Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

A novel energy-efficient cross-application-layer platform with QoS-security support

Security provisioning is an essential part in the design of any communication systems, which becomes more critical for wireless systems. Devising a quality of service (QoS) mechanism to coexist security algorithms is a daunting, yet inevitable task. The aim of this novel research article is to present a novel energy efficient, cross-layer-based application-layer wireless system with simultaneous security and QoS supports, which revolves around the practical and low-cost implementation of Suite-B cryptographic algorithms (promulgated by the National Security Agency) and detailed analyses of the associated complexities. The focus of this article is on the novel cross-layer mechanism and its effectiveness to handle QoS-enabled treatment while offering security enhancements.

Secure and energy-efficient data aggregation with malicious aggregator identification in wireless sensor networks

Data aggregation in wireless sensor networks is employed to reduce the communication overhead and prolong the network lifetime. However, an adversary may compromise some sensor nodes, and use them to forge false values as the aggregation result. Previous secure data aggregation schemes have tackled this problem from different angles. The goal of those algorithms is to ensure that the Base Station (BS) does not accept any forged aggregation results. But none of them have tried to detect the nodes that inject into the network bogus aggregation results. Moreover, most of them usually have a communication overhead that is (at best) logarithmic per node. In this paper, we propose a secure and energy-efficient data aggregation scheme that can detect the malicious nodes with a constant per node communication overhead. In our solution, all aggregation results are signed with the private keys of the aggregators so that they cannot be altered by others. Nodes on each link additionally use their pairwise shared key for secure communications. Each node receives the aggregation results from its parent (sent by the parent of its parent) and its siblings (via its parent node), and verifies the aggregation result of the parent node. Theoretical analysis on energy consumption and communication overhead accords with our comparison based simulation study over random data aggregation trees.

Energy-efficient tall buildings design strategies: a holistic approach

The number of tall buildings is increasing as a result of the advances in construction technologies and the rising land prices. These buildings are characterised by their high energy consumption compared to other building types as they rely intensively on mechanical HVAC systems due to the extreme weather conditions associated with the increase in height. However, they present a great opportunity for energy savings. In recent years, it has been noticed the increasing interest in geometry and form of tall buildings, as a result of the evolution of parametric modelling and 3D visualisation tools, on the expense of the environmental aspect. This paper discusses factors affecting the energy consumption in the tall buildings. Through an extensive analysis of Literature, active and passive energy efficient strategies adopted in tall building at various building stages are identified. In addition, the role of architectural design parameters, such as building form, orientation and envelope on the tall building energy performance are highlighted. Finally, a set of guidelines and environmental design strategies to be considered in different phases in order to achieve energy-efficient tall buildings are proposed. These strategies have been categorised into four stages namely early design, conceptualisation, and documentation and operational. A 3D modelling approach was used to visualise and illustrate the proposed strategies in different stages.

Adaptive energy-efficient qos-aware scheduling algorithm for TCP/IP mobile cloud

The expected pervasive use of mobile cloud computing and the growing number of Internet data centers have brought forth many concerns, such as, energy costs and energy saving management of both data centers and mobile connections. Therefore, the need for adaptive and distributed resource allocation schedulers for minimizing the communication-plus-computing energy consumption has become increasingly important. In this paper, we propose and test an efficient dynamic resource provisioning scheduler that jointly minimizes computation and communication energy consumption, while guaranteeing user Quality of Service (QoS) constraints. We evaluate the performance of the proposed dynamic resource provisioning algorithm with respect to the execution time, goodput and bandwidth usage and compare the performance of the proposed scheduler against the exiting approaches. The attained experimental results show that the proposed dynamic resource provisioning algorithm achieves much higher energy-saving than the traditional schemes.

Environmental sustainability and the human element: Decision making in National Cancer Institute-designated cancer centers and Practice Greenhealth subscribing institutions

Background. Various aspects of sustainability have taken root in the hospital environment; however, decisions to pursue sustainable practices within the framework of a master plan are not fully developed in National Cancer Institute (NCI) -designated cancer centers and subscribing institutions to the Practice Greenhealth (PGH) listserv.^ Methods. This cross sectional study was designed to identify the organizational characteristics each study group pursed to implement sustainability practices, describe the barriers they encountered and reasons behind their choices for undertaking certain sustainability practices. A web-based questionnaire was pilot tested, and then sent out to 64 NCI-designated cancer centers and 1638 subscribing institutions to the PGH listserv.^ Results. Complete responses were received from 39 NCI-designated cancer centers and 58 subscribing institutions to the PGH listserv. NCI-designated cancer centers reported greater progress in integrating sustainability criteria into design and construction projects than hospitals of institutions subscribing to the PHG listserv (p-value = <0.05). Statistically significant differences were also identified between these two study groups in undertaking work life options, conducting energy usage assessments, developing energy conservation and optimization plans, implementing solid waste and hazardous waste minimization programs, using energy efficient vehicles and reporting sustainability progress to external stakeholders. NCI-designated cancer centers were further along in implementing these programs (p-value = <0.05). In comparing the self-identified NCI-designated cancer centers to centers that indicated they were both and NCI and PGH, the later had made greater progress in using their collective buying power to pursue sustainable purchasing practices within the medical community (p-value = <0.05). In both study groups, recycling programs were well developed.^ Conclusions. Employee involvement was viewed as the most important reason for both study groups to pursue recycling initiatives and incorporated environmental criteria into purchasing decisions. A written sustainability commitment did not readily translate into a high percentage that had developed a sustainability master plan. Coordination of sustainability programs through a designated sustainability professional was not being undertaken by a large number of institutions within each study group. This may be due to the current economic downturn or management's attention to the emerging health care legislation being debated in congress. ^ Lifecycle assessments, an element of a carbon footprint, are seen as emerging areas of opportunity for health care institutions that can be used to evaluate the total lifecycle costs of products and services.^

Pathways to Low Carbon Transport in the EU – From Possibility to Reality. Report of the CEPS Task Force on transport and climate change. CEPS Task Force Report, June 2013

A new CEPS Task Force Report has identified possible pathways for achieving the EU’s ambitious climate change targets. It concludes that a GHG emissions reduction in line with EU climate change policy is possible, but it requires immediate action. This report argues that most of the reductions required of the transport sector in the EU could come from more energy-efficient vehicles, combined with the gradual introduction of low-carbon fuels and new engine technologies. The key policy for reducing GHG emissions in road transport is the steady tightening of emissions standards in line with technological progress. The report also identifies strategies for the transport system to become more energy and/or carbon efficient, arguing that leverage can be further enhanced by local and city governments’ incentives for efficient and low-carbon vehicles in line with local circumstances and choices. The Task Force on Low Carbon Transport brought together a diverse set of stakeholders from the car and oil industries, business associations, international organisations, member states, academic experts and NGOs. This authoritative report is the result of that unique collaboration.

Implementable efficient time and energy consumption trajectories design for an autonomous underwater vehicle

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Intelligent energy management for plug-in hybrid electric vehicles : the role of ITS infrastructure in vehicle electrification

The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control.

A first extension of geometric control theory to underwater vehicles

This paper serves as a first study on the implementation of control strategies developed using a kinematic reduction onto test bed autonomous underwater vehicles (AUVs). The equations of motion are presented in the framework of differential geometry, including external dissipative forces, as a forced affine connection control system. We show that the hydrodynamic drag forces can be included in the affine connection, resulting in an affine connection control system. The definitions of kinematic reduction and decoupling vector field are thus extended from the ideal fluid scenario. Control strategies are computed using this new extension and are reformulated for implementation onto a test-bed AUV. We compare these geometrically computed controls to time and energy optimal controls for the same trajectory which are computed using a previously developed algorithm. Through this comparison we are able to validate our theoretical results based on the experiments conducted using the time and energy efficient strategies.

Implementation results of efficient trajectories on a testbed AUV

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

Nanoscale control of energy and matter in plasma–surface interactions : toward energy- and matter-efficient nanotech

The approach to control the elementary processes of plasma–surface interactions to direct the fluxes of energy and matter at nano- and subnanometer scales is introduced. This ability is related to the solution of the grand challenge of directing energy and matter at nanoscales and is critical for the renewable energy and energy-efficient technologies for a sustainable future development. The examples of deterministic synthesis of self-organized arrays of metastable nanostructures in the size range beyond the reach of the present-day nanofabrication are considered to illustrate this possibility. By using precisely controlled and kinetically fast nanoscale transfer of energy and matter under nonequilibrium conditions and harnessing numerous plasma-specific controls of species creation, delivery to the surface,nucleation, and large-scale self-organization of nuclei and nanostructures, the arrays of metastable nanostructures can be created, arranged, stabilized, and further processed to meet the specific requirements of the envisaged applications.

The emergence of battery electric vehicles : A NZ manufacturing opportunity?

Personal passenger transport faces several challenges in the coming decades: depletion of cheap oil reserves, increasing congestion, localised pollution, the need for reduced carbon emissions and the long term goal of sustainability. One way of solving some of these problems could be to introduce comfortable, energy efficient, battery electric vehicles.

Currently, hybrid vehicles have been presented as a means to reducing the transportation related oil demand. New developments in materials and technologies have made them, cleaner and safer as well as more fuel efficient. However, hybrids will only prolong the use of oil until alternatively fuelled vehicles are developed.

One long term alternative is the battery electric vehicle (BEV). A BEV designed to be light, aerodynamic with high efficiency drive train and latest battery technology would have a performance comparable to a typical internal combustion engine vehicle (ICEV). Recent developments in virtual engineering, rapid prototyping and advanced manufacturing might enable low-cost development of niche market BEV’s designed and built in New Zealand for export markets.

This work examines the collaborative development of a twin seat BEV using new materials and latest technologies by the University of Waikato’s Engineering Department and a group of NZ and foreign companies. The car will be used to research the potential of BEVs and will also compete in the Commuter Class of the World Solar Challenge in 2007.