Automation for structured cabling system in data centers using Building Information Modelling

Two-phase liquid-immersion data center cooling system: Experimental performance and thermoeconomic analysis

A model predictive control for a multi-chiller system in data center considering whole system energy conservation

The State-of-charge (SOC) is a critical parameter for the battery, which is a hot research in areas such as new energy vehicles, but the research on lead-acid batteries as backup power in Uninterrupted Power System in data center has rarely been done. In this paper, for the first time, a model named Poly-Nernst, which is a combination of polynomial model and Nernst battery model, is proposed to estimate the SOC of the battery working in data center. Extended Kalman Filtering method is adopted for SOC online simulation, whose estimating results are compared with traditional Ah method. The simulation on the real UPS shows that the EKF estimating error is much smaller than that of Ah method with no accumulated integral error. To improve the adaptive capability of established the Poly-Nernst model, multi-model adaptive estimation based on EKF algorithm is designed and the experimental results show the MMAE model estimation is much better than any one of a single EKF estimation. To balance the model complexity and estimating accuracy, the experimental results show that a 3-model EKF estimation model is suggested to be appropriate. This SOC estimating method provides technical instructions for the maintenance of the battery system in data center.

33 - Structured cabling systems and voice distribution frames

Due to the advancement of the telecommunication and information technology (IT) industry, internet data centers (IDCs) have become widespread in the public and private sectors. As such, energy demand in the center has also become increasingly prominent. Several technologies on energy management have been studied to determine the options available to minimize the energy required to operate the data center as well as reduce greenhouse gas emissions. The cooling system is required to remove the high heat dissipated by the IT electronic components especially the servers in order to ensure safe and reliable working condition. However, it utilizes more than one-third of the total energy consumption in the data center. In this study, the energy efficiency technologies that are usually applied to cooling systems in data centers were reviewed. The aim is to find out the strategies that will reduce the energy consumption of the cooling system since the cooling demand in data center is all year round. Prior to that, the performance metric tool that is mostly used in analyzing data center efficiency was discussed. The conventional cooling system technologies that are utilized in data centers were also provided. Lastly, innovative cooling technologies for future solutions in data centers were discussed.

Various uncertainties self-correction method for the supervisory control of a hybrid cooling system in data centers

Data center downtime causes losses of millions of dollars. Maintaining high availability at all times is very critical to data centers. The distribution system with higher number of components is more likely to fail, resulting in increased downtime. This study presents a 380V DC powering option for data center distribution system, as the number of power conversion stages is less compared to the AC system. This study aims at comparing reliabilities of typical 480V AC distribution architecture against 380V DC architecture. Reliability assessment was done for both AC and DC sytems complying with Tier IV standard, as most of the data center uses Tier IV standard in their distribution system. The analysis was done for different level of redundancy (for eg. N, N+1, N+2) in the UPS system for both AC and DC systems. The reliability data was obtained from IEEE 493 Gold Book. Monte carlo simulation method was used to perform the reliability calculations. The simulation results showed that the 380V DC distribution system has higher level of reliability than conventional 480V ac distribution system in data centers but only up to certain level of redundancy in the UPS system. The reliability level of AC system will approach the reliability level of a DC system when a very high level of redundancy in the UPS system is considered, but this will increase the overall cost of the data center.

Two data centers in this study were within a co-location facility located on the sixth floor of a multi-story building in downtown Los Angeles, California. The facility had 37,758 gross square feet floor area with 2-foot raised-floors in the data services area. The two data centers were designated as the west data center (DC No.18) and the east data center (DC No.19). The study found that 56% of the overall electric power was consumed by sixth floor critical loads in both data centers, 33% of the power was consumed by HVAC systems, 3% of the power was consumed by UPS units, 3% of the power was for generator losses, and the remaining 5% was used by lighting and miscellaneous loads in the building. The power density of installed computer loads (rack load) in the two data centers was 20 W/ft{sup 2} and 56 W/ft{sup 2}, respectively. The power density was relatively lower in DC No.18 compared to other data centers previously studied. In addition, HVAC to IT power demand ratio was 0.6 in DC No.18 in this study, and was 0.4 in DC No.19. Two out of three chillers were running at a low partial load, making the operation very energy inefficient. The operation and control of the chillers and air-handling units should be optimized while providing sufficient cooling to the data centers. Although arranging hot aisle/cold aisle design to separate airflow streams would be difficult in such a co-location data center, optimizing air distribution should be pursued. General recommendations for improving overall data center energy efficiency include improving the design, operation, and control of mechanical systems serving the data centers with various critical loads in place. This includes chiller operation, chilled water system, AHUs, airflow management and control in data centers. Additional specific recommendations or considerations to improve energy efficiency are provided in this report.

The heat dissipated by large servers and switching equipment is reaching levels that make it very difficult to cool these systems in data centers or telecommunications rooms. Some of the highest powered systems are dissipating upwards of 4000 watts/ft2(43,000 watts/m2) based on the equipment footprint. When systems dissipate this amount of heat and then are clustered together within a data center significant cooling challenges can result. This paper describes the thermal profile of 3 data center layouts (2 are of the same data center but different points in time with a different layout). Detailed measurements of all three were taken: electronic equipment power usage; perforated floor tile airflow; cable cutout airflow; computer room air conditioning (CRAC) airflow, temperatures and power usage; electronic equipment inlet air temperatures. Although the detailed measurements were recorded this paper will focus at the macro level results of the data center to see if some patterns present themselves that might be helpful for future guidelines of data center layout for optimized cooling. Specifically, areas of the data center where racks have similar inlet air temperatures are examined relative to the rack and CRAC unit layout.

A data-driven approach to simultaneous fault detection and diagnosis in data centers

We review novel optical fibers for space division multiplexed short-reach transmission systems in data center applications. Both linear array multicore fibers and elliptical core few mode fibers are discussed and transmission results are presented.

In recent years, data centers have emerged to be an increasingly important computing infrastructure. It is shown that wireless sensor networks (sensor nets) can provide fine-grained measurements in data centers, and achieve better control of the data center platform for energy efficiency. However, the usage of sensor nets has so far been limited to auxiliary functions, such as sensory data collection across a data center. We argue that the combined computational and networking capability of a sensor network enables it to interact with the clusters in a much more sophisticated way and enhance essential functions in a data center. We have designed a Cluster-Area Sensor Network (CASN) to improve the cluster management and operational security in the system. Implemented with TelosB motes, CASN can be easily deployed in a cluster, with sensor nodes attached in an ad hoc manner to servers, and provides key system functions including cluster-wide command dissemination and verification of physical presence. Experimental results show that CASN has 85% success rate in verifying physical locations of servers with coarse-grained localization when the threshold is 3 meters, and incurs small latency in cluster-wide command dissemination.

Processing a workflow (or a job) created by a user, who can be a researcher from a scientific laboratory or an analysis from a commercial organization, is the main functionality that a data center or a high-performance computing center is generally expected to provide. It can be accomplished with a single core processor and rather small amount of memory if the problem is adequately small while it may require thousands of nodes to solve a complicated problem and peta-bytes of storage for its output. Also specific applications on various platforms are required in general by users for resolving the problems appropriately. In this aspect, a data center should operate non-homogeneous systems for resource management, so-called batch system, in which it results in inefficient resource utilization due to stochastic behavior of user activity. Implementation of virtualization for resource management, e.g. Cloud Computing, is one of promising solutions recently arising, however, it results in the increase of complexity of the system itself as well as the system administration because it naturally implies the intervention of virtualization stack, e.g. hypervisor, between Operating System and applications for resource management. In this paper, we propose a new conceptual design to be implemented as a pre-scheduler capable to insert user submitted jobs dedicated to a specific batch system into available resources managed by other kind of batch systems. The proposed design features transparency in between clients and batch systems, accuracy in terms of monitoring and prediction on the available resources, and scalability for additional batch systems. We suggest the implementation example of the conceptual design based on the scenario established from our experience of operating a data center.

We present a data mining approach to model the cooling infrastructure in data centers, particularly the chiller ensemble. These infrastructures are poorly understood due to the lack of “first principles” models of chiller systems. At the same time, they abound in data due to instrumentation by modern sensor networks. We present a multi-level framework to transduce sensor streams into an actionable dynamic Bayesian network model of the system. This network is then used to explain observed system transitions and aid in diagnostics and prediction. We showcase experimental results using a HP data center in Bangalore, India.

The constant increase in operating costs of data centers (DC) is the driving force behind innovations to increase their efficiency. Today, one of the newest ways to improve the design and functionality of data centers is the integration of building information modeling (BIM). The aim of the work is to analyze the possibilities of increasing the efficiency of the data center design stage based on the use of BIM-technologies, and the task is to design data center systems of all levels of certification of the Uptime Institute. The integration of the capabilities of BIM-technologies during design increases the efficiency of both the general design of the facility and special design indicators of data centers. This article sets out the basics of integrating BIM and data centers, a working mechanism for their interaction when designing the required level of functionality of the Uptime Institute with the design, as well as the possibility of using BIM-data from the design stage in the subsequent stages of installation and operation.