34,320 research outputs found
A Resource Intensive Traffic-Aware Scheme for Cluster-based Energy Conservation in Wireless Devices
Wireless traffic that is destined for a certain device in a network, can be
exploited in order to minimize the availability and delay trade-offs, and
mitigate the Energy consumption. The Energy Conservation (EC) mechanism can be
node-centric by considering the traversed nodal traffic in order to prolong the
network lifetime. This work describes a quantitative traffic-based approach
where a clustered Sleep-Proxy mechanism takes place in order to enable each
node to sleep according to the time duration of the active traffic that each
node expects and experiences. Sleep-proxies within the clusters are created
according to pairwise active-time comparison, where each node expects during
the active periods, a requested traffic. For resource availability and recovery
purposes, the caching mechanism takes place in case where the node for which
the traffic is destined is not available. The proposed scheme uses Role-based
nodes which are assigned to manipulate the traffic in a cluster, through the
time-oriented backward difference traffic evaluation scheme. Simulation study
is carried out for the proposed backward estimation scheme and the
effectiveness of the end-to-end EC mechanism taking into account a number of
metrics and measures for the effects while incrementing the sleep time duration
under the proposed framework. Comparative simulation results show that the
proposed scheme could be applied to infrastructure-less systems, providing
energy-efficient resource exchange with significant minimization in the power
consumption of each device.Comment: 6 pages, 8 figures, To appear in the proceedings of IEEE 14th
International Conference on High Performance Computing and Communications
(HPCC-2012) of the Third International Workshop on Wireless Networks and
Multimedia (WNM-2012), 25-27 June 2012, Liverpool, U
Persuading consumers to reduce their consumption of electricity in the home
Previous work has identified that providing real time feedback or interventions to consumers can persuade consumers to change behaviour and reduce domestic electricity consumption. However, little work has investigated what exactly those feedback mechanisms should be. Most past work is based on an in-home display unit, possibly complemented by lower tariffs and delayed use of non-essential home appliances such as washing machines. In this paper we focus on four methods for real time feedback on domestic energy use, developed to gauge the impact on energy consumption in homes. Their feasibility had been tested using an experimental setup of 24 households collecting minute-by-minute electricity consumption data readings over a period of 18 months. Initial results are mixed, and point to the difficulties of sustaining a reduction in energy consumption, i.e. persuading consumers to change their behaviour. Some of the methods we used exploit small group social dynamics whereby people want to conform to social norms within groups they identify with. It may be that a variety of feedback mechanisms and interventions are needed in order to sustain user interest
Promoting New Patterns in Household Energy Consumption with Pervasive Learning Games
Engaging computer games can be used to change energy consumption patterns in the home. PowerAgent is a pervasive game for Java-enabled mobile phones that is designed to influence everyday activities and use of electricity in
the domestic setting. PowerAgent is connected to the household’s automatic electricity meter reading equipment via the cell network, and this setup makes it
possible to use actual consumption data in the game. In this paper, we present a two-level model for cognitive and behavior learning, and we discuss the properties of PowerAgent in relation to the underlying situated learning, social learning, and persuasive technology components that we have included in the game
Evaluation of a Pervasive Game for Domestic Energy Engagement Among Teenagers
In this article, we present Power Agent—a pervasive game designed to encourage teenagers and
their families to reduce energy consumption in the home. The ideas behind this mobile phonebased
game are twofold; to transform the home environment and its devices into a learning arena
for hands-on experience with electricity usage and to promote engagement via a team competition
scheme. We report on the game’s evaluation with six teenagers and their families who played the
game for ten days in two cities in Sweden. Data collection consisted of home energy measurements
before, during, and after a game trial, in addition to interviews with participants at the end of
the evaluation. The results suggest that the game concept was highly efficient in motivating and
engaging the players and their families to change their daily energy-consumption patterns during
the game trial. Although the evaluation does not permit any conclusions as to whether the game had
any postgame effects on behavior, we can conclude that the pervasive persuasive game approach
appears to be highly promising in regard to energy conservation and similar fields or issues
A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments
In recent years, due to the unnecessary wastage of electrical energy in
residential buildings, the requirement of energy optimization and user comfort
has gained vital importance. In the literature, various techniques have been
proposed addressing the energy optimization problem. The goal of each technique
was to maintain a balance between user comfort and energy requirements such
that the user can achieve the desired comfort level with the minimum amount of
energy consumption. Researchers have addressed the issue with the help of
different optimization algorithms and variations in the parameters to reduce
energy consumption. To the best of our knowledge, this problem is not solved
yet due to its challenging nature. The gap in the literature is due to the
advancements in the technology and drawbacks of the optimization algorithms and
the introduction of different new optimization algorithms. Further, many newly
proposed optimization algorithms which have produced better accuracy on the
benchmark instances but have not been applied yet for the optimization of
energy consumption in smart homes. In this paper, we have carried out a
detailed literature review of the techniques used for the optimization of
energy consumption and scheduling in smart homes. The detailed discussion has
been carried out on different factors contributing towards thermal comfort,
visual comfort, and air quality comfort. We have also reviewed the fog and edge
computing techniques used in smart homes
Optimal configuration of active and backup servers for augmented reality cooperative games
Interactive applications as online games and mobile devices have become more and more popular in recent years. From their combination, new and interesting cooperative services could be generated. For instance, gamers endowed with Augmented Reality (AR) visors connected as wireless nodes in an ad-hoc network, can interact with each other while immersed in the game. To enable this vision, we discuss here a hybrid architecture enabling game play in ad-hoc mode instead of the traditional client-server setting. In our architecture, one of the player nodes also acts as the server of the game, whereas other backup server nodes are ready to become active servers in case of disconnection of the network i.e. due to low energy level of the currently active server. This allows to have a longer gaming session before incurring in disconnections or energy exhaustion. In this context, the server election strategy with the aim of maximizing network lifetime is not so straightforward. To this end, we have hence analyzed this issue through a Mixed Integer Linear Programming (MILP) model and both numerical and simulation-based analysis shows that the backup servers solution fulfills its design objective
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