MULTI-LAYER CAPACITY PLANNING, COST MODELING AND OPTIMIZATION Time Warner Cable, Inc. X. Leon Zhao, Ph.D., David T. Kao, Ph.D.
MULTI-LAYER CAPACITY PLANNING, COST MODELING AND OPTIMIZATION
Oct 27, 2015
It is desirable to take a holistic approach so that network capacity can be planned and optimized across the multiple boundaries in architecture, technology, data sources and service offerings. This paper introduces the current state of the art in the unification of network modeling, capacity planning, cost modeling and optimization across one of the big divides in network architecture, IP layer vs. optical layer.
In a typical service provider environment, there is often a clear demarcation between IP layer, i.e., layer 3, and optical layer, i.e., layer 1, in terms of organizations and functions for network engineering and capacity planning. Different groups with various methodologies and tools plan and optimize each layer individually. There is opportunity in collaboration between the two efforts, but it is often limited. In the end, while each layer can indeed and often be optimized (subject to skill and tool limitations), the combination of two layers as a whole is far from optimal.
This paper illustrates an approach to expand auto discovery and modeling of a network modeling tool from IP layer to the optical layer. The result is a multi-layer network model. Given a set of traffic demands, an optical topology, and a cost function, the modeling tool generates hundreds of thousands candidate IP topologies, performs exhaustive failure simulation, and scores each candidate with the cost function. The end result is a least cost, among the numerous candidates, multi-layer design supporting the traffic demand and failure criteria.
In a typical service provider environment, there is often a clear demarcation between IP layer, i.e., layer 3, and optical layer, i.e., layer 1, in terms of organizations and functions for network engineering and capacity planning. Different groups with various methodologies and tools plan and optimize each layer individually. There is opportunity in collaboration between the two efforts, but it is often limited. In the end, while each layer can indeed and often be optimized (subject to skill and tool limitations), the combination of two layers as a whole is far from optimal.
This paper illustrates an approach to expand auto discovery and modeling of a network modeling tool from IP layer to the optical layer. The result is a multi-layer network model. Given a set of traffic demands, an optical topology, and a cost function, the modeling tool generates hundreds of thousands candidate IP topologies, performs exhaustive failure simulation, and scores each candidate with the cost function. The end result is a least cost, among the numerous candidates, multi-layer design supporting the traffic demand and failure criteria.
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Transcript
MULTI-LAYER CAPACITY
PLANNING, COST MODELING
AND OPTIMIZATION
Time Warner Cable, Inc.
X. Leon Zhao, Ph.D., David T. Kao, Ph.D.
Introduction
Multi-Layer Capacity Planning
– Modeling and capacity planning for both Layer 3 and
Layer 1 together
Cost Modeling
– Bridge capacity planning with the cost ($$$)
Backbone Optimization
– Search for the opportunity to increase CAPEX efficiency
based on the multi-layer modeling and cost modeling
IP Backbone Demarcation
3
IP Router
Optical Equipment
IP Link
Optical fiber / Wavelength
Multi-Layer Modeling
IP layer
Optical layer
IP Router IP Link
Optical Equipment
Fiber / Wavelength
Logical mapping between two layers
Multi-Layer Capacity Planning
Directly translate layer 3 capacity requirements
to layer 1
Automatically generate Shared Risk Link Group
(SRLG)
Opportunities to optimize network from a holistic
view
Cost Modeling
Network is a complex system
Cost modeling can only be approximated
Abstraction helps
– Blended cost
– Abstracted network and elements
A Cost Model
7
Router A Router Z
OADM O1 OADM O2 OADM O3
$X per IP port
1x wavelength cost = $Y blended fixed cost plus $Z per N miles
𝐶𝑜𝑠𝑡 = 2𝑋 + 𝑌 + 𝑍*distance
An IP Link between A and Z
Validation of Cost Model
Compare the model with actual financial data
C/b: network cost per Gbps customer traffic
𝐶/𝑏 =𝑇𝑜𝑡𝑎𝑙 𝑛𝑒𝑡𝑤𝑜𝑟𝑘 𝑐𝑜𝑠𝑡
𝑇𝑜𝑡𝑎𝑙 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑡𝑟𝑎𝑓𝑓𝑖𝑐
Calculated C/b from model is compared to C/b
from finance department
Result is very close
Network Design Practice
Separated activity between layer 3 engineering
and layer 1 engineering
Without effective coordination, the final design
may not be optimal
Multi-Layer modeling and proper tools provide
new opportunities for optimization
Case 1: Double Dipping
B A
C IP Link
Optical fiber
Normal State
B A
C
Failure State
X
Layer 3 path
Actual traffic path
Case 2: Hidden Cost
D
B A
C Traffic Matrix
AB 10G
BC 10G
AC 10G
D
B A
C
preferred routes
Design I: Without Optical Bypass Design II: With Optical Bypass
Link Required Capacity
A-B 20G
B-C 20G
A-D 20G
D-C 20G
Link Required Capacity
A-B 20G
B-C 20G
A-C 10G
A-D 20G
D-C 20G
Multi-Layer Network Optimization
10%+ CAPEX Savings
Original network Optimized network
X. Leon Zhao, Ph.D., David T. Kao, Ph.D.
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