Energy efficiency of TCP: An analytical model and its application to reduce energy consumption of the most diffused transport protocol

Usman, Muhammad; Kliazovich, Dzmitry; Granelli, Fabrizio; Bouvry, Pascal; Castoldi, P.

doi:10.1002/dac.2934

Cited by 6 publications

(3 citation statements)

References 29 publications

(42 reference statements)

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“…To put these savings in context, virtualization technologies -particularly Xen and KVM-and container technologies -particularly LXC and Docker-consume between 126 and 128 Ws to run eight simultaneous idle virtual guests [30]. Likewise, the energy to send 27 MB of data via TCP in metropolitan-area networks where round-trip time is up to 50 milliseconds ranges from 921 to 43000 Ws [21]. Lastly, 30000 Ws is the energy necessary to execute Kmeans clustering algorithm from the benchmark in [9] by splitting the work to do under a 50-50 scheme between a CPU and an Nvidia GeForce 8800 GTX GPU [23].…”

Section: Results Summarymentioning

confidence: 99%

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

et al. 2019

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In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.

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Section: Results Summarymentioning

confidence: 99%

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

et al. 2019

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“…The axial flow fan is the main component of an air-conditioning system and a heat pump system. Improving its working efficiency can effectively reduce the energy consumption of the temperature regulation system (Usman et al, 2017). At the same time, its aerodynamic performance has a great impact on the overall performance of the air-conditioning system and heat pump system and determines the user's comfort level (Lim et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Optimization Design of a Forward-Swept Axial Flow Fan for Heat Pump

Zhou

et al. 2021

Front. Energy Res.

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As one of the key components of the heat pump system, compared to that of a conventional axial fan, the blade tip area of a forward-swept axial fan is much larger than its blade root, which is the main noise source of the fan and also has an important influence on the fan efficiency. Enhancement of the aerodynamic performance and efficiency of a forward-swept axial fan was addressed by utilizing the Bezier function to parameterize the forward-swept curve on blade tops. In order to quickly select an agent model suitable for the project, an ES model was established by integration of the radial basis function model and the Kriging model. When NSGA-II was combined, multi-objective optimization was carried out with the flow rate and total pressure efficiency as optimization goals. Analysis of optimization results revealed that the optimized axial flow fan’s flow rate and total pressure efficiency were improved to some degree. At the design working point, the fan’s flow rate increased by 1.78 m³/min, while the total pressure efficiency increased by 3.0%. These results lay solid foundation for energy saving of the heat pump system.

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“…For instance, when the predicted delay is smaller than the actual value, the information packets are redundantly retransmitted; on the other hand, if the predicted value of the delay is an overestimation, packet loss recovery will be slow, thus degrading quality of service (ie, throughput). [1][2][3] Different delay forecasting techniques have been based on its distribution characteristics; see Li and Mills, Ma and Barner et al, Ma and Arce et al, Rizo-Dominguez et al, and Jacobson. [4][5][6][7][8] It is pointed out that some algorithms assume uncorrelated delays, while others consider correlated delays.…”

Section: Introductionmentioning

confidence: 99%

Internet delay forecasting for correlated and uncorrelated scenarios

Rizo-Dominguez

Muñoz-Rodríguez

Vargas-Rosales

et al. 2017

Int J Communication

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Most Internet end-to-end communications rely on the transmission control protocol, and transmission control protocol performance depends upon the efficient detection of packet losses and delay estimations. Thus, several retransmission timeout prediction algorithms, which play an important role in the quality of service assurance, have been suggested in the literature. In this paper, we propose a novel forecasting algorithm, which, in contrast to those reported previously, is suitable for both the correlated and the uncorrelated delay scenarios. The proposed algorithm is compared with other methodologies by using standardized delay traces reported in the literature, and it is shown that the proposed algorithm obtains an improved performance with smaller errors than those of current predictors.

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Energy efficiency of TCP: An analytical model and its application to reduce energy consumption of the most diffused transport protocol

Cited by 6 publications

References 29 publications

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

Energy Efficiency Optimization Design of a Forward-Swept Axial Flow Fan for Heat Pump

Internet delay forecasting for correlated and uncorrelated scenarios

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