List of Articles انرژی

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  1 - Investigating the Effects of Hardware Parameters on Power Consumptions in SPMV Algorithms on Graphics Processing Units (GPUs)
  Farshad Khunjush
  Although Sparse matrix-vector multiplication (SPMVs) algorithms are simple, they include important parts of Linear Algebra algorithms in Mathematics and Physics areas. As these algorithms can be run in parallel, Graphics Processing Units (GPUs) has been considered as on More

  Although Sparse matrix-vector multiplication (SPMVs) algorithms are simple, they include important parts of Linear Algebra algorithms in Mathematics and Physics areas. As these algorithms can be run in parallel, Graphics Processing Units (GPUs) has been considered as one of the best candidates to run these algorithms. In the recent years, power consumption has been considered as one of the metrics that should be taken into consideration in addition to performance.  In spite of this importance, to the best of our knowledge, studies on power consumptions in SPMVs algorithms on GPUs are scarce.  In this paper, we investigate the effects of hardware parameters on power consumptions in SPMV algorithms on GPUs. For this, we leverage the possibility of setting the GPU’s parameters to investigate the effects of these parameters on power consumptions. These configurations have been applied to different formats of Sparse Matrices, and the best parameters are selected for having the best performance per power metric. Therefore, as the results of this study the settings can be applied in running different Linear Algebra algorithms on GPUs to obtain the best performance per power. Manuscript profile
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  2 - Investigating the Effect of Hardware Parameters Adjustments on Energy Consumption in Thin Matrix Multiplication Algorithm on GPUs
  mina ashouri Farshad Khunjush
  20.1001.1.27170411.1396.9.31.7.8
  Multiplication of thin algorithmic matrices is a simple but very important part of linear and scientific algebra programs in mathematics and physics, and due to its parallel nature, GPUs are one of the most suitable and important options. To select its executive platfor More

  Multiplication of thin algorithmic matrices is a simple but very important part of linear and scientific algebra programs in mathematics and physics, and due to its parallel nature, GPUs are one of the most suitable and important options. To select its executive platform. In recent years, due to the emphasis of researchers to consider energy consumption as one of the main design goals along with efficiency, very little effort has been made to improve the energy consumption of this algorithm on the GPU. In this article, this issue is addressed from the perspective of energy efficiency in efficiency obtained. Utilizing the configuration capability introduced in modern GPUs, by statistically examining the behavior of this algorithm when using different thin matrix storage formats and different hardware settings for more than 200 matrices Slim example, the best configuration settings for the thin matrix multiplication algorithm with different storage formats on the GPU are obtained. This configuration for each storage format is selected to give the best configuration in all samples tested. Manuscript profile
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  3 - Presenting a method based on computational intelligence to improve energy consumption in smart wireless sensor networks
  faezeh talebian حسن  ختن¬لو منصور  اسماعیل¬پور
  20.1001.1.27170411.1394.7.24.1.4
  Recent advances in the field of electronics and wireless communication have given the ability to design and manufacture sensors with low power consumption, small size, reasonable price and various uses. The limited energy capacity of sensors is a major challenge that af More

  Recent advances in the field of electronics and wireless communication have given the ability to design and manufacture sensors with low power consumption, small size, reasonable price and various uses. The limited energy capacity of sensors is a major challenge that affects these networks. Clustering is used as one of the well-known methods to manage this challenge. To find the suitable location of the cluster heads, the colonial competition algorithm, which is one of the branches of computational intelligence, has been used. Cluster heads are connected by a three-level model, so that cluster heads with low energy capacity and far from the station are known as the third level and exchange information indirectly with the base station. This increases the lifespan of wireless sensor networks Manuscript profile
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  4 - Increasing the value of collected data and reducing energy consumption by using network coding and mobile sinks in wireless sensor networks
  ehsan kharati
  20.1001.1.27170414.1399.12.43.3.4
  The wireless sensor network includes a number of fixed sensor nodes that move sink nodes to collect data between nodes. To reduce energy consumption and increase the value of collected data, it is necessary to determine the optimum route and residence location of mobile More

  The wireless sensor network includes a number of fixed sensor nodes that move sink nodes to collect data between nodes. To reduce energy consumption and increase the value of collected data, it is necessary to determine the optimum route and residence location of mobile sinks, which increases the life of wireless sensor networks. Using network coding, this paper presents a Mixed Integer Linear Programming Model to determine the optimal multicast routing of source sensor nodes to mobile sinks in wireless sensor networks, which determines the time and location of sinks to collect maximum coded data and reduces the delay in sink movement and energy consumption. Solving this problem in polynomial time is not possible due to the involvement of various parameters and the constrained resources of wireless sensor networks. Therefore, several exploratory and greedy and fully distributed algorithms are proposed to determine the movement of sinks and their residence location based on maximizing the value of coded data and the type of data dead time. By simulating, the optimal method and the use of coding and proposed algorithms, reduce the runtime and energy consumption and increase the value of collected data and network lifetime than non-coding methods. Manuscript profile
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  5 - Using a multi-objective optimization algorithm for tasks allocate in the cloud-based systems to reduce energy consumption
  sara tabaghchimilan nima jafari novimipour
  20.1001.1.27170414.1399.12.43.5.6
  Nowadays, new technologies have increased the demand for business in the web environment.Increasing demand will increase the variety and number of services. As a result, the creation of large-scale computing data centers has high operating costs and consumes huge amount More

  Nowadays, new technologies have increased the demand for business in the web environment.Increasing demand will increase the variety and number of services. As a result, the creation of large-scale computing data centers has high operating costs and consumes huge amounts of electrical power. On the other hand, inadequate and inadequate cooling systems not only cause excessive heating of resources and shorten the life of the machines. It also produces carbon that plays an important role in the weather. Therefore, they should reduce the total energy consumption of these systems with proper methods. In this research, an efficient energy management approach is provided in virtual cloud data centers, which reduces energy consumption and operational costs, and brings about an increase in the quality of services. It aims to provide a resource allocation strategy for cloud systems with the goal of reducing energy, cost of implementation and examining its use in cloud computing. The results of the simulation show that the proposed method in comaprision to NPA, DVFS, ST and MM methods can reduce the average energy consumption up to 0.626 kWh, also the need to immigration and SLA violation declined up to 186 and 30.91% respectively. Manuscript profile
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  6 - Investigating the Information and Communication Technology Deployment Impact on Energy Expenditures of Iranian households (A Provincial Approach)
  Elham Hosseinzadeh َAmir Hossein Mozayani
  20.1001.1.27170411.1400.13.49.3.8
  Nowadays, investing in information and communication technology (ICT) is inevitable, because it affects various aspects of human life, including the economy. Due to the rapid growth of population, increasing energy demand, and limited energy resources, one of the bas More

  Nowadays, investing in information and communication technology (ICT) is inevitable, because it affects various aspects of human life, including the economy. Due to the rapid growth of population, increasing energy demand, and limited energy resources, one of the basic measures to achieve sustainable development in countries, is optimization and reform of energy consumption structures. Given that the home sector is one of the main sectors of energy consumption, one of the effective approaches in reducing and managing household energy expenditures is to use ICT capabilities. In this regard, in this study, the effect of ICT expansion on energy consumption of urban households in Iran using the Panel Data method and GLS model during the period 2008-2015 and in the form of provincial data has been analyzed. The results indicate that in some models, a significant reducing effect of ICT on energy expenditure was observed. However, in most of the estimated models, there is no significant reducing effect of ICT on household energy expenditure. It seems that the main reasons for this are the subsidy structure governing energy prices, the low share of energy in total household consumption expenditures, the lack of proper consumption culture. Manuscript profile
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  7 - WSTMOS: A Method For Optimizing Throughput, Energy, And Latency In Cloud Workflow Scheduling
  Arash Ghorbannia Delavar Reza Akraminejad sahar mozafari
  20.1001.1.27170411.1402.15.57.5.0
  Application of cloud computing in different datacenters around the world has led to generation of more co2 gas. In addition, energy and throughput are the two most important issues in this field. This paper has presented an energy and throughput-aware algorithm for sche More

  Application of cloud computing in different datacenters around the world has led to generation of more co2 gas. In addition, energy and throughput are the two most important issues in this field. This paper has presented an energy and throughput-aware algorithm for scheduling of compressed-instance workflows in things-internet by cluster processing in cloud. A method is presented for scheduling cloud workflows with aim of optimizing energy, throughput, and latency. In the proposed method, time and energy consumption has been improved in comparison to previous methods by creating distance parameters, clustering inputs, and considering real execution time. In WSTMOS method by considering special parameters and real execution time, we managed to reach the optimized objective function. Moreover, in the proposed method parameter of time distance of tasks to virtual machines for reduction of number of migration in virtual machines was applied. In WSTMOS method by organizing the workflow inputs to low, medium and heavy groups and also by distributing appropriate load on more suitable servers for processors threshold, we accomplished to optimize energy and cost. Energy consumption was reduced by 4.8 percent while the cost was cut down by 4.4 percent using this method in comparison to studied method. Finally, average delay time, power and workload are optimized in comparison to previous methods. Manuscript profile