scholarly journals A Dynamic Programming Solution for Energy-Optimal Video Playback on Mobile Devices

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Minseok Song ◽  
Jinhan Park
Keyword(s):  
Dynamic Programming ◽  
Low Frequency ◽  
Practical Method ◽  
Video Data ◽  
Buffer Size ◽  
Operating Voltage ◽  
Video Playback ◽  
Programming Technique ◽  
Full Speed ◽  
Dynamic Voltage

Due to the development of mobile technology and wide availability of smartphones, the Internet of Things (IoT) starts to handle high volumes of video data to facilitate multimedia-based services, which requires energy-efficient video playback. In video playback, frames have to be decoded and rendered at high playback rate, increasing the computation cost on the CPU. To save the CPU power, dynamic voltage and frequency scaling (DVFS) dynamically adjusts the operating voltage of the processor along with frequency, in which appropriate selection of frequency on power could achieve a balance between performance and power. We present a decoding model that allows buffering frames to let the CPU run at low frequency and then propose an algorithm that determines the CPU frequency needed to decode each frame in a video, with the aim of minimizing power consumption while meeting buffer size and deadline constraints, using a dynamic programming technique. We finally extend this algorithm to optimize CPU frequencies over a short sequence of frames, producing a practical method of reducing the energy required for video decoding. Experimental results show a system-wide reduction in energy of27%, compared with a processor running at full speed.

scholarly journals Dynamic Operation Management of a Renewable Microgrid including Battery Energy Storage

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Shaozhen Jin ◽  
Zhizhong Mao ◽  
Hongru Li ◽  
Wenhai Qi
Keyword(s):  
Dynamic Programming ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Main Idea ◽  
Optimal Operation ◽  
Optimal Control Strategy ◽  
Programming Technique ◽  
Battery Energy Storage ◽  
Comparison Results ◽  
Battery Energy

In this paper, a novel dynamic programming technique is presented for optimal operation of a typical renewable microgrid including battery energy storage. The main idea is to use the scenarios analysis technique to proceed the uncertainties related to the available output power of wind and photovoltaic units and dynamic programming technique to obtain the optimal control strategy for a renewable microgrid system in a finite time period. First, to properly model the system, a mathematical model including power losses of the renewable microgrid is established, where the uncertainties due to the fluctuating generation from renewable energy sources are considered. Next, considering the dynamic power constraints of the battery, a new performance index function is established, where the Lagrange multipliers and interior point method will be presented for the equality and inequality operation constraints. Then, a feedback control scheme based on the dynamic programming is proposed to solve the model and obtain the optimal solution. Finally, simulation and comparison results are given to illustrate the performance of the presented method.

scholarly journals A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming

2021 ◽  
Vol 27 (1) ◽  
pp. 112-129
Author(s):  
Saba Qasim Jabbar ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Video Streaming ◽  
Video Quality ◽  
Prediction Algorithm ◽  
Buffer Size ◽  
Video Playback ◽  
Buffer Occupancy ◽  
Simulation Results ◽  
Streaming Technology ◽  
The Impact ◽  
Buffer Structure

A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video streaming, it may also cause a video bitrate oscillation. So the video buffer structure is adjusted by adding two thresholds as operating points for overflow and underflow states to filter the impact of throughput fluctuation on video buffer occupancy level. Then a bandwidth prediction algorithm is proposed for enhancing the performance of video bitrate adaptation. This algorithm's work depends on the current video buffer level, video bitrate of the previous segment, and iterative throughput measurements to predict the best video bitrate for the next segment. Simulation results show that reserving a bandwidth margin is better in adapting the video bitrate under bandwidth variation and then reducing the risk of video playback freezing. Simulation results proved that the playback freezing happens two times: firstly, when there is no bandwidth margin used and secondly, when the bandwidth margin is high while smooth video bitrate is obtained with moderate value. The proposed scheme is compared with other two schemes such as smoothed throughput rate (STR) and Buffer Based Rate (BBR) in terms of prediction error, QoE preferences, buffer size, and startup delay time, then the proposed scheme outperforms these schemes in attaining smooth video bitrates and continuous video playback.

scholarly journals Image compression based on classification coding of constant-pitched functions transformers

2021 ◽  
pp. 48-62
Author(s):  
Vladimir Barannik ◽  
Andrii Krasnorutsky ◽  
Sergii Shulgin ◽  
Valerii Yeroshenko ◽  
Yevhenii Sidchenko ◽  
...  
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
High Frequency ◽  
Orthogonal Transformation ◽  
Low Frequency ◽  
Information Delivery ◽  
Video Data ◽  
Arithmetic Coding ◽  
Video Images ◽  
Frequency Components

The subject of research in the article are the processes of video image processing using an orthogonal transformation for data transmission in information and telecommunication networks. The aim is to build a method of compression of video images while maintaining the efficiency of its delivery at a given informative probability. That will allow to provide a gain in the time of delivery of compressed video images, a necessary level of availability and authenticity at transfer of video data with preservation of strictly statistical regulations and the controlled loss of quality. Task: to study the known algorithms for selective processing of static video at the stage of approximation and statistical coding of the data based on JPEG-platform. The methods used are algorithm based on JPEG-platform, methods of approximation by orthogonal transformation of information blocks, arithmetic coding. It is a solution of scientific task-developed methods for reducing the computational complexity of transformations (compression and decompression) of static video images in the equipment for processing visual information signals, which will increase the efficiency of information delivery.The following results were obtained. The method of video image compression with preservation of the efficiency of its delivery at the set informative probability is developed. That will allow to fulfill the set requirements at the preservation of structural-statistical economy, providing a gain in time to bring compressed images based on the developed method, relative to known methods, on average up to 2 times. This gain is because with a slight difference in the compression ratio of highly saturated images compared to the JPEG-2000 method, for the developed method, the processing time will be less by at least 34%.Moreover, with the increase in the volume of transmitted images and the data transmission speed in the communication channel - the gain in the time of delivery for the developed method will increase. Here, the loss of quality of the compressed/restored image does not exceed 2% by RMS, or not worse than 45 dB by PSNR. What is unnoticeable to the human eye.Conclusions. The scientific novelty of the obtained results is as follows: for the first time the method of classification (separate) coding (compression) of high-frequency and low-frequency components of Walsh transformants of video images is offered and investigated, which allows to consider their different dynamic range and statistical redundancy reduced using arithmetic coding. This method will allow to ensure the necessary level of availability and authenticity when transmitting video data, while maintaining strict statistical statistics.Note that the proposed method fulfills the set tasks to increase the efficiency of information delivery. Simultaneously, the method for reducing the time complexity of the conversion of highly saturated video images using their representation by the transformants of the discrete Walsh transformation was further developed. It is substantiated that the perspective direction of improvement of methods of image compression is the application of orthogonal transformations on the basis of integer piecewise-constant functions, and methods of integer arithmetic coding of values of transformant transformations.It is substantiated that the joint use of Walsh transformation and arithmetic coding, which reduces the time of compression and recovery of images; reduces additional statistical redundancy. To further increase the degree of compression, a classification coding of low-frequency and high-frequency components of Walsh transformants is developed. It is shown that an additional reduction in statistical redundancy in the arrays of low-frequency components of Walsh transformants is achieved due to their difference in representation. Recommendations for the parameters of the compression method for which the lowest value of the total time of information delivery is provided are substantiated.

Transmission of Image Information in the Network Multimedia Teaching

2014 ◽  
Vol 571-572 ◽  
pp. 867-872
Author(s):  
Xiao Yun Liu ◽  
Li Ting Xiong ◽  
Jian Shen
Keyword(s):  
Information Transmission ◽  
Data Transmission ◽  
Video Data ◽  
Transmission Delay ◽  
Buffer Size ◽  
Information Network ◽  
Teaching System ◽  
Image Information ◽  
Multimedia Teaching ◽  
Network Transmission

To solve the problem of image information transmission delay in the network multimedia teaching system, the compression and multicast solutions are put forward on the basis of usual screen blocking skill of data. According to the characteristics of the multimedia teaching system, the screen changes typically little at smaller intervals. It means that only a few screen blocks, which are changing, are needed to be transferred by screen blocking skill. At the same time, the network video data transmission volume is further curtailed through compression and multicast so that the multimedia information network transmission delay is decreased. The minimal buffer size for allocation is determined to ensure the smooth transmission of video data in the multimedia teaching system.

Using Cluster Analysis and Dynamic Programming for Demand Response Applied to Electricity Load in Residential Homes

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Pattanun Chanpiwat ◽  
Steven A. Gabriel ◽  
Rachel L. Moglen ◽  
Michael J. Siemann
Keyword(s):  
Dynamic Programming ◽  
Demand Response ◽  
Power Market ◽  
Practical Method ◽  
Important Application ◽  
Homogeneous Groups ◽  
Market Participants ◽  
Electricity Load ◽  
Scheduling Tool ◽  
Business As Usual

Abstract This paper develops means to analyze and cluster residential households into homogeneous groups based on the electricity load. Classifying customers by electricity load profiles is a top priority for retail electric providers (REPs), so they can plan and conduct demand response (DR) effectively. We present a practical method to identify the most DR-profitable customer groups as opposed to tailoring DR programs for each separate household, which may be computationally prohibitive. Electricity load data of 10,000 residential households from 2017 located in Texas was used. The study proposed the clustered load-profile method (CLPM) to classify residential customers based on their electricity load profiles in combination with a dynamic program for DR scheduling to optimize DR profits. The main conclusions are that the proposed approach has an average 2.3% profitability improvement over a business-as-usual heuristic. In addition, the proposed method on average is approximately 70 times faster than running the DR dynamic programming separately for each household. Thus, our method not only is an important application to provide computational business insights for REPs and other power market participants but also enhances resilience for power grid with an advanced DR scheduling tool.

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