Deployment of a Hybrid Multicast Switch in Energy-Aware Data Center Network: A Case of Fat-Tree Topology

Recently, energy efficiency or green IT has become a hot issue for many IT infrastructures as they attempt to utilize energy-efficient strategies in their enterprise IT systems in order to minimize operational costs. Networking devices are shared resources connecting important IT infrastructures, especially in a data center network they are always operated 24/7 which consume a huge amount of energy, and it has been obviously shown that this energy consumption is largely independent of the traffic through the devices. As a result, power consumption in networking devices is becoming more and more a critical problem, which is of interest for both research community and general public. Multicast benefits group communications in saving link bandwidth and improving application throughput, both of which are important for green data center. In this paper, we study the deployment strategy of multicast switches in hybrid mode in energy-aware data center network: a case of famous fat-tree topology. The objective is to find the best location to deploy multicast switch not only to achieve optimal bandwidth utilization but also to minimize power consumption. We show that it is possible to easily achieve nearly 50% of energy consumption after applying our proposed algorithm.

Active suspension development based on energy analysis

This research focuses on developing active suspension optimal controllers for two linear and non-linear half-car models. A detailed comparison between quarter-car and half-car active suspension approaches is provided for improving two important scenarios in vehicle dynamics, i.e. ride quality and road holding. Having used a half-car vehicle model, heave and pitch motion are analyzed for those scenarios, with cargo mass as a variable. The governing equations of the system are analysed in a multi-energy domain package, i.e., 20-Sim. System equations are presented in the bond-graph language to facilitate calculation of energy usage. The results present optimum set of gains for both ride quality and road holding scenarios are the gains which has derived when maximum allowable cargo mass is considered for the vehicle. The energy implications of substituting passive suspension units with active ones are studied by considering not only the energy used by the actuator, but also the reduction in energy lost through the passive damper. Energy analysis showed less energy was dissipated in shock absorbers when either quarter-car or half-car controllers were used instead of passive suspension. It was seen that more energy could be saved by using half-car active controllers than the quarter-car ones. Results also proved that using active suspension units, whether quarter-car or half-car based, under those realistic limitations is energy-efficient and suggested.

Sensor Intelligence for Tackling Energy-Drain Attacks on Wireless Sensor Networks

In this paper we propose a model for intelligent agents (sensors) on a Wireless Sensor Network to guard against energy-drain attacks in an energy-efficient and autonomous manner. This is intended to be achieved via an energy-harvested Wireless Sensor Network using a novel architecture to propagate knowledge to other sensors based on automated reasoning from an attacked sensor.

Balancing Energy and Performance in Dense Linear System Solvers for Hybrid ARM+GPU platforms

The high performance computing community has traditionally focused uniquely on the reduction of execution time, though in the last years, the optimization of energy consumption has become a main issue. A reduction of energy usage without a degradation of performance requires the adoption of energy-efficient hardware platforms accompanied by the development of energy-aware algorithms and computational kernels. The solution of linear systems is a key operation for many scientific and engineering problems. Its relevance has motivated an important amount of work, and consequently, it is possible to find high performance solvers for a wide variety of hardware platforms. In this work, we aim to develop a high performance and energy-efficient linear system solver. In particular, we develop two solvers for a low-power CPU-GPU platform, the NVIDIA Jetson TK1. These solvers implement the Gauss-Huard algorithm yielding an efficient usage of the target hardware as well as an efficient memory access. The experimental evaluation shows that the novel proposal reports important savings in both time and energy-consumption when compared with the state-of-the-art solvers of the platform.

Using ICT Energy consumption for monitoring ICT architecture

Energy efficient policies are being applied to network protocols, devices and classical network management systems. Researchers have already studied in depth each of those fields, including for instance a long monitoring processes of various number of individual ICT equipment from where power models are constructed. With the development of smart meters and emerging protocols such as SNMP and NETCONF, currently there is an open field to couple the power models, translated to the expected behavior, with the realtime energy measurements. The goal is to derive a comparison on the power data between both of the processes in the direction of detection for possible deviations on the expected results. The logical assumption is that a fault in the usage of a particular device will not only increase its own energy usage, but also may cause additional consumption on the other devices part of the network. A platform is developed to monitor and analyze the retrieved power data of a simulated enterprise ICT infrastructure. Moreover, smart algorithms are developed which are aware of the different states that are occurring on each device during their typical use phase, as well as to detect and isolate possible anomalies. The produced results are obtained and validated with the use of Cisco switches and routers, Dell Precision stations and Raritan PDU as part of the monitored infrastructure.

Energy efficiency and appliance’s characteristics considered prior to purchase: Differences and similarities between the United Kingdom, Germany, Portugal, Greece, Poland, Spain and Italy

This article reports country differences in the consumer’s most considered characteristics when choosing electrical appliances, including but not restricted to the energy efficiency aspect. A survey was performed to store customers from 7 countries: the United Kingdom; Germany; Portugal; Greece; Poland; Spain; Italy. Results showed consistency between countries in the top three characteristics considered: cost; quality; and a balance between price and quality. Differences were found for reported environmental attitudes and behaviours, purchase motives, and store employees evaluation. The results may support national policies and store level energy efficiency interventions. Specifically, they can provide input for store employee’s training, in persuading customers towards the purchase of energy efficient appliances.

Developing strategies to mitigate the energy consumed by network infrastructures

The energy consumption by ICT (Information and Communication Technology) equipment is rapidly increasing which causes a significant economic and environmental problem. At present, the network infrastructure is becoming a large portion of the energy footprint in ICT. Thus the concept of energy efficient or green networking has been introduced. Now one of the main concerns of network industry is to minimize energy consumption of network infrastructure because of the potential economic benefits, ethical responsibility, and its environmental impact. In this paper, the energy management strategies to reduce the energy consumed by network switches in LAN (Local Area Network) have been developed. According to the lifecycle assessment of network switches, during usage phase, the highest amount of energy consumed. The study considers bandwidth, link load and traffic matrixes as input parameters which have the highest contribution in energy footprint of network switches during usage phase and energy consumption as output. Then with the objective of reducing energy usage of network infrastructure, the feasibility of putting Ethernet switches hibernate or sleep mode was investigated. After that, the network topology was reorganized using clustering method based on the spectral approach for putting network switches to hibernate or switched off mode considering the time and communications among them. Experimental results show the interest of this approach in terms of energy consumption

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Bionano Electronics: Magneto-Electric Nanoparticles for Drug Delivery, Brain Stimulation and Imaging Applications

Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.

An empirical investigation of the impact of global energy transition on Nigerian oil and gas exports

18 months embargo on the thesis and check appendix for copy right materials

Smart buildings for healthy and sustainable workplace: scoping study report

Deficiencies in the design and operation of office buildings can give rise to high social, environmental and economic (triple bottom line) costs. As a result, there are significant pressures and incentives to develop ‘smart building’ technologies that can facilitate improved indoor environment quality (IEQ), and more energy efficient operation of office buildings. IEQ indicators include lighting, ventilation, thermal comfort, indoor air quality and noise. In response to this, the CRC for Construction Innovation commissioned a six-month scoping study (Project no. 2002-043) to examine how different technologies could be used to improve the ‘triple bottom line’ for office buildings. The study was supported by three industry partners, Bovis Lend Lease, Arup, and The Queensland Department of Public Works. The objective of the study was to look at the history, trends, drivers, new technologies and potential application areas related to the operation of healthy and efficient office buildings. The key output from the study was a recommendation for a prototype system for intelligent monitoring and control of an office environment, based on identified market, technical and user requirements and constraints.

High quality indoor environments for office buildings

The quality of office indoor environments is considered to consist of those factors that impact the occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. It can be estimated that the potential cost of lost productivity from poor IEQ may be much in excess of other operating costs of a building. However, the relative productivity impacts of each of the four indicators is largely unknown. The CRC Project ‘Regenerating Construction to Enhance Sustainability’ has a focus on IEQ impacts before and after building refurbishment. This paper provides an overview of IEQ impacts and criteria and the implementation of a CRC project that is currently researching these factors during the refurbishment of a Melbourne office building. IEQ measurements and their impacts will be reported in a future paper

High quality indoor environments for sustainable office buildings

The quality of office indoor environments is considered to consist of those factors that impact occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. While the potential cost of lost productivity from poor IEQ has been estimated to exceed building operation costs, the level of impact and the relative significance of the above four indicators are largely unknown. However, they are key factors in the sustainable operation or refurbishment of office buildings. This paper presents a methodology for assessing indoor environment quality (IEQ) in office buildings, and indicators with related metrics for high performance and occupant comfort. These are intended for integration into the specification of sustainable office buildings as key factors to ensure a high degree of occupant habitability, without this being impaired by other sustainability factors. The assessment methodology was applied in a case study on IEQ in Australia’s first ‘six star’ sustainable office building, Council House 2 (CH2), located in the centre of Melbourne. The CH2 building was designed and built with specific focus on sustainability and the provision of a high quality indoor environment for occupants. Actual IEQ performance was assessed in this study by field assessment after construction and occupancy. For comparison, the methodology was applied to a 30 year old conventional building adjacent to CH2 which housed the same or similar occupants and activities. The impact of IEQ on occupant productivity will be reported in a separate future paper

Sustainable suburbs : the developer’s challenge

As our cities expand, developers are transforming more and more land to create our suburbs of the future. Developers and government bodies have a golden opportunity to design suburbs that are not only great places to live, but also are environmentally sensitive and sustainable. This is a unique opportunity, as significant changes after development are constrained by the configuration of the subdivision, and then by the construction of the dwellings. This paper explores some of these issues by presenting initial findings from the CRCCI, Sustainable Subdivisions Project. The Project examines the drivers and barriers that land developers face when trying to achieve sustainable subdivisions. This paper will review the results from a series of industry interviews and workshops and explore possible ways forward. In addition, the possible effect on the way future land subdivision is managed and planned as a result of recent changes in the energy efficiency provisions of the Building Code of Australia will be explored. This paper highlights problems that both builders and land developers may face through poor subdivision design. Finally an innovative program being driven by a major land developer will be introduced. The program aims to deliver over 400 energy and water efficient homes through a series of compulsory and voluntary schemes that the developer is designing, funding and implementing. This program is the first large-scale development in Australia that demonstrates how developers can help achieve environmentally sensitive and sustainable suburbs of the future.