Abstract

In this paper, we propose the Programmable LInk Metric Identification (ProgLIMI) infrastructure for software-defined networking (SDN) networks. ProgLIMI identifies round-trip link metrics (RTLMs) from accumulated end-to-end metrics of selected measurement paths by leveraging the flexible routing control capability of SDN networks. ProgLIMI mainly solves three sub-problems: 1) monitor placement; 2) linearly independent measurement path construction; and 3) flow rule design. To reduce measurement cost, ProgLIMI tries to minimize the number of required monitors and flow rules. In this paper, we address the three sub-problems for both full and hybrid SDN networks. For full SDN networks, ProgLIMI can achieve full RTLM identification using only one monitor and two flow rules in each SDN switch. In contrast, the RTLM identification in hybrid SDN networks is more complicated due to the routing constraint of hybrid SDN networks. We first prove that the monitor placement problem in hybrid SDN networks is NP-hard. We then formulate the monitor placement and measurement path selection problem in hybrid SDN networks and propose a greedy heuristic algorithm to solve the problem efficiently. Our evaluations on both physical testbed and simulation platform reveal that ProgLIMI can accurately identify the RTLMs (delay and loss rate). Besides, ProgLIMI is also resource efficient, i.e., it only requires two flow rules in each SDN switch and a small number of monitors, and the extra probing traffic load incurred by ProgLIMI is also low.

Highlights

  • A CCURATE and timely monitoring of time-varying link performance metrics are essential for various daily SDN networkManuscript received September 11, 2016; revised April 29, 2017, November 22, 2017, and June 5, 2018; accepted August 2, 2018; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor K

  • Minimizing the number of required monitors brings a negative impact on the accuracy of RTLM identification, especially for the Round-Trip Link Loss Rate (RTLLR) identification

  • The reason is that less monitors will lead to longer measurement paths, and the accumulated measurement error will increase as the lengths of measurement paths increase

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Summary

INTRODUCTION

A CCURATE and timely monitoring of time-varying link performance metrics (e.g., delays, loss rates, and available bandwidth) are essential for various daily SDN network. While the indirect approaches infer link metrics/states by measuring the performance of selected paths between monitors, which are connected to a subset of nodes. Hop-by-hop direct measurement approaches use diagnostic tools such as ping, traceroute, pathchar, and clink to measure the performance metrics of hop-by-hop links on probe packets forwarding paths. WANG et al.: ProgLIMI IN SOFTWARE-DEFINED NETWORKS how to identify additive link metrics from end-to-end path measurements. This paper uses the algebraic approach to identify round-trip link metrics for SDN networks. To uniquely identify all link metrics, we must first deploy m linearly independent measurement paths in a network, where m is the number of links. Link metric identification in SDN networks needs that TCAM entries correctly define and implement forwarding rules for measurement paths. We assume that the link metrics are additive and change slowly relative to the measurement process (i.e., the link metrics can be viewed as constants)

RELATED WORKS AND OUR CONTRIBUTIONS
PROBLEM FORMULATION
RTLM IDENTIFICATION IN FULL SDN NETWORKS
Measurement Path Construction
Flow Rule Design
RTLM IDENTIFICATION IN HYBRID SDN NETWORKS
The Monitor Placement and Measurement Path Selection Algorithm
21: Select z as a monitor and insert z into M
8: Add path p to set LP
PERFORMANCE EVALUATION
Testbed Experiments
DISCUSSION
Full SDN Network
Hybrid SDN Network
Findings
VIII. CONCLUSION
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