Thermal energy aware proportionate scheduler for  multiprocessor systems

Fluid scheduling allows tasks to be allocated with fractional processing capacity, which significantly improves the schedulability performance. For dual-criticality systems (DCS), dual-rate fluid-based scheduling has been widely studied, e.g., the state-of-the-art approaches mixed-criticality fluid scheduling (MCF) and MC-Sort. However, most of the existing works on DCS either only focus on the schedulability analysis or minimize the energy consumption treating leakage power as a constant. To this end, this paper considers the effect of temperature on leakage power and proposes a thermal and power aware fluid scheduling strategy, referred to as thermal and energy aware (TA)-MCF which minimizes both the energy consumption and temperature, while ensuring a comparable schedulability ratio compared with the MCF and MC-Sort. Extensive experiments validate the efficiency of TA-MCF.

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

ISRN Communications and Networking ◽

10.5402/2012/209573 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Tosmate Cheocherngngarn ◽

Jean Andrian ◽

Deng Pan

Keyword(s):

Energy Consumption ◽

Power Consumption ◽

Data Center ◽

Tree Topology ◽

Data Center Network ◽

Bandwidth Utilization ◽

Shared Resources ◽

Energy Aware ◽

Deployment Strategy ◽

It Systems

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.

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Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.pp3283-3292 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3283 ◽

Cited By ~ 1

Author(s):

Mahendra Kumar Gourisaria ◽

S. S. Patra ◽

P. M. Khilar

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Power Consumption ◽

Resource Utilization ◽

Data Centers ◽

Carbon Dioxide Emission ◽

Computing Environment ◽

Energy Aware ◽

Cloud Computing Environment ◽

Cpu Utilization

<p>Cloud computing is an emerging field of computation. As the data centers consume large amount of power, it increases the system overheads as well as the carbon dioxide emission increases drastically. The main aim is to maximize the resource utilization by minimizing the power consumption. However, the greatest usages of resources does not mean that there has been a right use of energy. Various resources which are idle, also consumes a significant amount of energy. So we have to keep minimum resources idle. Current studies have shown that the power consumption due to unused computing resources is nearly 1 to 20%. So, the unused resources have been assigned with some of the tasks to utilize the unused period. In the present paper, it has been suggested that the energy saving with task consolidation which has been saved the energy by minimizing the number of idle resources in a cloud computing environment. It has been achieved far-reaching experiments to quantify the performance of the proposed algorithm. The same has also been compared with the FCFSMaxUtil and Energy aware Task Consolidation (ETC) algorithm. The outcomes have shown that the suggested algorithm surpass the FCFSMaxUtil and ETC algorithm in terms of the CPU utilization and energy consumption.</p>

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Energy Aware Better Implementation of Load Balancing in Cloud Computing

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813666191125140638 ◽

2020 ◽

Vol 13 ◽

Author(s):

Alekhya Orugonda ◽

V. Kiran Kumar

Keyword(s):

Energy Consumption ◽

Load Balancing ◽

Power Consumption ◽

Virtual Machines ◽

Average Power ◽

Power Saving ◽

System Level ◽

Energy Aware ◽

Physical Machine ◽

Average Power Consumption

Background: It is important to minimize bandwidth that improves battery life, system reliability and other environmental concerns and energy optimization.It also do everything within their power to reduce the amount of data that flows through their pipes.To increase resource exertion, task consolidation is an effective technique, greatly enabled by virtualization technologies, which facilitate the concurrent execution of several tasks and, in turn, reduce energy consumption. : MaxUtil, which aims to maximize resource exertion, and Energy Conscious Task Consolidation which explicitly takes into account both active and idle energy consumption. Method: In this paper an Energy Aware Cloud Load Balancing Technique (EACLBT) is proposed for the performance improvement in terms of energy and run time. It predicts load of host after VM allocation and if according to prediction host become overloaded than VM will be created on different host. So it minimize the number of migrations due to host overloading conditions. This proposed technique results in minimize bandwidth and energy utilization. Results: The result shows that the energy efficient method has been proposed for monitor energy exhaustion and support static and dynamic system level optimization.The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving.Besides minimization in bandwidth along with energy exertion, reduction in the number of executed instructions is also achieved. Conclusion: This paper comprehensively describes the EACLBT (Energy Aware Cloud Load Balancing Technique) to deploy the virtual machines for power saving purpose. The average power consumption is used as performance metrics and the result of PALB is used as baseline. The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving. It shown that on average an idle server consumes approximately 70% of the power consumed by the server running at the full CPU speed.The performance holds better for Common sub utterance elimination. So, we can say the proposed Energy Aware Cloud Load Balancing Technique (EACLBT) is effective in bandwidth minimization and reduction of energy exertion.

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Towards a Secure Thermal-Energy Aware Routing Protocol in Wireless Body Area Network Based on Blockchain Technology

Sensors ◽

10.3390/s20123604 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3604 ◽

Cited By ~ 7

Author(s):

Zeinab Shahbazi ◽

Yung-Cheol Byun

Keyword(s):

Energy Consumption ◽

High Throughput ◽

Thermal Energy ◽

Routing Protocol ◽

Temperature Rise ◽

Data Transmission ◽

Physiological Data ◽

Body Area ◽

Energy Aware ◽

Energy Aware Routing

The emergence of biomedical sensor devices, wireless communication, and innovation in other technologies for healthcare applications result in the evolution of a new area of research that is termed as Wireless Body Area Networks (WBANs). WBAN originates from Wireless Sensor Networks (WSNs), which are used for implementing many healthcare systems integrated with networks and wireless devices to ensure remote healthcare monitoring. WBAN is a network of wearable devices implanted in or on the human body. The main aim of WBAN is to collect the human vital signs/physiological data (like ECG, body temperature, EMG, glucose level, etc.) round-the-clock from patients that demand secure, optimal and efficient routing techniques. The efficient, secure, and reliable designing of routing protocol is a difficult task in WBAN due to its diverse characteristic and restraints, such as energy consumption and temperature-rise of implanted sensors. The two significant constraints, overheating of nodes and energy efficiency must be taken into account while designing a reliable blockchain-enabled WBAN routing protocol. The purpose of this study is to achieve stability and efficiency in the routing of WBAN through managing temperature and energy limitations. Moreover, the blockchain provides security, transparency, and lightweight solution for the interoperability of physiological data with other medical personnel in the healthcare ecosystem. In this research work, the blockchain-based Adaptive Thermal-/Energy-Aware Routing (ATEAR) protocol for WBAN is proposed. Temperature rise, energy consumption, and throughput are the evaluation metrics considered to analyze the performance of ATEAR for data transmission. In contrast, transaction throughput, latency, and resource utilization are used to investigate the outcome of the blockchain system. Hyperledger Caliper, a benchmarking tool, is used to evaluate the performance of the blockchain system in terms of CPU utilization, memory, and memory utilization. The results show that by preserving residual energy and avoiding overheated nodes as forwarders, high throughput is achieved with the ultimate increase of the network lifetime. Castalia, a simulation tool, is used to evaluate the performance of the proposed protocol, and its comparison is made with Multipath Ring Routing Protocol (MRRP), thermal-aware routing algorithm (TARA), and Shortest-Hop (SHR). Evaluation results illustrate that the proposed protocol performs significantly better in balancing of temperature (to avoid damaging heat effect on the body tissues) and energy consumption (to prevent the replacement of battery and to increase the embedded sensor node life) with efficient data transmission achieving a high throughput value.

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Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.12251 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3283

Author(s):

Mahendra Kumar Gourisaria ◽

S. S. Patra ◽

P. M. Khilar

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Power Consumption ◽

Resource Utilization ◽

Data Centers ◽

Carbon Dioxide Emission ◽

Computing Environment ◽

Energy Aware ◽

Cloud Computing Environment ◽

Cpu Utilization

<p>Cloud computing is an emerging field of computation. As the data centers consume large amount of power, it increases the system overheads as well as the carbon dioxide emission increases drastically. The main aim is to maximize the resource utilization by minimizing the power consumption. However, the greatest usages of resources does not mean that there has been a right use of energy. Various resources which are idle, also consumes a significant amount of energy. So we have to keep minimum resources idle. Current studies have shown that the power consumption due to unused computing resources is nearly 1 to 20%. So, the unused resources have been assigned with some of the tasks to utilize the unused period. In the present paper, it has been suggested that the energy saving with task consolidation which has been saved the energy by minimizing the number of idle resources in a cloud computing environment. It has been achieved far-reaching experiments to quantify the performance of the proposed algorithm. The same has also been compared with the FCFSMaxUtil and Energy aware Task Consolidation (ETC) algorithm. The outcomes have shown that the suggested algorithm surpass the FCFSMaxUtil and ETC algorithm in terms of the CPU utilization and energy consumption.</p>

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Determinants of the Energy Poverty of Polish Students during the COVID-19 Pandemic

Energies ◽

10.3390/en14113233 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3233

Author(s):

Łukasz Mamica ◽

Jakub Głowacki ◽

Kamil Makieła

Keyword(s):

Energy Efficiency ◽

Energy Consumption ◽

Distance Learning ◽

Thermal Energy ◽

Small Degree ◽

Energy Aware ◽

Energy Poverty ◽

Factors Influencing ◽

And Behavior ◽

Attitudes And Behavior

The aim of this paper is to define the factors influencing the level of energy poverty among students. The analysis of these factors is based on the results of a survey conducted among a group of 937 students at the Cracow University of Economics. The study takes into consideration the changes in the attitudes and behavior of students resulting from the introduction of distance learning during the COVID-19 pandemic. The switch to distance learning resulted in a significant increase in the number of responses related to feeling ill or sick due to inadequate temperature (from 24% before a lockdown to 32% after the introduction of a lockdown). Students experienced temporary surges in their overall living costs due to the pandemic, especially during the first wave. The respondents who experienced inappropriate temperatures (inadequate heating) due to excessive costs felt ill or became sick more often than others. The study demonstrated that those who pay more for energy (defined as a surplus payment in excess of 10%) tended to be, on average, less energy-aware than others. The following indicators of energy poverty among the students were distinguished: high living costs, small degree of influence over the choice of living quarters, as well as concerns over energy efficiency and environment. The conclusions drawn from the conducted studies may be utilized to design public policies aimed at curtailing the phenomenon of energy poverty among students. This issue is particularly prominent in large urban agglomerations where the costs of living are high and result in the feeling of pressure regarding the need to save money on thermal energy consumption.

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DISCHARGING PROCESS OF A HIGH-TEMPERATURE HEAT PIPE-ASSISTED THERMAL ENERGY STORAGE SYSTEM WITH NANO-ENAHNCED PHASE CHANGE MATERIAL

10.1615/tfec2019.tes.028083 ◽

2019 ◽

Cited By ~ 1

Author(s):

Saeed Tiari ◽

Olivia L. Rose ◽

Mahboobe Mahdavi

Keyword(s):

High Temperature ◽

Energy Storage ◽

Thermal Energy ◽

Thermal Energy Storage ◽

Storage System ◽

Energy Storage System ◽

Thermal Energy Storage System ◽

Temperature Heat ◽

High Temperature Heat Pipe ◽

Change Material

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High-Temperature Pumping of Silicon for Thermal Energy Grid Storage

Energy ◽

10.1016/j.energy.2021.121105 ◽

2021 ◽

pp. 121105

Author(s):

Caleb Amy ◽

Mehdi Pishahang ◽

Colin Kelsall ◽

Alina LaPotin ◽

Asegun Henry

Keyword(s):

High Temperature ◽

Thermal Energy ◽

Energy Grid ◽

Grid Storage

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Demonstration of Phase Change Thermal Energy Storage in Zinc Oxide Microencapsulated Sodium Nitrate

Applied Sciences ◽

10.3390/app11136234 ◽

2021 ◽

Vol 11 (13) ◽

pp. 6234

Author(s):

Ciprian Neagoe ◽

Ioan Albert Tudor ◽

Cristina Florentina Ciobota ◽

Cristian Bogdanescu ◽

Paul Stanciu ◽

...

Keyword(s):

Zinc Oxide ◽

Thermal Properties ◽

High Temperature ◽

Energy Storage ◽

Phase Change ◽

Thermal Energy ◽

Sodium Nitrate ◽

Thermal Energy Storage ◽

Metal Corrosion ◽

Scanning Calorimetry

Microencapsulation of sodium nitrate (NaNO3) as phase change material for high temperature thermal energy storage aims to reduce costs related to metal corrosion in storage tanks. The goal of this work was to test in a prototype thermal energy storage tank (16.7 L internal volume) the thermal properties of NaNO3 microencapsulated in zinc oxide shells, and estimate the potential of NaNO3–ZnO microcapsules for thermal storage applications. A fast and scalable microencapsulation procedure was developed, a flow calorimetry method was adapted, and a template document created to perform tank thermal transfer simulation by the finite element method (FEM) was set in Microsoft Excel. Differential scanning calorimetry (DSC) and transient plane source (TPS) methods were used to measure, in small samples, the temperature dependency of melting/solidification heat, specific heat, and thermal conductivity of the NaNO3–ZnO microcapsules. Scanning electron microscopy (SEM) and chemical analysis demonstrated the stability of microcapsules over multiple tank charge–discharge cycles. The energy stored as latent heat is available for a temperature interval from 303 to 285 °C, corresponding to onset–offset for NaNO3 solidification. Charge–self-discharge experiments on the pilot tank showed that the amount of thermal energy stored in this interval largely corresponds to the NaNO3 content of the microcapsules; the high temperature energy density of microcapsules is estimated in the range from 145 to 179 MJ/m3. Comparison between real tank experiments and FEM simulations demonstrated that DSC and TPS laboratory measurements on microcapsule thermal properties may reliably be used to design applications for thermal energy storage.

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