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A tree-structured index allocation method with replication over multiple broadcast channels in wireless environments

机译:一种在无线环境中通过多个广播信道进行复制的树形索引分配方法

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摘要

Broadcast has often been used to disseminate frequently requested data efficiently to a large volume of mobile units over single or multiple channels. Since mobile units have limited battery power, the minimization of the access and tuning times for the broadcast data is an important problem. There have been many research efforts that focus on minimizing access and tuning times by providing indexes on the broadcast data. We have studied an efficient index allocation method for broadcast data with skewed access frequencies over multiple physical channels which cannot be coalesced into a single high bandwidth channel. Previously proposed index allocation techniques have one of two problems. The first problem is that they require equal size for both index and data. The second problem is that their performance degrades when the number of given physical channels is not enough. These two problems result in an increased average access time for the broadcast data. To cope with these problems, we propose a tree-structured index allocation method. Our method minimizes the average access time by broadcasting the hot data and their indices more frequently than the less hot data and their indexes over the dedicated index and data channels. We present an in-depth experimental and theoretical analysis of our method by comparing it with other similar techniques. Our performance analysis shows that it significantly decreases the average access and tuning times for the broadcast data over existing methods.
机译:广播经常被用来通过单个或多个信道将经常请求的数据有效地传播到大量的移动单元。由于移动单元的电池电量有限,因此最小化广播数据的访问和调整时间是一个重要的问题。已经有许多研究工作着重于通过在广播数据上提供索引来最小化访问和调整时间。我们已经研究了一种有效的索引分配方法,用于无法在多个物理信道上合并到单个高带宽信道上的具有偏斜访问频率的广播数据。先前提出的索引分配技术具有两个问题之一。第一个问题是它们要求索引和数据的大小相等。第二个问题是,当给定物理通道的数量不足时,它们的性能会降低。这两个问题导致广播数据的平均访问时间增加。为了解决这些问题,我们提出了一种树形结构的索引分配方法。我们的方法通过在专用索引和数据通道上比不那么热的数据及其索引更频繁地广播热数据及其索引,从而使平均访问时间最小化。通过与其他类似技术进行比较,我们对方法进行了深入的实验和理论分析。我们的性能分析表明,与现有方法相比,它显着减少了广播数据的平均访问和调整时间。

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