Peter Siska, Marc Ph. Stoecklin, et al.
IWCMC 2010
Data center networks are expected to support emerging types of bandwidth-hungry applications to perform real-time search and data analysis. They impose significant challenges to identify the cause of congestion down to the flow level on a physical port of a switch/router in real time with high accuracy, low computational complexity and good scalability with the exploding data. In this article, we propose two sketch-based algorithms, called α-CU and P(d)-CU, based on the existing Conservative Update (CU) approach. α-CU adds no extra implementation cost to traditional CU, but successfully trades off the achieved error with time complexity. P(d)-CU fully considers the amount of skew for different network services to aggregate traffic statistics of each service type at individual horizontally partitioned sketches. We also introduce a way to produce the real-time moving average of the reported results. The effectiveness of the proposed algorithms is verified by sufficient experiments by a real DCN trace. © 1986-2012 IEEE.
Peter Siska, Marc Ph. Stoecklin, et al.
IWCMC 2010
Xenofontas Dimitropoulos, Marc Stoecklin, et al.
Computer Networks
Saumay Pushp, Chulhong Min, et al.
SenSys 2012
Heiko Ludwig, Kamal Bhattacharya, et al.
CNSM 2010