Design of Optical Aggregation Network with Carrier Edge Functions Virtualization
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1 Design of Optical Aggregation Network with Carrier Edge Functions Virtualization September 28, 2017 Takashi Miyamura 1, Akira Misawa 2, Jun-ichi Kani 1 1 NTT Laboratories 2 Chitose Institute of Science and Technology (CIST) Copyright 2017 NTT corp. All Rights Reserved. P.1
2 Outline 1. Background 2. Objective 3. Proposed Method 4. Performance Evaluation 5. Conclude 2
3 Outline 1.Background 2. Objective 3. Proposed Method 4. Performance Evaluation 5. Conclude 3
4 Carrier network architecture Aggregation network (metro): Transport traffic from access network to backbone network, based on electronic L2 SW. Carrier edge function: provides servicespecific functions such as QoS and flow identification at edge router. Others IX Public cloud (e.g., Amazon) Internet Access net. Layer 2 switches Backbone net. GW router Opt. fiber OLT Aggregation network OXC Legend (symbols): Layer 2 switch Access net. Access network: Connecting user premises with carrier network Edge router Aggregation network: Concentrate user traffic and transport it to the backbone OLT: Optical Line Terminal, OXC: Optical Cross-connect Backbone network: Transport longhaul traffic IP router OXC / OADM
5 Recent trend in aggregation networks 1: Introducing NFV for Carrier Edge functions Edge functions to be relocated from edge routers to distributed pools of commodity servers 2: TDM/WDM-based Optical Aggregation Network WDM ring network to accommodate large-volume traffic efficiently VNF: Virtual Improving Network efficiency Function by sharing same wavelength through TDM 1 NFV for edge Improving OLT efficiency functions of wavelength through TDM Server farms OLT Re-optimize VNF placement according to uneven resource usage OLT OLT TDM/WDM ring 2 TDM/WDM-based network Accommodate unpredictable traffic demand changes by NFV 5
6 1 Carrier edge functions virtualization Advantages: Create VNF for each OLT. The VNF can be flexibly placed on any servers among distributed pools of commodity servers. Can be live-migrated from an over-loaded server to an underutilized one in response to unpredictable traffic changes. Challenges: Determine VNF placement considering traffic demand and geographical location (e.g. distance bet. OLT-Server). Conventional network Edge functions QoS BAS SBC ACL VNF #1 NFV VNF #2 VNF #3 VNF #4 Edge routers(dedicated hardware) Commodity servers VNF (virtual network function): Implementation as software 6
7 2 TDM/WDM-based aggregations network Advantages: To cope with bursty traffic, enable the same wavelength channel to be shared by multiple OLTs through DBA or other TDM technologies. Challenges: How to efficiently select route for P2MP wavelength path considering bandwidth requirement of each OLT? time 1 1 time DBA Access node DBA OLT1 time WDM link 2 Optical copler O/E conversion OLT2 DBA NE WDM link ES (Edge server) [1] K. Hattori et al., IEICE Trans. Electron., Vol. E99-C, No. 2, pp , February
8 Outline 1. Background 2.Objective 3. Proposed Method 4. Performance Evaluation 5. Conclude 8
9 Edge routers Conventional: Deployment of edge routers Edge routers accommodate fixed group of OLTs based on location. This causes congested or under-utilized routers due to unpredictable traffic demand changes Our approach: Issues in carrier edge virtualization NFV for carrier edge fucntions Can accommodate OLTs independent of location, so it can provides robustness However, consumes more network resources if we allocate VNFs on geographically remote server. Conventional Our approach: NFV for edge functions Seoul Busan Jeju VNF More resources are consumed if server is far distant from OLT Seoul Busan Jeju Edge servers (ES) OLT OLT Degrade efficiency if traffic demand of OLTs varies widely Improve efficiency to optimize accommodation according to demand changes
10 Objective VNF Minimize network cost while efficiently utilizing server resources. 1 For optimal VNF placement, we need to consider resource requirements of optical network in addition to server resources In optical aggregation network, we need to consider the sharing of wavelength paths as we can use P2MP paths connecting server and OLTs 2 Establish optimal design method for VNF placement and P2MP path Consume routing 3 WDM links Disperse server load Consume 2 WDM links Server may be over-loaded 1 2 ES ES 1 2 OLT OLT 1 2
11 Outline 1. Background 2. Objective 3.Proposed Method 4. Performance Evaluation 5. Conclude 11
12 Proposed design method We formulate the design problem as mixed integer linear programming (MILP). Objective function: Minimize weighted sum of network cost and max server load Variables: P2MP wavelength paths between server and OLTs VNF placement (Select ES to be accommodated) : Network cost Max server load Weight parameter Total of WDM links used for P2MP paths Max load ES load
13 Network model Logical topology design (VNF~OLT) 1 VNF 2 1 OLT 2 Problems1: Place VNFs on ES 3 3 Select ES to accommodate VNF Physical topology design (ES~OLT) Edge server Problem 2: Compute route bet. ES and OLT. TDM-WDM network Legends : ES : OLT : OADM : VNF : Wavelength path OLT
14 Overview of MILP formulations VNF placement Assign binary variables to candidate ES for VNF placement Route for P2MP wavelength path Configure logical flow bet. VNF~OLT. Find route for P2MP path minimize network cost while Binary variable X k 1 accommodating traffic demand of logical flows. VNF placement VNF k X 2 k X 3 k ES P2MP wavelength path D 1 +D 2 Bandwidth of λ ES X 1 k =1 (accommodate VNF k) =0 (no placement) Traffic demand D 1 Traffic demand D OLT
15 Outline 1. Background 2. Objective 3. Proposed Method 4.Performance Evaluation 5. Conclude 15
16 Objective of performance evaluation 1: Design of parameter α Parameter α governs the weight of network cost on server load 2: Effectiveness Effectiveness regarding reduction in network cost and server load 3: Robustness against unpredictable traffic changes Evaluate impact of increased variations of traffic demand Objective function Network cost Max server load Wight parameter 16
17 Evaluation conditions Topology: 10-node multi-ring Traffic demand: Zipf distribution T(x)=b*x -β Reference method: MinHop, RoundRobin Network topology MinHop Select server with minimum hop OLT n OLT RoundRobin Select server in RoundRobin order OLT i j k 17
18 Network cost/ Max server load Result1: Design of parameter α To configure parameter α around 0~1, we can efficiently disperse server load while avoiding increase in network cost Network cost Max server load Minimize network cost Optimization parameter α Minimize server load 18
19 Network cost Result 2-1: Effectiveness Compare network cost for various traffic demand Proposed method reduced by up to 21% 2 RoundRobin Reduction By 21% Proposed MinHop 10% increase Average traffic demand ( Normalized by λ bandwidth) 19
20 Max server load Result 2-2 Effectiveness Compare max server load for various traffic demand Proposed method reduced by up to 30% RoundRobin MinHop Reduction By 30% 2 Proposed Average traffic demand ( Normalized by λ bandwidth) 20
21 Max server load Network cost Result 3 Robustness Evaluate robustness for various traffic variations β Zipf distribution T(x)=b*x -β Proposed method ensures robustness against traffic variations 2 2 Traffic= MinHop RoundRobin 1.5 RoundRobin 1 1 MinHop 0.5 Proposed 0.5 Proposed Traffic variations (β) Sharp fluctuations Traffic variations (β) 21
22 Outline 1. Background 2. Objective 3. Proposed Method 4. Performance Evaluation 5.Conclude 22
23 Conclusions We studied the optimal design of optical aggregation networks with carrier edge function virtualization. NFV improves efficiency of server resources for carrier edge functions. Consider joint optimization problem that minimizes network cost and maximum server load. Formulate the problem as mixed integer linear programming. We quantitatively evaluated effectiveness of the optimal aggregation network design with VNF placement. It reduced the maximum server load and network cost by up to 30% and 21%, respectively. Can improve resource efficiency and robustness to 23
24 Thank you for your kind attention. 24
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