Deterministic and Probabilistic P4-Enabled Lightweight In-Band Network Telemetry
arxiv(2024)
摘要
In-band network telemetry (INT), empowered by programmable dataplanes such as
P4, comprises a viable approach to network monitoring and telemetry analysis.
However, P4-INT as well as other existing frameworks for INT yield a
substantial transmission overhead, which grows linearly with the number of hops
and the number of telemetry values. To address this issue, we present a
deterministic and a probabilistic technique for lightweight INT, termed as
DLINT and PLINT,respectively. In particular, DLINT exercises per-flow
aggregation by spreading the telemetry values across the packets of a flow.
DLINT relies on switch coordination through the use of per-flow telemetry
states, maintained within P4 switches. Furthermore, DLINT utilizes Bloom
Filters (BF) in order to compress the state lookup tables within P4 switches.
On the other hand, PLINT employs a probabilistic approach based on reservoir
sampling. PLINT essentially empowers every INT node to insert telemetry values
with equal probability within each packet. Our evaluation results corroborate
that both proposed techniques alleviate the transmission overhead of P4-INT,
while maintaining a high degree of monitoring accuracy. In addition, we perform
a comparative evaluation between DLINT and PLINT. DLINT is more effective in
conveying path traces to the telemetry server, whereas PLINT detects more
promptly path updates exploiting its more efficient INT header space
utilization
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