On the Interplay between Network Traffic and Energy Consumption in Virtualized Environment: An Empirical Study

2014 ◽  
Author(s):  
Chi Xu ◽  
Ziyang Zhao ◽  
Haiyang Wang ◽  
Jiangchuan Liu
Keyword(s):  
Energy Consumption ◽  
Empirical Study ◽  
Network Traffic

scholarly journals Assessment of the Dependence of GHG Emissions on the Support and Taxes in the EU Countries

2021 ◽  
Vol 13 (14) ◽  
pp. 7650
Author(s):  
Astrida Miceikienė ◽  
Kristina Gesevičienė ◽  
Daiva Rimkuvienė
Keyword(s):  
Energy Consumption ◽  
Empirical Study ◽  
Ghg Emissions ◽  
Gdp Per Capita ◽  
Environmental Taxes ◽  
Environmental Support ◽  
Eu Countries ◽  
Support Measures ◽  
Per Capita ◽  
The Eu

The reduction of GHG emissions is one of the priorities of the EU countries. The majority of studies show that financial support and environmental taxes are one of the most effective measures for the mitigation of the negative consequences of climate change. The EU countries employ different environmental support measures and environmental taxes to reduce GHG emissions. There is a shortage of new studies on these measures. The aim of the present study is to compare the effectiveness of the environmental support measures of the EU countries with the effectiveness of environmental taxes in relation to the reduction of GHG emissions. This study is characterized by the broad scope of its data analysis and its systematic approach to the EU’s environmental policy measures. An empirical study was performed for the EU countries with the aim of addressing this research problem and substantiating theoretical insights. A total of 27 EU member states from 2009 to 2018 were selected as research samples. The research is based on a cause-and-effect relationship, where the factors affecting environmental pollution (environmental taxes and subsidies) are the cause, and GHG emissions are the effect. Statistical research methods were used in the empirical study: descriptive statistics, the Shapiro–Wilk test, one-way analysis of variance (ANOVA), simple regression and cluster analysis. The results show that the older member countries of the EU, which had directed the financial measures of environmental policy towards a reduction in energy consumption, managed to achieve a greater reduction in GHG emissions compared to the countries which had not applied those measures. The Central and Eastern European countries are characterized by lower environmental taxes and lower expenditure allocated to environmental protection. The countries with a higher GDP per capita have greater GHG emissions that the countries with lower GDP per capita. This is associated with greater consumption, waste, and energy consumption. The study conducted gives rise to a discussion regarding data sufficiency in the assessment and forecasting of GHG emissions and their environmental consequences.

Adaptive IEEE 802.15.4 MAC Protocol for Wireless Sensor Networks

2015 ◽  
pp. 109-123 ◽  
Author(s):  
Yousef S. Kavian ◽  
Hadi Rasouli
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Duty Cycle ◽  
Network Traffic ◽  
Ieee 802.15.4 ◽  
Extreme Environments ◽  
Wireless Sensor ◽  
Media Access ◽  
The Coordinator

The energy efficiency is a main challenging issue for employing wireless sensor networks (WSNs) in extreme environments where the media access progress consumes the main part of network energy. The IEEE 802.15.4 is adopted in low complexity, ultra-low power and low data rate wireless sensor applications where the energy consumption of nodes should be managed carefully in harsh and inaccessible environments. The beacon-enabled mode of the IEEE 802.15.4 provides a power management scheme. When the network traffic is variable, this mode does not work as well and the coordinator is not capable for estimating the network traffic and adjusting proper duty cycle dynamically. In this chapter an approach for estimating network traffic in star topology is proposed to overcome this issue where the coordinator could estimate the network traffic and dynamically adjusts duty cycle proportion to the variation of network traffic. The simulation results demonstrate the superiority of proposed approach for improving the energy consumption, throughput and delay in comparison with the IEEE 802.15.4 under different traffic conditions.

Research on Wireless Sensor Networks Data Fusion Algorithm Based on COA-BP

2014 ◽  
Vol 539 ◽  
pp. 247-250
Author(s):  
Xiao Xiao Liang ◽  
Li Cao ◽  
Chong Gang Wei ◽  
Ying Gao Yue
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Network Lifetime ◽  
Bp Neural Network ◽  
Network Traffic ◽  
Bp Algorithm ◽  
Wireless Sensor

To improve the wireless sensor networks data fusion efficiency and reduce network traffic and the energy consumption of sensor networks, combined with chaos optimization algorithm and BP algorithm designed a chaotic BP hybrid algorithm (COA-BP), and establish a WSNs data fusion model. This model overcomes shortcomings of the traditional BP neural network model. Using the optimized BP neural network to efficiently extract WSN data and fusion the features among a small number of original date, then sends the extracted features date to aggregation nodes, thus enhance the efficiency of data fusion and prolong the network lifetime. Simulation results show that, compared with LEACH algorithm, BP neural network and PSO-BP algorithm, this algorithm can effectively reduce network traffic, reducing 19% of the total energy consumption of nodes and prolong the network lifetime.

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