The most important reason to use more than one user table space is to manage buffer utilization.
使用多个用户表空间的最重要原因是管理缓冲区的利用率。
With this method, synchronization system can always meet the perceived QoS defined by user. Additionally, it also has high buffer utilization and satisfied end to end delay.
实验表明采用该方法可以使同步系统满足用户提出的可感知服务质量，而且具有较高的缓冲区利用率和满意的端到端时延。
One of the reasons this view was created was to establish Buffer, Warning, and Critical thresholds for CPU utilization.
创建这个视图的原因之一是为CPU利用率建立缓冲、警告和危险阈值。
Increase the size of the log buffer area if there is considerable read activity on a dedicated log disk, or there is high disk utilization.
如果在某个专用的日志磁盘上存在大量的读活动，或者具有较高的磁盘利用率，就增加日志缓冲区域的大小。
Consider buffer pool utilization, which might lead you to make some changes to the previous table space design.
考虑缓冲池的利用率。这可能会使前面的表空间设计产生一些变化。
Once the total available size is determined, this area can be divided into different buffer pools to improve utilization.
一旦确定了总的可用大小，就可以将这个区域划分成不同的缓冲池以提高利用率。
Our second hypothesis was that specifying the buffer pool size affects memory utilization differently at various user loads (Test Case #2).
我们的第二个假设是指定缓冲池大小对内存利用率的影响因用户负载不同而不同（测试案例 #2）。
To calculate the maximum buffer size, DB2 considers all other storage utilization, the operating system, and any other applications.
要计算最大的缓冲区大小，DB 2、操作系统以及其它任何应用程序都必须考虑其它所有存储器的利用率。
In other words, after CPU utilization bumps against the buffer on a regular basis, the server is considered full and is off-limits to LPAR builds.
换句话说，如果CPU利用率经常达到缓冲阈值，就认为服务器满负载了并禁止构建新的LPAR。
When a Power server utilization goes slightly beyond the buffer threshold (two CPUs beyond, to be exact), it crosses the warning threshold (not displayed on graph).
当Power服务器利用率略微超过缓冲阈值时(准确地说，超过两个CPU)，就会触及警告阈值(在图形上没有显示)。
As a result, compression allows more data to be in memory than without compression, which increases the buffer-pool hit ratio and makes higher utilization of the available memory.
因此，相比不压缩，压缩能让内存存储更多的数据，进而提高了缓冲池命中率和可用内存的利用率。
In order to improve the efficiency of the resource utilization of the VOD server and for the high quality of playback in the clients, we propose a novel dynamic buffer management algorithm.
为了提高视频服务器的资源利用率、提高客户端节目的播放质量和流畅性，我们提出一种动态的缓存管理算法。
In the storage tier, it should pay more attention to the rational utilization of the limited resources, and adopt the way of memory buffer to promote systematic function.
存储层的设计尤其要注意对有限设备资源的合理利用，并采用缓存策略来提升系统性能。
The simulation results show that this algorithm can significantly improve the quality-of-service (QoS) performances in terms of low delay, small buffer and high utilization.
仿真实验表明，所提出的算法能够准确地对实时可变比特率视频流量进行预测，有效地降低排队时延，减小队列长度并提高带宽利用率。
Accurate algorithms to compute the performance indexes including data loss possibility, data transmission rate and output channel utilization rate under given finite buffer capacity are given.
给出有限缓冲条件下系统的稳态数据丢失率、数据传输率和输出通道利用率等性能指标的精确求解算法。
Accurate algorithms to compute the performance indexes including data loss possibility, data transmission rate and output channel utilization rate under given finite buffer capacity are given.
给出有限缓冲条件下系统的稳态数据丢失率、数据传输率和输出通道利用率等性能指标的精确求解算法。
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