the other hand, we further explore the training issue for the generative models under the GZSL setting. Two incremental training modes are designed to learn directly the unseen classes from the synthesized exemplars instead of the training classifiers with the seen and synthesized unseen exemplars together. It not only presents an effective unseen class learning but also requires less computing and storage resources in practical application. Comprehensive experiments are conducted based on five benchmark data sets. In comparison with the state-of-the-art methods, both the generating and training processes are considered for virtual exemplars by the proposed transfer-increment strategy, which results in a significant improvement in the conventional and GZSL tasks. [ABSTRACT FROM AUTHOR]

The diode - an electronic component that lets electricity preferentially travel in one direction - is a fundamental part of the transistor, the foundational component of modern computing. Superconductors have no resistance and so no energy loss, but they don't work as diode components, since resistance is how diodes ensure that electricity travels in only one direction. Diodes and transistors are made from semiconductors that have electrical resistance, meaning energy is lost in the form of heat. [Extracted from the article]

This article describes Google's implementation of a distributed Cron service, serving the vast majority of internal teams that need periodic scheduling of compute jobs. During its existence, we have learned many lessons on how to design and implement what might seem like a basic service. Here, we discuss the problems that distributed Crons face and outline some potential solutions. Cron is a common Unix utility designed to periodically launch arbitrary jobs at user-defined times or intervals. We will first analyze the basic principles of Cron and its most common implementations and then review how an application such as Cron can work in a large, distributed environment, in order to increase the reliability of the system against single-machine failures. We describe a distributed Cron system that is deployed on a small number of machines, but is capable of launching Cron jobs on machines across an entire datacenter, in conjunction with a datacenter scheduling system. [ABSTRACT FROM AUTHOR]

• A new power-exponent function model based on the CPU utilization rate is put forward. • A hardware-aware CPU power measurement (HCPM) is designed and implemented. • Experimental results show the proposed HCPM is effective and efficient. The energy consumption of cloud servers accounts for about 25% of the total energy of cloud data centers. Reducing and optimizing this energy consumption is thus extremely important in energy saving in cloud data centers. Power model is fundamental in energy efficiency optimization scheduling for cloud computing. However, systems and tools for power measurement in the cloud computing environment are relatively scarce, and power models of cloud servers cannot keep up with the times. Therefore, we propose a new CPU power model named power-exponent function model (PEFM) is proposed, which provides higher accuracy in estimating the CPU power of the latest cloud servers than the current linear, polynomial and power function models. A novel hardware-aware CPU power measurement (HCPM) is also proposed, that can select an appropriate CPU power model through the launch year of CPU without power model training. For validating the efficacy of PEFM and HCPM, a set of experiments including OpenStack cluster experiment, based on a distributed energy meter (DEM) implemented by our team were conducted. The experimental results indicate that the proposed PEFM and HCPM not only improve the accuracy of CPU power estimation in cloud servers in cloud environment, but also reduce the difficulty of model training and simplify system deployment. [ABSTRACT FROM AUTHOR]

Purpose: Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future. Design/methodology/approach: Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms. Findings: The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance. Research limitations/implications: This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP. Practical implications: The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area. Originality/value: The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers. [ABSTRACT FROM AUTHOR]

And while agencies will pursue common enterprise-wide contracts for goods and services, OMB said they will do so "consistent with practices that grow small business participation in the federal marketplace and strengthen diversity and resilience". Keywords: Management omb gsa government contracting omb memo idiq contracts EN Management omb gsa government contracting omb memo idiq contracts N.PAG N.PAG 1 11/10/23 20231108 NES 231108 The Biden administration unveiled a new plan to find contract savings and better performance for the federal government. [Extracted from the article]

Sensor–cloud system, as one of the vital components of the Internet of Everything, has increasingly gained popularity since it bridges the physical and cyber worlds. In the smart city, sensing devices are deployed to monitor the environment and the data aggregate at the roadside Aggregation Devices (ADs). Then, Mobile Vehicles (MVs) submit the data to the data center in an opportunistic routing way when passing ADs. We propose a Content based Intelligent Trust Evaluation (CITE) scheme for trustworthy data collection over large-scale sensor-cloud systems. In CITE scheme, unmanned Mobile Electric Vehicles (MEVs) are employed to visit some sensing devices and collect their data along the designed routing path. Then, a delicate comparison algorithm is proposed to determine the credibility of devices' data operations, and trust evaluation is based on it. Similarly, the trust of MVs is obtained by comparing the data reported from ADs with the data submitted to the data center. Moreover, to reduce the cost of MEVs, we also design a path planning algorithm. The simulation results show that the CITE scheme can identify reliable sensing devices and MVs with a rate of 87.3% and 100% and increase the collection rate by 25.2% on average compared with the previous strategies. [ABSTRACT FROM AUTHOR]