使用有界缓冲区平衡工作和大小
Balancing Work and Size with Bounded Buffers
摘要：
我们认为，管理一个有界大小的队列缓冲区的流量由不同大小的数据包，每个数据包需要几轮的处理，然后才可以从队列缓冲区传输的基本问题。这种环境的目标是最大化成功传输的数据包的总大小。这种模型的动机是不断增长的无处不在的网络处理器架构，必须处理异构的流量大小，异构的处理要求。我们的工作解决了两个冲突的算法方法之间的紧张局势，在这样的设置：倾向于处理要求较少的数据包，从而导致快速贡献的累积吞吐量，而不是更喜欢的数据包的大小，这意味着在每一步的吞吐量大幅增加。我们提出了一个模型，研究这样的系统，并提出竞争力的算法，其性能取决于一个数据包的最大大小可能有，和最大量的处理数据包可能需要。我们进一步提供了在这种设置下的算法性能的下限。
英文摘要：
We consider the fundamental problem of managing a bounded size queue buffer where traffic consists of packets of varying size, where each packet requires several rounds of processing before it can be transmitted from the queue buffer. The goal in such an environment is to maximize the overall size of packets that are successfully transmitted. This model is motivated by the ever-growing ubiquity of network processors architectures, which must deal with heterogeneously-sized traffic, with heterogeneous processing requirements. Our work addresses the tension between two conflicting algorithmic approaches in such settings: the tendency to favor packets with fewer processing requirements, thus leading to fast contributions to the accumulated throughput, as opposed to preferring packets of larger size, which imply a large increase in throughput at each step. We present a model for studying such systems, and present competitive algorithms whose performance depend on the maximum size a packet may have, and maximum amount of processing a packet may require. We further provide lower bounds on algorithms performance in such settings.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
