CeMon: A Cost-effective Flow Monitoring System in Software Defined Networks

TL;DR

CeMon is a low-cost, high-accuracy network monitoring system for SDN that optimizes polling strategies to significantly reduce communication overhead while maintaining measurement precision.

Contribution

The paper introduces novel polling schemes, MCPS and AFPS, that optimize monitoring costs in SDN, addressing limitations of existing approaches by reducing communication overhead.

Findings

MCPS reduces over 50% of communication cost with negligible accuracy loss.

AFPS decreases monitoring cost by up to 20% with minimal accuracy impact.

Proposed heuristics efficiently handle traffic dynamics in SDN monitoring.

Abstract

Network monitoring and measurement are crucial in network management to facilitate quality of service routing and performance evaluation. Software Defined Networking (SDN) makes network management easier by separating the control plane and data plane. Network monitoring in SDN is relatively light-weight since operators only need to install a monitoring module into the controller. Active monitoring techniques usually introduce extra overhead into the network. The state-of-the-art approaches utilize sampling, aggregation and passive measurement techniques to reduce measurement overhead. However, little work has focused on reducing the communication cost of network monitoring. Moreover, most of the existing approaches select polling switch nodes by sub-optimal local heuristics.Inspired by the visibility and central control of SDN, we propose CeMon, a generic low-cost high-accuracy monitoring system that supports various network management tasks. We first propose a Maximum Coverage Polling Scheme (MCPS) to optimize the polling cost for all active flows. The problem is formulated as a weighted set cover problem which is proved to be NP-hard. Heuristics are presented to obtain the polling scheme efficiently and handle traffic dynamics practically. In order to balance the cost and flexibility, an Adaptive Fine-grained Polling Scheme (AFPS) is proposed as a complementary method to implement flow level measurement tasks. Three sampling algorithms are further proposed to eliminate measurement overhead while maintain high accuracy. Both emulation and simulation results show that MCPS reduces more than 50% of the communication cost with negligible loss of accuracy for different topologies and traffics. We also use real traces to demonstrate that AFPS reduces the cost by up to 20% with only 1.5% loss in accuracy.