Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

PROSPECTS AND ISSUES FOR FUEL CELLS WITH FREIGHT RAIL TRANSPORTATION

Recent changes in the cost and availability of natural gas (NG) as compared to diesel have sparked interest at all levels of the commercial shipping sector. In particular, Class 1 heavy-duty rail has been researching NG as a supplement to diesel combustion. This study investigates the relative economic and emissions advantage of making use of the energy efficiencies if combustion is circumvented altogether by use of fuel cell (FC) technologies applied to NG. FC technology for the transport sector has primarily been developed for the private automobile. However, FC use in the automobile sector faces considerable economic and logistical barriers such as cost, range, durability, and refueling infrastructure. The heavy-duty freight sector may be a more reasonable setting to introduce FC technology to the transportation market. The industry has shown interest in adopting NG as a potential fuel by already investing in NG infrastructure and locomotives. The two most promising FC technologies are proton exchange membrane fuel cells (PEMFCs) and solid oxide fuel cells (SOFCs). SOFCs are more efficient and capable of accepting any kind of fuel, which makes them particularly attractive. The rail industry can benefit from the adoption of FC technology through reduced costs and emissions, as well as limiting dependence on diesel, which accounts for a large portion of operation expenses for Class 1 railroads. This report provides an economic feasibility analysis comparing the use of PEMFCs and SOFCs in heavy freight rail transport applications. The scope is to provide insight into which technologies could be pursued by the industry and to prioritize technologies that need further development. Initial results do not show economic potential for NG and fuel cells in locomotion, but some minimal potential for reduced emissions is seen. Various technology configurations and market scenarios analyzed could provide savings if the price of LNG is decreased and the price of diesel increases. The most beneficial areas of needed research include technology development for the variable output of SOFCs, and hot start-up optimization.