Improving Video Transmission in Software Defined Wired and Wireless Networks using Multi-Path Transmission

Chih-Heng Ke,Yeong-Sheng Chen,Yun-Shuai Yu 한국통신학회 2017 Journal of communications and networks Vol.19 No.6

Recently, increasing attention has been paid to the studyof applying software defined networks to improve video transmission. Compared with the existing studies which focus on a wirednetwork, this study proposed a multi-path transmission mechanismfor improving the performance of transmitting videos from awired network to a wireless one in a software defined network environment. In the proposed mechanism, a mobile host could applynetwork bonding to integrate several physical or virtual wirelessnetwork modules, each of which was connected to a different accesspoint, into a combined device. Thus, multiple wireless links ofthe mobile host could be established and hence multiple transmissionpaths from the video source in the wired network to the mobilehost were derived. In addition, different amount of video packetswere allocated onto different transmission paths so as to maximizethe performance of the multi-path transmission. According to theresults of our experiments, the proposed mechanism can enhancethe performance of transmission in terms of Peak Signal to NoiseRatio (PSNR).

myEvalSVC: an Integrated Simulation Framework for Evaluation of H.264/SVC Transmission

( Chih-heng Ke ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.1

The ever-increasing demand for H.264 scalable video coding (H.264/SVC) distribution motivates researchers to devise ways to enhance the quality of video delivered on the Internet. Furthermore, researchers and practitioners in general depend on computer simulators to analyze or evaluate their designed network architecture or proposed protocols. Therefore, a complete toolset, which is called myEvalSVC, for evaluating the delivered quality of H.264/SVC transmissions in a simulated environment is proposed to help the network and video coding research communities. The toolset is based on the H.264 Scalable Video coding streaming Evaluation Framework (SVEF) and extended to connect to the NS2 simulator. With this combination, people who work on video coding can simulate the effects of a more realistic network on video sequences resulting from their coding schemes, while people who work on network technology can evaluate the impact of real video streams on the proposed network architecture or protocols. To demonstrate the usefulness of the proposed new toolset, examples of H.264/SVC transmissions over 802.11 and 802.11e are provided.

Applying Deep Reinforcement Learning to Improve Throughput and Reduce Collision Rate in IEEE 802.11 Networks

( Chih-heng Ke ),( Lia Astuti ) 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.1

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.

Applying multi-agent deep reinforcement learning for contention window optimization to enhance wireless network performance

Ke Chih-Heng,Astuti Lia 한국통신학회 2023 ICT Express Vol.9 No.5

This paper investigates the Contention Window (CW) optimization problem in multi-agent scenarios, where the fully cooperative among mobile stations is considered. A partially observable environment is employed to model and analyze the CW optimization problem, and Smart Exponential-Threshold-Linear with Deep Q-learning Network (SETL-DQN) Multi-Agent (MA) algorithm is proposed to obtain the optimal system throughput through the CW Threshold optimization. In the determined scenarios, SETL-DQN(MA) can effectively cope with the mutual interaction among mobile stations. The simulation results show that our proposed method is superior from both static and dynamic scenarios and has the highest optimum packet transmission efficiency.

A reinforcement learning approach for widest path routing in software-defined networks

Ke Chih-Heng,Tu Yi-Hao,Ma Yi-Wei 한국통신학회 2023 ICT Express Vol.9 No.5

In this paper, a routing method based on reinforcement learning (RL) under software-defined networks (SDN), namely the Q-learning widest-path routing algorithm (Q-WPRA), is proposed. This algorithm processes the reward function according to the link bandwidth in the execution environment to find the optimal (i.e., widest) transmission path with the maximum bandwidth between the source and the destination through RL. The experimental results reveal that the Q-WPRA is outperformance than Dijkstra’s algorithm and Dijkstra’s widest-path algorithm to find the widest transmission path in SDN environment under different bandwidths, loss rates, and background traffic.

MyEvalvid_RTP: a Evaluation Framework for More Realistic Simulations of Multimedia Transmission

Chia-Yu Yu,Chih-Heng Ke,Reuy-Shin Chen,Ce-Kuen Shieh,Naveen Chilamkurti 보안공학연구지원센터 2008 International Journal of Software Engineering and Vol.2 No.2

Recently, multimedia is a more and more important Internet service. For multimedia, Quality of service (QoS) support is a crucial requirement. To meet these QoS requirements, researchers develop specific multimedia mechanism to enhance the performance of video transmission. When they evaluate the performance of their mechanism, most researchers use simulation tools to evaluate. However, when using these simulation tools, researchers usually acquire network-level performance metrics, such as throughput. They cannot evaluate video and audio delivered quality by comparing the original and distorted video. However, using network-level performance metrics can not evaluate the delivered quality correctly. To address this issue, some esearchers proposed simulation tool-sets. These simulation tool-sets can evaluate the video delivered quality well. However, they cannot evaluate the audio delivered quality. Therefore, we propose a new simulation tool-set called as MyEvalvid_RTP to achieve more realistic simulations in this paper. By MyEvalvid_RTP, researchers can evaluate both the video delivered quality and the audio delivered quality.

A Computationally Inexpensive Radio Propagation Model for Vehicular Communication on Flyovers and Inside Underpasses

( Muhammad Ahsan Qureshi ),( Ehsan Mostajeran ),( Rafidah Md Noor ),( Azra Shamim ),( Chih-heng Ke ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

Vehicular Ad Hoc Networks (VANETs) utilize radio propagation models (RPMs) to predict path loss in vehicular environment. Modern urban vehicular environment contains road infrastructure units that include road tunnels, straight roads, curved roads flyovers and underpasses. Different RPMs were proposed in the past to predict path loss, but modern road infrastructure units especially flyovers and underpasses are neglected previously. Most of the existing RPMs are computationally complex and ignore some of the critical features such as impact of infrastructure units on the signal propagation and the effect of both static and moving radio obstacles on signal attenuation. Therefore, the existing RPMs are incapable of predicting path loss in flyovers and underpass accurately. This paper proposes an RPM to predict path loss for vehicular communication on flyovers and inside underpasses that considers both the static and moving radio obstacles while requiring only marginal overhead. The proposed RPM is validated based upon the field measurements in 5 GHz frequency band. A close agreement is found between the measured and predicted values of path loss.