Server load estimation by Burr distribution mixture analysis of TCP SYN response time

Abstract

Server load estimation is key in balancing traffic between servers when optimizing data center resources. Intrusive methods are sometimes difficult or impossible to implement. Therefore, non-intrusive estimation methods are the best alternative in these cases. The objective of this paper is to present a server load estimation method based on external network traffic measurements obtained in a vantage point close to the server. Statistical distributions of TCP SYN response time, that is, the time from SYN to SYN+ACK segments at the server side, are used to fit Burr Type XII heavy tail distribution mixtures. The fitting algorithm, based on maximum likelihood estimation, is developed in detail in this paper. Experimental data shows that the median of the fitted distribution correlates within the 95% confidence interval of the server load figures and, thus, it can be used as a non-intrusive and accurate method to measure it. This new method can be applied to almost any existing load balancing algorithm, as it does not make any assumption about the server, which is considered a black box.