Online computation and competitive analysis
Online computation and competitive analysis
A guessing game and randomized online algorithms
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On-line analysis of the TCP acknowledgment delay problem
Journal of the ACM (JACM)
Theoretical Computer Science
A faster off-line algorithm for the TCP acknowledgement problem
Information Processing Letters
Dynamic TCP acknowledgement: penalizing long delays
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
A Dynamic Delayed Acknowledgment Mechanism to Improve TCP Performance for Asymmetric Links
ISCC '98 Proceedings of the Third IEEE Symposium on Computers & Communications
Dynamic TCP acknowledgment in the LogP model
Journal of Algorithms
| Hi-index | 5.23 |
The dynamic TCP acknowledgement problem which focuses theacknowledgment mechanism in TCP protocol has been intensivelystudied in the area of competitive analysis. However, its frameworkdoes not consider the sliding window in the TCP protocol thatrestricts the maximum number of packets that the sender can injectinto the network without an acknowledgement. This paper proposes anew problem in which the sliding window is realisticallyintegrated. We study how the ability of on-line algorithms changes,depending on whether the receiver is taught the window size. Thegreater part of this paper assumes that the window size is aconstant integer W. We first show that, if W isgiven, the optimal on-line algorithm for the previous framework canbe extended to our new framework and achieves the optimalcompetitive ratio of 2. Next we prove that, if W is notgiven, the lower bound of the competitive ratio for an algorithmclass which contains the optimal algorithm for the previousframework depends on the peak packet rate T from the senderand W, and is not better than(T/W+[T/W]-1)-competitive. Then, weprove that there exists an on-line algorithm that is([T/W]+2)-competitive, when W is unknown. Anoptimal off-line algorithm is also presented in this paper.Significantly, our problem models the situation in which an on-linealgorithm involuntarily transforms the input and processes themodified input without noticing the transformation.