90 resultados para energy efficient

em Deakin Research Online - Australia


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The energy required to create a comfortable living environment in  high-density cities in hot and humid climates usually demands a substantial electricity usage with an associated environmental burden. This paper describes an integrated passive design approach to reduce the cooling requirement for high-rise apartments through an improved building envelope design. The results show that a saving of 31.4% in annual required cooling energy and 36.8% in the peak cooling load for the BASECASE apartment can be achieved with this approach. However, all the passive strategies have marginal effect on latent cooling load, often less than 1%.

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Conserving of battery power is a critical requirement in WSNs. Past studies have shown that the transceiving process consumes more energy than the internal processing. This work focuses on eliminating overhead messages used for address allocation by employing multiple base-stations. In this context we explore address allocation without Duplicate Address Detection (DAD). We present an alternative approach to Duplicate address detection using the sink as an address pool to maintain and systematize available addresses. Experimental results show that this approach eliminates overhead messages generated by DAD; resulting in energy savings when used in conjunction with an on-demand address allocation mechanism.

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Fully-connected mesh networks that can potentially be employed in a range of applications, are inherently associated with major deficiencies in interference management and network capacity improvement. The tree-connected (routing based) mesh networks used in today’s applications have major deficiencies in routing delays and reconfiguration delays in the implementation stage. This paper introduces a CDMA based fully-connected mesh network, which controls the transmission powers of the nodes in order to ensure that the communication channels remain interference-free and minimizes the energy consumption. Moreover, the bounds for the number of nodes and the spatial configuration are provided to ensures that the communication link satisfies the QoS (Quality of Service) requirements at all times.

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Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. Emerging WSN applications require dissemination of information to interested clients within the network requiring support for differing traffic patterns. Further, in-network query processing capabilities are required for autonomic information discovery. In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay. We propose novel methods for data dissemination, information discovery and data aggregation that are designed to provide significant QoS benefits. We make use of affinity propagation to group "similar" sensors and have developed efficient mechanisms that can resolve both ALL-type and ANY-type queries in-network with improved energy-efficiency and query resolution time. Simulation results prove the proposed method(s) of information discovery offer significant QoS benefits for ALL-type and ANY-type queries in comparison to previous approaches.

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Medium access control for wireless sensor networks has been an active
research area in the past decade. This chapter discusses a set of important medium access control (MAC) attributes and possible design trade-offs in protocol design, with an emphasis on energy efficiency. Then we categorize existing MAC protocols into five groups, outline the representative protocols, and compare their advantages and disadvantages in the context of wireless sensor network. Finally, thoughts for practitioners are presented and open research issues are also discussed.

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Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

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Previous studies on residential energy end use behavior reported significant reduction in energy end use of 7% to 24% when feedback is used to modify behavior in an energy efficient manner. However, most feedback systems investigated in previous studies have not benefited from advanced information systems (IS). IS can shape energy efficiency behavior by providing real-time feedback on energy consumption, cost and environmental impact. Such systems represent a new and less-researched subfield of energy informatics. This paper provides a conceptual framework for showing the potential use of IS to modify residential energy use behavior towards better energy efficiency. The framework builds on research in residential energy end use, in particular energy end use behavioral model. It provides conceptual inputs for a blue-print to develop a residential energy management information system (REMIS) and also highlights the use of new information and communications technologies (ICT) that had not been widely used, setting the grounds for further research in this area.

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Despite significant advancements in wireless sensor networks (WSNs), energy conservation remains one of the most important research challenges. Proper organization of nodes (clustering) is one of the major techniques to expand the lifespan of the whole network through aggregating data at the cluster head. The cluster head is the backbone of the entire cluster. That means if a cluster head fails to accomplish its function, the received and collected data by cluster head can be lost. Moreover, the energy consumption following direct communications from sources to base stations will be increased. In this paper, we propose a type-2 fuzzy based self-configurable cluster head selection (SCCH) approach to not only consider the selection criterion of the cluster head but also present the cluster backup approach. Thus, in case of cluster failure, the system still works in an efficient way. The novelty of this protocol is the ability of handling communication uncertainty, which is an inherent operational aspect of sensor networks. The experiment results indicate SCCH performs better than other recently developed methods.