TY - JOUR
T1 - Robust Distributed Monitoring of Traffic Flows
AU - Demianiuk, Vitalii
AU - Gorinsky, Sergey
AU - Nikolenko, Sergey I.
AU - Kogan, Kirill
N1 - Publisher Copyright:
© 1993-2012 IEEE.
PY - 2021/2
Y1 - 2021/2
N2 - Unrelenting traffic growth, device heterogeneity, and load unevenness create scalability challenges for traffic monitoring. In this paper, we propose Robust Distributed Computation (RoDiC), a new approach that addresses these challenges by shifting a portion of the monitoring-task execution from an overloaded network element to another element that has spare resources. Moving the entire execution of the task away from the overloaded element might be infeasible because execution on multiple elements is inherent in the task or requires at least partial participation by the designated overloaded element. Furthermore, distributed execution of a stateful task has to be resilient to network noise in the form of packet reordering and loss. The RoDiC approach relies on two main principles of packet grouping and state overlap to support exact robust distributed monitoring of traffic flows under network noise. RoDiC uses an open-loop paradigm that does not add any control packets, communicates flow state in-band by appending few control bits to packets of monitored flows, and keeps measurement latency low. We apply RoDiC to the problem of flow-size computation and discuss how to instantiate our general technique for real-time packet-loss telemetry. The paper develops robust algorithms, proves their correctness and performance properties, and reports an evaluation driven by realistic traffic traces. The RoDiC algorithms successfully distribute the monitoring-task load while keeping the memory and computation overhead low.
AB - Unrelenting traffic growth, device heterogeneity, and load unevenness create scalability challenges for traffic monitoring. In this paper, we propose Robust Distributed Computation (RoDiC), a new approach that addresses these challenges by shifting a portion of the monitoring-task execution from an overloaded network element to another element that has spare resources. Moving the entire execution of the task away from the overloaded element might be infeasible because execution on multiple elements is inherent in the task or requires at least partial participation by the designated overloaded element. Furthermore, distributed execution of a stateful task has to be resilient to network noise in the form of packet reordering and loss. The RoDiC approach relies on two main principles of packet grouping and state overlap to support exact robust distributed monitoring of traffic flows under network noise. RoDiC uses an open-loop paradigm that does not add any control packets, communicates flow state in-band by appending few control bits to packets of monitored flows, and keeps measurement latency low. We apply RoDiC to the problem of flow-size computation and discuss how to instantiate our general technique for real-time packet-loss telemetry. The paper develops robust algorithms, proves their correctness and performance properties, and reports an evaluation driven by realistic traffic traces. The RoDiC algorithms successfully distribute the monitoring-task load while keeping the memory and computation overhead low.
KW - Traffic monitoring
KW - distributed algorithm
KW - flow-size computation
KW - network noise
KW - real-time telemetry
KW - robust design
KW - stateful task
UR - http://www.scopus.com/inward/record.url?scp=85098750320&partnerID=8YFLogxK
U2 - 10.1109/TNET.2020.3034890
DO - 10.1109/TNET.2020.3034890
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AN - SCOPUS:85098750320
SN - 1063-6692
VL - 29
SP - 275
EP - 288
JO - IEEE/ACM Transactions on Networking
JF - IEEE/ACM Transactions on Networking
IS - 1
M1 - 9260251
ER -