An optimization-based approach for efficient network monitoring using in-band network telemetry

Journal of Internet Services and Applications

  ^{1    1    1    2} 

[1] 0000 0001 2200 7498, grid.8532.c, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;0000 0004 0387 9962, grid.412376.5, Federal University of Pampa, Alegrete, Brazil;

关键词: Network Monitoring;    Software-Defined Networking;    Programmable Networks;    P4;    In-Band Network Telemetry;   

DOI  :  10.1186/s13174-019-0112-0

来源: publisher

【 摘 要 】

In recent years, as a result of the proliferation of non-elastic services and the adoption of novel paradigms, monitoring networks with high level of detail is becoming crucial to correctly identify and characterize situations related to faults, performance, and security. In-band Network Telemetry (INT) emerges in this context as a promising approach to meet this demand, enabling production packets to directly report their experience inside a network. This type of telemetry enables unprecedented monitoring accuracy and precision, but leads to performance degradation if applied indiscriminately using all network traffic. One alternative to avoid this situation is to orchestrate telemetry tasks and use only a portion of traffic to monitor the network via INT. The general problem, in this context, consists in assigning subsets of traffic to carry out INT and provide full monitoring coverage while minimizing the overhead. In this paper, we introduce and formalize two variations of the In-band Network Telemetry Orchestration (INTO) problem, prove that both are NP-Complete, and propose polynomial computing time heuristics to solve them. In our evaluation using real WAN topologies, we observe that the heuristics produce solutions close to optimal to any network in under one second, networks can be covered assigning a linear number of flows in relation to the number of interfaces in them, and that it is possible to minimize telemetry load to one interface per flow in most networks.

【 授权许可】

CC BY