Load Balancing in SDN Networks using Metaheuristic Methods

Bilgisayar Mühendisliği BölümüLoad Balancing in SDN Networks using Metaheuristic Methods CSE624 Mahmud Rasih ÇELENLİOĞLU December 2013 GYTE - Bilgisayar Mühendisliği Bölümü Outline • • • • • Overview of Software Defined Networking Related Works LB-VNS LB-GA Conclusion GYTE .Bilgisayar Mühendisliği Bölümü 2 . SDN Architecture Control Plane: • Logically centralized • Smart • Slow Data Plane: • Dummy • Fast Protocol for Controller – Switch Communication (e.g. OpenFlow Protocol) GYTE .Bilgisayar Mühendisliği Bölümü 3 . Software-Defined Networking • Traffic Engineering • Network Virtualization • Virtual Private Networks Scalability • Signalling • Computational Complexity • Switch Configuration Reliability • Controller GYTE .Bilgisayar Mühendisliği Bölümü 4 . Bilgisayar Mühendisliği Bölümü 5 .Related Works – MPLS GYTE . Bilgisayar Mühendisliği Bölümü 6 .Virtual Path Approach • Create virtual links • Capacity of VL is proportional to pyhsical link capacity • Local Solution GYTE . Bilgisayar Mühendisliği Bölümü 7 .Objective Function • Max load balancing with min path change • Path Change Ratio (PCR): How many flows are shifted to other paths • Avg Distance Ratio (ADR): Avg distance btw current loads and ideal loads for all paths GYTE . Details • Distribute N flows to M paths • Solution Representation 8 20 12 16 32 14 10 8 8 24 1 2 1 2 3 1 3 1 3 2 2 2 1 2 1 2 3 3 2 2 GYTE .Bilgisayar Mühendisliği Bölümü 8 . Bilgisayar Mühendisliği Bölümü 9 .LB-VNS Neighborhood Structures: – Smart Insert: Randomly chosen flow is assigned to the path whose distance is maximum – Random Insert: Randomly chosen flow is assigned to a randomly chosen path – Smart Swap: Randomly chosen two flows are swapped between two paths with max distances. Distance of one path exceeds the ideal load and the another one does not – Random Swap: Randomly chosen two flows are assigned to two randomly chosen paths – Fully Random Assignment: All flows are randomly assigned to paths without any consideration Local Search: Smart Insert. Smart Swap Shaking: Fully Random Assignment GYTE . Bilgisayar Mühendisliği Bölümü 10 .LB-VNS GYTE . Select F number of individuals 2. Pick best among them – SecondTournament: 1.Bilgisayar Mühendisliği Bölümü 11 . Select S number of individuals & Pick best among them • F = Population Size/3 & S = (Population Size .F)/3path GYTE .GA • Population Size: 20 • Tournament Selection: – First Tournament: 1. Discard individuals attended to first tournament 2. 9 otherwise inherited from one of parents • Recessive Gene: Always inherit assignment of one of parents Mutation: • Shift a flow belongs to overloaded path to underloaded • Perform after crossover GYTE .Bilgisayar Mühendisliği Bölümü 12 .GA Crossover: • Dominant Gene: Flows Size < Th-Min OR Flows Size > Th-Max • Recessive Gene: Th-Min <= Flows Size <= Th-Max • Dominant Gene: Stay in the same path with probability of 0. Bilgisayar Mühendisliği Bölümü 13 .LB-GA GYTE . Bilgisayar Mühendisliği Bölümü 14 .5] • 1000 iteration GYTE .LB-GA Experiment • 10 run for each path number [2. Bilgisayar Mühendisliği Bölümü 15 .LB-GA Experiment GYTE . Bilgisayar Mühendisliği Bölümü 16 .Conclusion • LB-GA works better than LB-VNS • LB-VNS is faster • Performance of LB-VNS can be increased by changing local search method GYTE . Bilgisayar Mühendisliği Bölümü 17 .Questions? Thank You  & Questions? 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