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Some of the default video allocation scenarios are also been discussed.
In order to overcome these challenges, an efficient video allocation algorithm is a desirable and necessary option.
In this paper, the authors developed a new video allocation algorithm for flash-based SSDs storage media systems.
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Then, we investigate the performance of our video frames allocation algorithm by comparing it with the random video frames allocation scheme.
In this paper, we present a unified optimization framework for video rate allocation over wireless networks.
In this subsection, we intend to find an optimal video frames allocation algorithm by formulating it as 0-1 Knaproblemroblem.
In this subsection, we compare our cooperative relay selection scheme and video frames allocation algorithm with the corresponding random methods, respectively.
In a typical video rate allocation problem, the objective is to optimally distribute a source rate budget among a set of (in dependently coded data units to minimize the total distortion.
As Figure 6 shows, the realistic cooperative rate in the situation where applying the proposed video frames allocation is almost as same as the transmission rate for 720P HD video, which implies that our scheme can support HD video transmissions.
The video frames allocation algorithm which is based on the Knapsack problem is depicted in Algorithm 3. In this section, we evaluate the performance of our cooperative HD video transmission scheme by simulations.
The objective of our video frames allocation is to determine the subset Q i ⊆{1,2,⋯,M i } such that: text{max} sumlimits_{tin Q_{i}}D_{t}^{i*}, (35).
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