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- 저자 : ( Tein-yaw Chung ) (검색결과 2 건)
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Hybrid Algorithm for Selecting Multimedia Network Connections in Heterogeneous Networks
Tein-Yaw Chung,Ibrahim Mashal,Fong-Ching Yuan,Yuan-Hao Chiang,Osama Alsaryrah 한국산학기술학회 2015 SmartCR Vol.5 No.6
The heterogeneity of mobile and wireless networks exposes mobile users to different access network technologies. In the past, many paradigms have been introduced, such as Always Best Connected (ABC) and Always Best Network Connection (ABNC), to meet user’s preferences. However, they fail to consider multimedia services consisting of video and data, besides voice, for both source and destination. This paper presents a new model called Always Best Multiple Network Connection (ABMNC) to support multimedia services. ABMNC is first formulated as a Multiple Attribute Decision Making (MADM) problem with an embedded utility-based Multiple Knapsack Problem (MKP). In order to reduce computation complexity, the MADM hierarchy of ABMNC is decomposed into a number of iterated sub-MADM hierarchies, and a hybrid Analytic Hierarchy Process (AHP) and a Simple Additive Weighting (SAW) scheme are used to solve them. A novel Heuristic Rate Allocation Algorithm (HRAA) is then presented to reduce the computation complexity of the assignment and rate allocation. Moreover, a comprehensive Heuristic Path Selection Algorithm (HPSA) is proposed to efficiently resolve the ABMNC hierarchy. Finally, computer simulation is performed to study ABMNC, and the results show that our approach, most of the time, chooses the optimal network connections.
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A Novel Bandwidth Estimation Method Based on MACD for DASH
( Van-huy Vu ),( Ibrahim Mashal ),( Tein-yaw Chung ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.3
Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adap-tively. However, experiment results show that current schemes either adapt slowly to net-work changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Av-erage Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the present-ed scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.
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