ASYMPTOTICALLY OPTIMAL LOAD DISTRIBUTION FOR MULTIPATH STREAMING UNDER FEC

2010 ◽  
Vol 24 (4) ◽  
pp. 509-523
Author(s):  
Cathy H. Xia ◽  
Alix L. H. Chow

Multipath streaming protocols have recently attracted much attention because they provide an effective means to provide high-quality streaming over the Internet. Most existing multipath streaming schemes also apply forward error correction (FEC) encoding in the stream so as to provide high-quality streaming of prestored or live media content. However, the problem of how to intelligently split the FEC-encoded stream among multiple available paths has not been fully addressed. Most previous work focused on protocol design or heuristic-based engineering approaches. Exact analysis turns out to be hard, as it involves heavy combinatorics computation. In this article, we develop an analytical model and use asymptotic analysis to address the problem of optimal load distribution. Using asymptotic approximations, we propose a closed-form formulation for the optimal load distribution problem. We then develop interesting properties of the optimal solution based on majorization, interchanging argument, and optimization techniques. These results are surprisingly simple yet insightful. We further demonstrate through simulation that our asymptotic solution works quite well in practice.

2014 ◽  
Vol 494-495 ◽  
pp. 1715-1718
Author(s):  
Gui Li Yuan ◽  
Tong Yu ◽  
Juan Du

The classic multi-objective optimization method of sub goals multiplication and division theory is applied to solve optimal load distribution problem in thermal power plants. A multi-objective optimization model is built which comprehensively reflects the economy, environmental protection and speediness. The proposed model effectively avoids the target normalization and weights determination existing in the process of changing the multi-objective optimization problem into a single objective optimization problem. Since genetic algorithm (GA) has the drawback of falling into local optimum, adaptive immune vaccines algorithm (AIVA) is applied to optimize the constructed model and the results are compared with that optimized by genetic algorithm. Simulation shows this method can complete multi-objective optimal load distribution quickly and efficiently.


2020 ◽  
Vol 13 (1) ◽  
pp. 114-129 ◽  
Author(s):  
Omar Abdel Wahab ◽  
Jamal Bentahar ◽  
Hadi Otrok ◽  
Azzam Mourad

2014 ◽  
Vol 511-512 ◽  
pp. 954-957
Author(s):  
Yue Liang Liu

In order to overcome the low speed serial links of the bandwidth low, easy to produce decline, low rate of transmission characteristics, This paper design a transmission optimization system, In the system, this paper proposes a forward error correction and data compression transmission optimization combined method, Transmission optimization technology in recent years has been widely used in the field of network communication. Transmission optimization technology has been shown to improve the utilization rate of bandwidth, improve transmission efficiency. In this paper, the transmission optimization of the forward error correction technology has carried on the simulation test, And the analysis of experimental data were compared before and after the optimization, The experimental results show that the proposed transmission optimization method for low speed serial links the data transmission efficiency has been obviously increased . Transmission Optimization Technology Transmission optimization techniques include forward error correction, data compression, and adaptive protocol of three parts, combined guarantee bad message transmission efficiency in transmission environment. This paper mainly studies the transmission on the wireless communication channel environment serial links optimization techniques. Bandwidth Compression Technology. Bandwidth compression is transmitted through compression technology after traditional smaller packets, such as real time transmission of packets is more than the number of packets before compression, so as to realize the goal of improving transmission speed. Bandwidth compression technology is not really to data compression, because the network of packet size and length size has strict rules, if the size of the data has changed, and is also change his nature. So the true meaning of bandwidth compression is part of the data in other ways to replace, including cache corresponding not change information data or with short data instead of long, Then after receiving inverse substitution process, complete the purpose of saving bandwidth. The most commonly used three kinds of compression algorithm: Huffinan coding, dictionary coding and arithmetic coding [.


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