Sharif Digital Repository

Shortage of energy sources in the new decade along with the increasing level of greenhouse gas emissions urges researchers in the field of energy to explore for the new source of energy as well as seeking for methods for usage of available energy resources more efficiently. Therefore, development of building with low level of energy usage may significantly reduce the need for grid energy. This can be met with new construction materials to reduce the energy consumption, using renewable energies sources such as solar and wind as well as design and development of materials with capability to store energy. The use of materials which can store energy and release it when needed has been considered... 

Buildings are responsible for 40% of total energy consumption worldwide. A significant portion of this energy contributes to building temperature control, and energy storage is an effective way to reduce energy consumption and to levelize the supply of heat load. A solution for reducing energy consumption in the building is to increase the thermal inertia of the building and to store energy using smart materials in the building components. Materials with phase change can stabilize the internal temperature of the building.In the present study, model is exmined with the help of modeling the thermal behavior of a room in Tehran in summer, using MATLAB software. The problem is solved by the... 

Buildings account for more than 30% of the world’s total energy consumption. Among building end-uses, air conditioning and in particular cooling systems have a major share of more than 50%. Therefore, design of optimal controllers for AC systems has become increasingly important. Classical and model-free control methods typically lack the ability to optimize energy consumption. On the other hand, model-based optimal control methods rely on precise modeling, which is difficult to acquire due to the complexity of the AC system dynamics.In recent years, deep reinforcement learning has become a popular choice for optimal control of systems with complex dynamics. In this thesis, a deep... 

In recent years, Internet traffic has nearly doubled in the core network every two years, and it is expected to continue to grow in the future. With this growth, there is a need for very high capacity and economically efficient transmission systems, which optical communication is the best choice. Elastic optical network (EON) is one of the best options for achieving this goal in the future. Unlike existing networks, the transmission parameters of EON will be customizable, which will have an essential role in optimizing bandwidth assignment. The problem facing scientists today is to approach the final physical capacity of current optical fibers. The solution proposed for this challenge is... 

Machine learning algorithms are achieving state-of-the-art performance in many various applications such as image processing, machine vision, speech recognition, diagnosis diseases, robotics, military, and aerospace. For decades, the usage of machine learning algorithms especially Neural Network Algorithms (NNA) has been restricted due to their complexity and high computation time of available inefficient hardwares. Although advances in technology and the emergence of powerful processors has increased the usage of NNAs, especially Deep Neuaral Networks (DNNs), the research gap in machine learning hardware platform with high performance as well as high energy efficiency is still remaining.... 

Virtualization has provided good and efficient use of resources in today datacenters. In this environment, modules of multi-tier applications can run on several Virtual Machines (VMs). VMs that are dedicated to a module often need to transfer data among themselves, and also to the VMs in other modules, and hence, the overall application runtime may be increased if the communicating VMs are put on far physical machines; consequently, servers must be up for a longer time and will consume more energy. Consolidating several VMs on a single Physical Machine (PM) effectively reduces the total computing power consumption, but we show that it is also important to consider the above inter-VM... 

This research examines the impact of road transport fleet renewal on the transportation behavior of vehicles in Iran. The study identifies different effects of fleet renewal in different years. The method of fixed effects estimation is used to analyze the dataset of Iran's domestic bills of lading between 1394 and 1400, which contains information on over 200 million bills of lading issued for shipments of more than 490 thousand road transport vehicles. The findings indicate that vehicles with a lifetime of less than one year (≤1) move about 1.4 fewer cargoes per month on average compared to those with a lifetime of more than 35 years (≥35). Per trip, they carry 1.9 tons less, travel 100 km... 

Delay Tolerant Networks (DTNs) are sparse networks in which intermittent connectivity happens due to energy shortage or high mobility and long latency is unavoidable.These networks have a wide range of applications in our daily life such as internet of moving things. In delay tolerant networks, finding an end to end path between source and destination is almost impossible. Therefore, routing can’t be done based on finding an end to end path but it has to be done based on hop by hop sessions. In this thesis, we aim to represent an efficient routing algorithm for delay tolerant networks that can improve delivery probability, delivery cost and delivery latency.Our proposed routing algorithm is... 

In this thesis the superstructure of continuous monitoring system has been developed to help energy service companies’ network. Suggested superstructure consists of three main sections: data acquisition, data analysis and decision-making, optimizer. Historical data and data which picked up by sensors are imported in decision support tool. Input data are analyzed by technical, economical and environmental models and converted to actionable indicator for best management of the project to promote energy saving project. Because the ESCO income obtained from the energy saving project, development of analytical decision support tool will help ESCO to evaluate the procedure of the project.... 

Wireless sensor networks (WSNs) are tiny devices with limited computation and power supply. For such devices, data transmission is a very energy-consuming operation. Data aggregation eliminates redundancy and minimizes the number of transmissions in order to save energy. This research explores the efficiency of data aggregation by focusing on different aspects of the problem such as energy efficiency, latency and accuracy. To achieve this goal, we first investigate data aggregation efficiency with constraint on delay, which can be compatible with other important system properties such as energy consumption and accuracy. By simulation, we will show that, depending on the application, we can... 

Wireless Sensor Networks (WSNs) consist of sensor nodes that are connected to each other and are widely used in many applications to acquire and process information. WSN nodes are battery powered, therefore energy management is a key factor for long live network. Node radio transceiver unit uses the most part of energy resource of the node and as a result limits the network lifetime. One way to prolong lifetime of network is to utilize routing protocols to manage energy consumption. To have an energy efficient protocol, we can apply cluster organization on the network, where sensor nodes are partitioned into groups called cluster. Then, the whole cluster data is sent through Cluster Head... 

Wireless Sensor Network (WSN) is a rapidly growing technology that is used to meet different requirements of a wide range of applications. Energy conservation is one of the main design challenges in WSNs due to limited energy resources. Routing plays a significant role for energy efficient communication in WSNs. Although there are many research studies that utilize energy efficient routing to conserve energy in WSNs, there are a few works that took advantage of machine learning techniques for saving energy through energy efficient routing.The main goal of this thesis is to indicate that machine learning is a functional approach to many problems in WSNs. To fulfill this goal we first... 

Due to rapid growth of energy consumption in recent years, extensive efforts to improve energy efficiency in production and consumption sectors have been done in order to reduce energy consumption in these sectors. The primary assumption is that improving energy efficiency has a one-to-one impact on reducing energy consumption, but in practice this is not true in all cases. In fact, by elevating energy efficiency, the cost of energy services is decreased and, thus, remained accessible income is increased. This issue will increase the demand for all energy and non-energy commodities, therefore, it will have influence on their supply. The effects of this variation in supply can be spread in... 

Today, building sectors account for 34% of total energy consumption in Iran. Increasing demand of the comfort level along with population growth necessitates much more attention about energy requirements in the country. Such phenomenon has already raised concerns about the heavy environmental impacts. The present research studies minimization of global warming potential effect for an educational building by developing life cycle optimization model. The Department of Engineering of Sharif University of Technology is selected as the case study and optimal solutions has been achieved for this building. Results state that implementing cogeneration and renewable energies can reduce20 -25% of the... 

The present study aims to reduce the carbon footprint of greenhouse products to provide a decision tool for sustainable development of greenhouses. In order to provide this decision tool, the impact of four scenarios or energy-efficient technology for greenhouse heating, including: combine heat and power system(CHP), new greenhouse covering material, industrial symbiosis, and solar collector on the carbon footprint of greenhouse products has been studied because one of the main factors in the release of carbon footprints of greenhouse products is the use of fossil fuels for greenhouse heating. Energy modeling has been used to estimate the amount of heating, cooling, and artificial lighting... 

Increasing the workload of physical machines in data centers, performance of the system decreases and energy consumption increases. Various methods have been proposed to overcome this challenge and solve the problem. One of these solutions is the migration of virtual machines (VMs) from the over-loaded physical machine (PM) to another one, namely the under-loaded PM, in the clouds, which is effective in increasing the performance of the system and improving energy consumption When the performance of a PM is less than a certain threshold, due to overload, migration of the selected VM to a candidate PM can improve performance, if it is done in an intelligent way. Choosing the best suitable VM... 

Optimization of energy consumption is generally important in mobile networks and in particular in automotive networks. One of the challenges of installing roadside units in automotive case networks is to provide energy to the equipment assigned to these units. In some cases, power is easily available, but in many places, the cost of energy is very high and does not have economic justification. Therefore, optimization of energy consumption in roadside unit is of great importance. Typically, vehicles limitations in terms of energy consumption for communications are far lower than that of a roadside unit. In this dissertation, part of roadside communication to vehicles is shifted to the... 

With a growing concern on the considerable energy consumed by data centers, research efforts are targeting toward green data centers with higher energy efficiency. Networks are essential to today’s highly instrumented and connected society. Currently responsible for a fraction of the energy the IT sector consumes, networks rely on equipments that often use a constant amount of power regardless of their utilization; a worsening scenario as traffic is expected to increase by a factor of three in the next few years. Datacenter networks, for instance, employ devices that consume several kilowatts of power even when idle. This work aims to improve the energy efficiency of datacenter networks by... 

As far as reliable supply and cost-effective methods of power delivery to end-users are concerned, new advancements in smart grids and, in particular, smart pricing are of high significance to grid operators. In the recent decade, there has been a considerable raise in penetration of renewable energy resources and also the number of hybrid electric vehicles which can act as a huge mobile storage in the network. Hence, finding a practical and cost-effective method of management of all these new resources and avoiding potential problems associated with them seems to be of high importance. In this study, first, the response of demand to pricing signals has been modeledAfterwards, the response... 

In recent years, GPUs have become a popular choice for high-performance general-purpose systems. However, since general-purpose applications do not always utilize processing and memory resources efficiently, energy consumption in these systems has not been managed effectively. As the variety of resources within GPUs continues to increase, the problem of low utilization has become more critical. Past solutions have focused on integrating resources and using multi-tasking, but these methods have limitations in terms of performance and security. Therefore, this research proposes new methods for improving the resource utilization and energy efficiency of GPUs. This dissertation first examines...