TY - JOUR
T1 - Accurate Traffic Splitting on SDN Switches
AU - Rottenstreich, Ori
AU - Kanizo, Yossi
AU - Kaplan, Haim
AU - Rexford, Jennifer
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - Traffic splitting is essential for load balancing over multiple servers, middleboxes, and paths. Often the target traffic distribution is not uniform (e.g., due to heterogeneous servers or path capacities). A natural approach is to implement traffic split in existing rule matching tables in commodity switches. In this paper, we conduct an analytical study to understand this ability of switches. To do that, we indicate on a surprising strong connection between the description of distributions in switches to signed representations of positive integers. We introduce an optimal algorithm that minimizes the number of rules needed to represent a weighted traffic distribution. Since switches often have limited rule-table space, the target distribution cannot always be exactly achieved. Accordingly, we also develop a solution that, given a restricted number of rules, finds a distribution that can be implemented within the limited space. To select among different solutions, we describe metrics for quantifying the accuracy of an approximation. We demonstrate the efficiency of the solutions through extensive experiments.
AB - Traffic splitting is essential for load balancing over multiple servers, middleboxes, and paths. Often the target traffic distribution is not uniform (e.g., due to heterogeneous servers or path capacities). A natural approach is to implement traffic split in existing rule matching tables in commodity switches. In this paper, we conduct an analytical study to understand this ability of switches. To do that, we indicate on a surprising strong connection between the description of distributions in switches to signed representations of positive integers. We introduce an optimal algorithm that minimizes the number of rules needed to represent a weighted traffic distribution. Since switches often have limited rule-table space, the target distribution cannot always be exactly achieved. Accordingly, we also develop a solution that, given a restricted number of rules, finds a distribution that can be implemented within the limited space. To select among different solutions, we describe metrics for quantifying the accuracy of an approximation. We demonstrate the efficiency of the solutions through extensive experiments.
KW - Load balancing
KW - software defined networking
KW - ternary content addressable memory
UR - http://www.scopus.com/inward/record.url?scp=85054255925&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2018.2869949
DO - 10.1109/JSAC.2018.2869949
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AN - SCOPUS:85054255925
SN - 0733-8716
VL - 36
SP - 2190
EP - 2201
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 10
M1 - 8469157
ER -