A Filtered-based Flow Control Scheme
在實驗中，我們將新提出來的濾波式流量控制機制，與傳統的速率式流量控制機制(rate-based)與信用式流量控制機制(credit-based)作比較。在四個節點的網路架構假設下，可以發現濾波式流量控制機制無論在輸出量(throughput)和封包遺掉率(packet loss rate)，都跟傳統的流量控制機制有幾乎相當的效能，但是在輸出量的變異性上，卻是明顯的較其他兩者為優，所以濾波式流量控制機制對於流量變化較大的網路表現較為強健。但當網路的節點超過四個以上，在各種效能表現上，就可以看出濾波式流量控制機制，比傳統的機制流量控制要好。|
In this thesis, we propose a new flow control scheme based on filter theory, where the conventional (+,×) algebra is replaced by the (min,+) algebra. An essential part of the filter flow control is to determine the filter formula for the measured arrival and departure so that we can use “convolution” of all the intermediate node filters to estimate the end-to-end congenstionness. We first show that it is unlikely to determine the exact filter expression for given input arrival and output departure in terms of spectrum analysis or transformation technique. We then prove in terms of time-domain analysis that there are situations where the filter formula (for given arrival and departure processes) does not exist. We therefore turn to an absolute-error approximation of the filter expression for which the output due to the measured input and the estimated filter yield minimum absolute-error with the true departure. For ease of convolution calculation, we only take first-order filter approximate h(t) whose formula can be expressed as c•t+d, where t is the time scale. Since h(t), by filter theory, behaves as an upper bound to the departure process, we then employ the sample of x(t)-h(t) at the end of each measured window as a degree of crowdedness over the network, where x(t) is the non-decreasing input arrival process. In order to enhance the performance (throughput), we also propose to include both the feedback and feedforward regulation rules in our flow control scheme. The feedback regulation aims at letting the previous node to regulate the departure rate once crowdedness is sensed. The feedforward regulation focuses on letting the node to re-decide the outgoing rate once crowdedness of its subsequent nodes are sensed. Furthermore, as aforementioned, we also convolve the filter (i.e., c and d) of the subsequent nodes to estimate the degree of congestionness, which we named history information. As expected, each node will periodically pass its estimate of c and d to its previous node. Experiment results over a four-node network will be performed on conventional rate-based and credit-based, as well as our newly proposed filter-based flow control schemes. Simulations show that the filter-based flow control can reach almost the same throughput and packet loss rate as the conventional rate-based and credit-based flow control schemes; however, it results in a much smaller variance of throughput than the other two. As a result, the filter-based flow control is more robust to variability of traffic patterns. When a system involved with more than four network nodes is considered, the superiority of filter-based flow control in its robustness becomes more certain.
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