TY - GEN
T1 - Optimal approximations for traffic distribution in bounded switch memories
AU - Sadeh, Yaniv
AU - Rottenstreich, Ori
AU - Kaplan, Haim
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/23
Y1 - 2020/11/23
N2 - Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacities of the servers determine the partition by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are often also required for other tasks such as classification and routing. Previous work showed how to compute the smallest TCAM necessary to implement a given partition exactly. In this paper we solve the more practical case, where at most n TCAM rules are available, restricting the ability to implement the desired partition. We give simple and efficient algorithms to find n rules that generate a partition closest in L∞ to the desired one. We do the same for a one-sided version of L∞ which equals to the maximum overload on a server and for a relative version of it. We use our algorithms to evaluate how the expected error changes as a function of the number of rules, the number of servers, and the width of the TCAM.
AB - Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacities of the servers determine the partition by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are often also required for other tasks such as classification and routing. Previous work showed how to compute the smallest TCAM necessary to implement a given partition exactly. In this paper we solve the more practical case, where at most n TCAM rules are available, restricting the ability to implement the desired partition. We give simple and efficient algorithms to find n rules that generate a partition closest in L∞ to the desired one. We do the same for a one-sided version of L∞ which equals to the maximum overload on a server and for a relative version of it. We use our algorithms to evaluate how the expected error changes as a function of the number of rules, the number of servers, and the width of the TCAM.
UR - http://www.scopus.com/inward/record.url?scp=85097618554&partnerID=8YFLogxK
U2 - 10.1145/3386367.3431297
DO - 10.1145/3386367.3431297
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AN - SCOPUS:85097618554
T3 - CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies
SP - 309
EP - 322
BT - CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies
PB - Association for Computing Machinery, Inc
T2 - 16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020
Y2 - 1 December 2020 through 4 December 2020
ER -