Next Generation Data Center design under Smart Grid

A smart grid is an intervention technology for the massive energy demand of the world today. It combines cyber-physical technologies, information communication technology, and electrical power networks from the generating company stations to the end-users while ensuring bidirectional communication among the actors. The smart grid is a complex growing technology that is yet to reach its maturity state. This paper seeks to examine the literature on the state of the art of smart grid technology both from the industry perspective and from academia. To this end, a literature review with a qualitative deductive approach built on the National Institute of Standards and Technology (NIST) guideline and the simplified International Telecommunication Union Telecommunication Standardization Sector (ITU-T) five-domain model were used as a guide to this research. Furthermore, the paper reviewed Smart Grid data centre topologies and identified prospects in spine-leaf architecture as a promising architecture that can be adapted in a smart grid ecosystem data centre design. The literature was searched from the databases: IEEE Xplore Digital Library, Springer Link Digital Library, and Google Scholar, IET Digital Library, Frontiers Library, ACM Digital Library repositories resulting in 151 papers after several exclusions. The work reviewed relevant literatures published from 2002 to 2021 and grouped the reviewed papers according to the key domains of the NIST/ITU-T model. Based on the evaluated literature, the need for more built-in predictive learning curves in smart grid systems and robust Smart grid architecture with enhanced data centre design for Smart grid systems is observed and recommended Keywords: Smart Grid, Smart Metre, Data Centre Computing, Distributed Energy, Protocols

With the rapid development of national economy, our demand for power resources has also increased rapidly. The traditional power grid can not be achieved operational status of equipment for effective monitoring and control, we will not be able to ensure the quality and quality of electricity service. Cloudbased build smart grid information platform enables gathering the parameter of grid operation state, greatly increasing the economic efficiency of power enterprises. Firstly, cloud computing and smart grid briefly described, and then pointed out that cloud computing applications in the smart grid information platform, and specialized of cloud-based smart grid information platform, in order for the power grid enterprises to enhance their level of service and provide effective reference. KEYWORD: cloud computing; smart power grids; information platform; Application 4th International Conference on Mechanical Materials and Manufacturing Engineering (MMME 2016) © 2016. The authors Published by Atlantis Press 202 3 THE MAIN PROBLEM IS STILL THE SMART GRID INFORMATION PLATFORM FACING The transition to a cloud computing data center. Our data center because of the different regions and the degree of information presents different characteristics, some data centers already have a basic cloud computing capabilities, but most data centers still remain in the initial level, to ensure the normal operation of the existing data center power under the premise, gradual transition to cloud computing data center in order to meet future requirements of the development of smart grid. Restricting data transmission problem. State Grid Corporation between provincial branches and there are a lot of data needs to be transmitted, will bring massive data transmission efficiency decreases, taking into account the load balancing device between the cloud node, thus building a wide area network channels to resolve data transmission problem. Security of data transmission. Data Center for Cloud Computing power companies to build internal private cloud, capable of self-maintenance and management, system wide area network data transmission services, according to the third security zone defined security partition, and install proprietary equipment production area and external public network isolation . 4 CLOUD COMPUTING APPLICATIONS IN THE SMART GRID INFORMATION POLICY PLATFORM Integrate and optimize the management of heterogeneous resources. Among the smart grid systems, data resources, information systems between various platforms and mutually dispersed, severe heterogeneity, thus leading to the integration of the quality of information sharing to increase difficulty, unable to effectively improve network management efficiency for the power distribution system electrical work quality management and marketing operations system maintenance upgrade will not be able to effectively meet demand (Jie Yang, 2014). Cloud computing technology enables the power system to effectively integrate the various business data and computing resources on the basis of information for business collaboration platform built on effective, able to satisfy the huge demand for smart grid information resource sharing. Cloud computing network virtualization and application virtualization technology, the server virtualization technology and other resources to achieve each service abstraction, and then realize the difference between the system and the software effectively eliminated by the appropriate method to achieve the effective integration of information resources, and then to optimize the management, greatly improving the efficiency of heterogeneous resources management applications. Distributed storage and management of large volume of data. After application of smart grid information platform construction, customer service requests varied, huge data volume information brought it to the storage and management of data provides a great challenge. Cloud computing technology in general face amount of data each smart grid system and unit collected using forms distributed storage of data to achieve the effective storage, greatly to ensure the security and reliability of data storage. GFS effective use of technology with each node, the master server is responsible for the effective management of the whole file system, the file system and complete the work of the metadata stored in the data block is the main server for data storage block sliced, and by saving three or more redundant backup storage. At the same time, client access and complete access to the main block server information. Fast Power System Parallel Computation and Treatment. Smart grids and information platform for the large volume of data to provide stable operation of the power grid data base, but more critical is the analysis and design of each system operating data, planning and decision-making, and even failures and transient stability, state estimation and intelligent a variety of computing and content analysis and decision-making process, its huge computing needs, general computing system can not reach its goal (Wang, Mengxue, 2015). Cloud computing technology through parallel computing technology has greatly enhanced parallel processing capability of the power system, which provides parallel programming model makes more simple and efficient parallel algorithms. MapReduce as Google made an important parallel programming model, and its role in large data sets in parallel computing plays a very prominent. Parallel processing job results by the client to achieve effective user submitted, via decomposition automated master role, the corresponding task scheduling to working nodes and nodes work completed by the specific calculations and perform the appropriate task. 5 SMART GRID INFORMATION PLATFORM CLOUD COMPUTING ANALYSIS Cloud Computing Smart Grid Information Platform Architecture. Smart grid technology information platform architecture cloud computing include the following several levels and aspects (Yan Cui, 2015): First, that the platform infrastructure layer is the integration of the various hardware resources and related management capabilities of virtualized using virtual technology to achieve the corresponding hardware devices such as computers and network storage devices abstraction, and then complete the automation and optimization of resource data and load management; secondly, the main platform for the integration of the various layers of software

Research and Technologies for next-generation high-temperature data centers – State-of-the-arts and future perspectives

Data centres are large energy consumers, which have become more energy efficient in recent years due to increased awareness of opportunities, increasing energy costs and corporate social responsibility pressures. A lifecycle assessment approach identifies two other significant areas of impact: the embodied impact of IT equipment and mechanical and electrical plant, and the electricity source used in operational and embodied processes. Many data centre operators publicise their energy efficiency, some also report on their carbon footprint. However, there is a need for simple tools in order to help operators better understand and quantify the embodied impact and inform green procurement. Focussing purely on energy efficiency may cause a burden shift, e.g. by replacing equipment with more efficient equipment but increasing the embodied impact. The total environmental impact could remain the same/increase, but with the perception of a ‘greener’ data centre. Although currently there is limited data available for data centre life cycle assessments and the process is resource intensive, research has identified which factors significantly impact a facility’s environmental impact. This knowledge should be used in the design process and throughout the data centre lifecycle to minimise data centre environmental impact. Practical application: As the data centre industry continues to grow and its sustainability receives closer scrutiny, it is important to increase awareness of where its highest environment impacts lie and analyse the factors which influence this. This can help inform policy and decision-making to support the design and operation of data centres which are truly more sustainable. It is important that this research is not just theoretical but can translate into practical actions which can be implemented in a cost-effective manner for the benefit of everyone. The current focus in industry has been energy consumption and energy efficiency; many practices which were considered innovative a few years ago have now become standard best practice. It is time to examine which other areas should be prioritised for improvement.

Relevance. Data centers are a specialized facility that is an interconnected system of IT infrastructure, engineering infra-structure, equipment (server and network) and parts of which are located in a building or room connected to external networks, both engineering and telecommunications. Due to the significant heat generation of these systems, there is a need to increase the efficiency of cooling systems through efficient heat recovery.The purpose. Calculation of the energy balance of a typical data center designed for operation in central Russia.Methods. The developed energy model of a data center is a mathematical description of all energy processes in a building, including heat transfer processes, the effects of ventilation and air conditioning, the operation of lighting, electrical appliances and other equipment, and the operation of engineering systems.Results. According to the simulation results, the specific energy consumption was 1,353 kWh/m2, the specific annual cost of energy resources was 8,572.90 rubles/m2. The following key results were obtained: energy consumed by data center modules – 38,399.53 MWh/year; energy consumed by IT equipment – 31,685.20 MWh/year; PUE (it represents the ratio of the total energy consumed by the data center to the energy directly used by the IT equipment) – 1.21.Conclusion. Data on annual energy consumption, the cost of consumed energy resources and the amount of CO2 released into the atmosphere during the production of energy resources were obtained. A monthly energy consumption chart has been developed by category (heating, cooling, fans, heat recovery, pumps, interior lighting, outlet equipment, servers). In the course of further research, it is planned to consider priority schemes for the utilization of thermal energy of the data center.

1 - Data center architectures

Chapter 4 - Design from the top-down

The advent of the big data era, the rapid development of mobile internet, and the rising demand of cloud computing services require increasingly more compute capability from their data center. This compute increase will most likely come from higher rack and room power densities or even construction of new Internet data centers. But an increase in a data center’s business-critical IT equipment (servers, hubs, routers, wiring patch panels, and other network appliances), not to mention the infrastructure needed to keep these devices alive and protected, encroaches on another IT goal: to reduce long-term energy usage. Large Internet Data Centers are looking at every possible way to reduce the cooling cost and improve efficiency. One of the emerging trends in the industry is to move to higher ambient data center operation and use air side economizers. However, these two trends can have significant implications for corrosion risk in data centers. The prevailing practice surrounding the data centers has often been “The colder, the better.” However, some leading server manufacturers and data center efficiency experts share the opinion that data centers can run far hotter than they do today without sacrificing uptime, and with a huge savings in both cooling related costs and CO2 emissions. Why do we need to increase the temperatures? To cool data center requires huge refrigeration system which is energy hog and also cost of cooling infrastructure, maintenance cost and operation cost are heavy cost burden. Ahuja et al [1] studied cooling path management in data center at typical operating temperature as well as higher ambient operating temperatures. High Temperatures and Corrosion Resistance technology will reduce the refrigeration output and how this innovation will open up new direction in data centers. Note that, HTA is not to say that the higher the better. Before embracing HTA two keys points need to be addressed and understood. Firstly, server stability along with optimal temperature from data center perspective. Secondly, corrosion resistant technology. With Fresh air cooling the server has to bear with the seasons and diurnal variation of temperatures and these can be over 35 degree C, therefore to some extent, we have to say, HTA design is the premise of corrosion resistant design. In this paper, we present methods to realize precise HTA operation along with corrosive resistant technology. This is achieved through an orchestrated collaboration between the IT and cooling infrastructures.

Today, there is a generalized standard usage of internet for all.The devices via multiple technologies that facilitates to provide few communication methods to scholars to work with. By forming multiple paths in the data center network, latest generation data centers offer maximum bandwidth with robustness. To utilize this bandwidth, it is necessary that different data flows take separate paths. In brief, a single-path transport seems inappropriate for such networks. By using Multipath TCP, we must reconsider data center networks, with a diverse approach as to the association between topology, transport protocols, routing. Multipath TCP allows certain topologies that single path TCP cannot use. In newer generation data centers, Multipath TCP is already deployable using extensively deployed technologies such as Equal-cost multipath routing. But, major benefits will come when data centers are specifically designed for multipath transports. Due to manifold of technologies like Cloud computing, social networking, and information networks there is a need to deploy the number of large data centers. While Transport Control Protocol is the leading Layer-3 transport protocol in data center networks, the operating conditions like high bandwidth, small-buffered switches, and traffic patterns causes poor performance of TCP. Data Center TCP algorithm has newly been anticipated as a TCP option for data centers which address these limitations. It is worth noting that traditional TCP protocol.

Maliciously-injected power load, a.k.a. power attack, has recently surfaced as a new egregious attack vector for dangerously compromising the data center availability. This paper focuses on the emerging threat of power attacks in a multi-tenant colocation data center, an important type of data center where multiple tenants house their own servers and share the power distribution system. Concretely, we discover a novel physical side channel --- a voltage side channel --- which leaks the benign tenants' power usage information at runtime and helps an attacker precisely time its power attacks. The key idea we exploit is that, due to the Ohm's Law, the high-frequency switching operation (40~100kHz) of the power factor correction circuit universally built in today's server power supply units creates voltage ripples in the data center power lines. Importantly, without overlapping the grid voltage in the frequency domain, the voltage ripple signals can be easily sensed by the attacker to track the benign tenants' runtime power usage and precisely time its power attacks. We evaluate the timing accuracy of the voltage side channel in a real data center prototype, demonstrating that the attacker can extract benign tenants' power pattern with a great accuracy (correlation coefficient = 0.90+) and utilize 64% of all the attack opportunities without launching attacks randomly or consecutively. Finally, we highlight a few possible defense strategies and extend our study to more complex three-phase power distribution systems used in large multi-tenant data centers.

The 2007 US EPA report to Congress (US EPA, 2007) on the state of energy consumption in data centers brought to light the true energy inefficiencies built into today’s data centers. Marquez et al. (2008) conducted an initial analysis on the productivity of a Pacific Northwest National Lab computer using The Green Grid’s Data Center Energy Productivity metric (The Green Grid, 2008). Their study highlights how the Top500 ranking of computers disguises the serious energy inefficiency of today’s High Performance Computing data centers. In the rapidly expanding Cloud Computing space, the race will be won by the providers that deliver the lowest cost of computing — such cost is heavily influenced by the operational costs incurred by data centers. As a means to address the urgent need to lower the cost of computing, solution providers have been intensely focusing on real-time monitoring, visualization, and control/management of data centers. The monitoring aspect involves the widespread use of networks of sensors that are used to monitor key data center environmental variables such as temperature, relative humidity, air flow rate, pressure, and energy consumption. Such data is then used to visualize and analyze data center problem areas (e.g., hotspots), which is then followed by control/management actions designed to alleviate such problem areas. The authors have been researching the operational benefits of a network of sensors tied in to a software package that uses the data to visualize, analyze, and control/manage the data center cooling system and IT Equipment for maximum operational efficiency. The research is being conducted in a corporate production data center that is networked in to the authors’ company’s global network of data centers. Results will be presented that highlight the operational benefits that are realizable through real-time monitoring and visualization.

High-speed routers and high-performance data centers share a common system-level architecture in which multiple processing nodes are connected by an interconnection network for high-speed communications. Load balancing is an important technique for maximizing throughput and minimizing delay of the interconnection network. In this thesis, efficient load balancing schemes are designed and analyzed for next-generation routers and data centers.
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\nIn high-speed router design, two preferred switch architectures are input-queued switch and load-balanced switch. In an input-queued switch, time-domain load balancing can be carried out by an iterative algorithm that schedules packets for sending in different time slots. The complexity of an iterative algorithm increases rapidly with the number of scheduling iterations. To address this problem, a single-iteration scheduling algorithm called D-LQF is designed, in which exhaustive service policy is adopted for reusing the matched input-output pairs in the previous time slots to grow the match size. 
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\nUnlike an input-queued switch, a load-balanced switch consists of two stages of crossbar switch fabrics, where load balancing is carried out in both time and space domains. Among various load-balanced switches, the feedback-based switch gives the best delay-throughput performance. In this thesis, the feedback-based switch is enhanced in three aspects. Firstly, we focus on reducing its switch fabric complexity. Instead of using crossbars, a dual-banyan network is proposed. The complexity of dual-banyan can be further reduced by merging the two banyans to form a Clos network, resulting in a Clos-banyan network. Secondly, we target at improving the delay performance of the feedback-based switch. A Clos-feedback switch architecture is devised where each switch module in the Clos network is a small feedback-based switch. With application-flow based load balancing, packet order is ensured and the average packet delay is reduced from O(N) to O(n), where N and n are the switch and switch module sizes, respectively. Thirdly, we extend the feedback-based switch to support multicast traffic. Based on the notion of pointer-based multicast VOQ, an efficient multicast scheduling algorithm with packet replication at the middle-stage ports only is proposed. In order to provide close-to-100% throughput for any admissible multicast traffic patterns, a three-stage implementation of feedback-based switch is also designed.
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\nIn designing load balancing schemes for data centers, we focus on the most popular fat-tree based data centers. Notably, packet-based load balancing is widely considered infeasible for data centers. This is because the associated packet out-of-order problem will cause unnecessary TCP fast retransmits, and as a result, severely undermine TCP performance. In this thesis, we show that if packet-based load balancing is performed properly, the packet out-of-order problem can be easily addressed by slightly increasing the number of duplicate ACKs required for triggering fast retransmit. Admittedly, in case of a real packet loss, the loss recovery time will be increased. But our simulation results show that such an increase is far less than the reduction in the network queueing delay (due to a better load-balanced network). As compared to a flow-based load balancing scheme, our packet-based scheme consistently provides significantly higher goodput and noticeably smaller delay.

Modern-day data center administrators are finding it increasingly difficult to lower the costs incurred in mechanical cooling of their IT equipment. This is especially true for high-performance computing facilities like Artificial Intelligence, Bitcoin Mining, and Deep Learning, etc. Airside Economization or free air cooling has been out there as a technology for a long time now to reduce the mechanical cooling costs. In free air cooling, under favorable ambient conditions of temperature and humidity, outside air can be used for cooling the IT equipment. In doing so, the IT equipment is exposed to sub-micron particulate/gaseous contaminants that might enter the data center facility with the cooling airflow. The present investigation uses a computational approach to model the airflow paths of particulate contaminants entering inside the IT equipment using a commercially available CFD code. A Discrete Phase Particle modeling approach is chosen to calculate trajectories of the dispersed contaminants. Standard RANS approach is used to model the airflow in the airflow and the particles are superimposed on the flow field by the CFD solver using Lagrangian particle tracking. The server geometry was modeled in 2-D with a combination of rectangular and cylindrical obstructions. This was done to comprehend the effect of change in the obstruction type and aspect ratio on particle distribution. Identifying such discrete areas of contaminant proliferation based on concentration fields due to changing geometries will help with the mitigation of particulate contamination related failures in data centers.

advent of the big data era, the rapid development of mobile internet, and the rising demand of cloud computing services require increasingly more compute capability from their data center. This compute increase will most likely come from higher rack and room power densities or even construction of new Internet data centers. But an increase in a data center's business-critical IT equipment (servers, hubs, routers, wiring patch panels, and other network appliances), not to mention the infrastructure needed to keep these devices alive and protected, encroaches on another IT goal: to reduce long-term energy usage. Large Internet Datacenters are looking at every possible way to reduce the cooling cost and improve efficiency. One of the emerging trends in the industry is to move to higher ambient datacenter operation and use air side economizers. However, these two trends can have significant implications for corrosion risk in data centers. prevailing practice surrounding the data centers has often been The colder, the However, some leading server manufacturers and data center efficiency experts share the opinion that data centers can run far hotter than they do today without sacrificing uptime, and with a huge savings in both cooling related costs and CO2 emissions. Why do we need to increase the temperatures? To cool data center requires huge refrigeration system which is energy hog and also cost of cooling infrastructure, maintenance cost and operation cost is heavy cost burden. This paper describes how HTA and Corrosion Resistance technology will reduce the refrigeration output and how this innovation will open up new direction in data centers. Note that, HTA is not to say that the higher the better. Before embracing HTA two keys points need to be addressed and understood. Firstly, server stability along with optimal temperature from data center perspective. Secondly, corrosion resistant technology. With Fresh air cooling the server has to bear with the seasons and diurnal variation of temperatures and these can be over 35 degree C, therefore to some extent, we have to say, HTA design is the premise of corrosion resistant design. In this paper, we present methods to realize precise HTA operation along with corrosive resistant technology. This is achieved through an orchestrated collaboration between the IT and cooling infrastructures.

This research project, which was conducted during the Summer and Fall of 2011, investigated some commercially available assessment tools with a focus on IT equipment to see if such tools could round out the DC Pro tool suite. In this research, the assessment capabilities of the various tools were compiled to help make “non-biased” information available to the public. This research should not be considered to be exhaustive on all existing vendor tools although a number of vendors were contacted. Large IT equipment OEM’s like IBM and Dell provide their proprietary internal automated software which does not work on any other IT equipment. However, found two companies with products that showed promise in performing automated assessments for IT equipment from different OEM vendors. This report documents the research and provides a list of software products reviewed, contacts and websites, product details, discussions with specific companies, a set of recommendations, and next steps. As a result of this research, a simple 3-level approach to an IT assessment tool is proposed along with an example of an assessment using a simple IT equipment data collection tool (Level 1, spreadsheet). The tool has been reviewed with the Green Grid and LBNL staff. The initial feedback has been positive although further refinement to the tool will be necessary. Proposed next steps include a field trial of at least two vendors’ software in two different data centers with an objective to prove the concept, ascertain the extent of energy and computational assessment, ease of installation and opportunities for continuous improvement. Based on the discussions, field trials (or case studies) are proposed with two vendors – JouleX (expected to be completed in 2012) and Sentilla.