scholarly journals Energy Efficiency for Data Offloading in D2D Cooperative Caching Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Weiguang Wang ◽  
Hui Li ◽  
Wenjie Zhang ◽  
Shanlin Wei
Keyword(s):  
Energy Efficiency ◽  
Optimization Algorithm ◽  
Network Performance ◽  
Transmission Probability ◽  
Maximum Energy ◽  
Joint Optimization ◽  
Data Traffic ◽  
Data Offloading ◽  
Transmit Power ◽  
Policy Optimization

D2D communication improves the cellular network performance by using proximity-based services between adjacent devices, which considered is an effective way to solve the problem of spectrum scarcity caused by tremendous mobile data traffic. If the cache-enabled users are willing to send the cached file to the requesters, the content delivery traffic can be offloaded through the D2D link. In this paper, we strive to find the maximum energy efficiency of the D2D caching network through the joint optimization of cache policy and content transmit power. Specifically, based on stochastic geometry-aided modeling of the network, we derive the data offloading rate in closed form, which jointly considers the effects of success sensing probability and success transmission probability. According to the data offloading rate, we formulate a joint optimization problem integrating cache policy and transmit power to maximize the system energy efficiency. To solve this problem, we propose two optimization algorithms that the cache policy optimization algorithm based on gradient update and the joint optimization algorithm. The simulation results demonstrate that the joint optimization has twice the superiority in improving the energy efficiency of the D2D caching network compared with other schemes.

scholarly journals Resource Allocation for Green Cognitive Radios: Energy Efficiency Maximization

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Zhou Yang ◽  
Wenqian Jiang ◽  
Gang Li
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Cognitive Radio ◽  
Cognitive Radios ◽  
Maximum Energy ◽  
Secondary User ◽  
Power Constraint ◽  
Transmit Power ◽  
Delay Sensitive ◽  
Allocation Strategies

Green cognitive radios are promising in future wireless communications due to high energy efficiency. Energy efficiency maximization problems are formulated in delay-insensitive green cognitive radio and delay-sensitive green cognitive radio. The optimal resource allocation strategies for delay-insensitive green cognitive radio and delay-sensitive green cognitive radio are designed to maximize the energy efficiency of the secondary user. The peak interference power and the average/peak transmit power constraints are considered. Two algorithms based on the proposed resource allocation strategies are proposed to solve the formulated problems. Simulation results show that the maximum energy efficiency of the secondary user achieved under the average transmit power constraint is higher than that achieved under the peak transmit power constraint. It is shown that the design of green cognitive radio should take the tradeoff between its complexity and its achievable maximum energy efficiency into consideration.

scholarly journals Joint Optimization of Pico-Base-Station Density and Transmit Power for an Energy-Efficient Heterogeneous Cellular Network

2019 ◽  
Vol 11 (10) ◽  
pp. 208
Author(s):  
Jie Yang ◽  
Ziyu Pan ◽  
Hengfei Xu ◽  
Han Hu
Keyword(s):  
Energy Efficiency ◽  
Focal Point ◽  
Transmission Rate ◽  
Optimization Method ◽  
Base Station ◽  
Base Stations ◽  
Joint Optimization ◽  
Total Power ◽  
Transmit Power ◽  
Total Power Consumption

Heterogeneous cellular networks (HCNs) have emerged as the primary solution for explosive data traffic. However, an increase in the number of base stations (BSs) inevitably leads to an increase in energy consumption. Energy efficiency (EE) has become a focal point in HCNs. In this paper, we apply tools from stochastic geometry to investigate and optimize the energy efficiency (EE) for a two-tier HCN. The average achievable transmission rate and the total power consumption of all the BSs in a two-tier HCN is derived, and then the EE is formulated. In order to maximize EE, a one-dimensional optimization algorithm is used to optimize picocell BS density and transmit power. Based on this, an alternating optimization method aimed at maximizing EE is proposed to jointly optimize transmit power and density of picocell BSs. Simulation results validate the accuracy of the theoretical analysis and demonstrate that the proposed joint optimization method can obviously improve EE.

scholarly journals A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3147
Author(s):  
Kiyoung Kim ◽  
Namdoo Kim ◽  
Jongryeol Jeong ◽  
Sunghwan Min ◽  
Horim Yang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Hybrid Electric Vehicle ◽  
New Technologies ◽  
New Technology ◽  
Dynamic Performance ◽  
Minimum Principle ◽  
Component Sizing ◽  
Hybrid Electric

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Powder Spheroidization Using Induction Plasma Technology

2000 ◽  
Author(s):  
N.M. Dignard ◽  
M.I. Boulos
Keyword(s):  
Energy Efficiency ◽  
Maximum Energy ◽  
Operating Conditions ◽  
Side Reactions ◽  
Induction Plasma ◽  
Silica Alumina ◽  
Change In The Mean ◽  
The Individual ◽  
Semi Empirical ◽  
Objective Being

Abstract An experimental study of the spheroidization efficiency of induction plasma processes was completed. The main objective being to obtain models which could be subsequently used for the prediction of the spheroidization efficiency for various powders and plasma operating conditions. Silica, alumina, chromium oxide and zirconia powders were treated during the experimentation. For the plasma treatment of the powders the installation used had a maximum available power of 50 kW with an operating frequency of 3 MHz. Operating conditions were varied such to minimize side reactions and the evaporation of powders. The resulting powders did show the presence of cavities and a slight change in the mean diameters. The maximum energy efficiency based semi-empirical model did predict the spheroidization efficiency of the particles beyond a defined critical point known as the maximum energy efficiency point. For the model, the maximum energy efficiency is distinct for the individual powders but remain within a defined range which is reflected in the small variations in the Z constant.

scholarly journals A New Approach for Real Time Train Energy Efficiency Optimization

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2660 ◽  
Author(s):  
Agostinho Rocha ◽  
Armando Araújo ◽  
Adriano Carvalho ◽  
João Sepulveda
Keyword(s):  
Energy Efficiency ◽  
Simulated Annealing ◽  
Energy Consumption ◽  
Real Time ◽  
Optimization Algorithm ◽  
Normal Operation ◽  
Speed Profile ◽  
Railway Systems ◽  
Optimal Speed ◽  
Advisory System

Efficient use of energy is currently a very important issue. As conventional energy resources are limited, improving energy efficiency is, nowadays, present in any government policy. Railway systems consume a huge amount of energy, during normal operation, some routes working near maximum energy capacity. Therefore, maximizing energy efficiency in railway systems has, recently, received attention from railway operators, leading to research for new solutions that are able to reduce energy consumption without timetable constraints. In line with these goals, this paper proposes a Simulated Annealing optimization algorithm that minimizes train traction energy, constrained to existing timetable. For computational effort minimization, re-annealing is not used, the maximum number of iterations is one hundred, and generation of cruising and braking velocities is carefully made. A Matlab implementation of the Simulated Annealing optimization algorithm determines the best solution for the optimal speed profile between stations. It uses a dynamic model of the train for energy consumption calculations. Searching for optimal speed profile, as well as scheduling constraints, also uses line shape and velocity limits. As results are obtained in seconds, this new algorithm can be used as a real-time driver advisory system for energy saving and railway capacity increase. For now, a standalone version, with line data previously loaded, was developed. Comparison between algorithm results and real data, acquired in a railway line, proves its success. An implementation of the developed work as a connected driver advisory system, enabling scheduling and speed constraint updates in real time, is currently under development.

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