在數據中心中，負載平衡是一個很重要的技術，用來處理動態與不
可預測的交通需求量。一般而言，負載平衡的目標是分配相等的交通
量到多重路徑上。然而，大多數的方法都受制於封包亂序或者快速回
應。近年來，Flare 引進基於flowlet 的分流方法，它達到快速回應且不
造成封包亂序。但是，資料中心內的高頻寬環境造成產生flowlet 的間
隔減少。除此之外，分流的細膩度會隨著交通量變大而變粗，在此篇
論文中，我們提出一個人工flowlet 為基底的負載平衡演算法，其能保
持好的分流細膩度且避免封包亂序，在實驗中顯示，我們的方法在流
的完成時間好20%。

Load balancing is an important technique to cope with dynamic and unpredictable
traffic demands in data center networks. In general, load balancing
schemes aim to split traffics evenly among multiple paths. However, most
existing approaches either suffers from packet reordering (which may confuse
TCP congestion control) or fail to quick response (i.e., coarse slicing
granularity). Recently, FLARE introduced a burst (called flowlet) based traffic
splitting, which attains responsiveness without causing packet reordering.
However, the very high bandwidth of internal datacenter flows suggests that
the gaps needed for flowlets may be rare. Besides, in Flare, splitting granularity
increases (i.e., coarse granularity) when flow size increases. In this
paper, we propose an artificial flowlet-based load balancing algorithm which
can maintain fine-granularity (even in large flows) and can also avoid packet
reordering. Our scheme has at least 20% improvement in flow completion
time under the same incidence of packet reordering.

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