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Telco Clouds:Modelling and Simulation
Jakub Krzywda1, William Tärneberg2,P-O Östberg1, Maria Kihl2, Erik Elmroth1
1 – Umeå University2 – Lund University
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Multi-Model
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Telecommunication Cloud computing
… that combines:
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Mobility Infrastructure Setup
… to simulate the influence of:
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Performance Costs
… on:
Computation Offloading
Mobile Devices• high requirements on Quality of Service• limited battery lifetime• less powerful resources
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Computation Offloading
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Other motivations
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Telecommunication Infrastructure
Cloud Computing Infrastructure
Current Situation
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Latency
Issues
Network Congestion
Hardware costs
IntroducingTelco Cloud
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Current SituationMerging Telecommunication and Cloud Infrastructures
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Introducing ProximalData Centers
Telco Cloud
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Reduce Latency
Benefits
Prevent Network Congestion
Decrease costs
• Applications• Mobility
• Quality of Service• Costs
• Topology• DC Capacity• Service placement
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Telco Cloud Dynamics
Workload
ObjectivesSetup
Multi-Model
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Multi-Model Parameters
• Objectives– Performance Overhead
(e.g., migration cost)
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Multi-Model Parameters
• Objectives• Workload
– User’s State
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Request
Response State1010
Stateful Applications
User’s State Size
Total Size ofUser’s Requests
• Objectives• Workload
– User’s State– Mobility
Multi-Model Parameters
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User’s State has to follow User’s movements User
changes PDC
Sta
te
• Objectives• Workload
– User’s State– Mobility
• Setup– Data Center Catchment
Multi-Model Parameters
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:
Ratio between
RBS and DC
• Objectives• Workload
– User’s State– Mobility
• Setup– Data Center Catchment– Virtual Machine Life-Cycle
Multi-Model Parameters
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Virtual Machine Life-Cycle
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Simulation Showcase
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Simulation Showcase Setup
• 16 Radio Base Stations (4x4 layout)• Catchment of Data Centers varies
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Results
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Static Mobile
Small Catchment Few Devices Inactivity
Bigger Catchment Longer Stay More to Migrate
Summary
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Telco Cloud Dynamics
Workload
ObjectivesSetup
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Multi-Model
Who can benefit?
• Telecommunication Operators and Equipment Developers– Model existing infrastructure and plan changes
• Researchers– Testing algorithms for resource management
• Mobile Applications Developers– Testing behavior of apps in Telco Cloud
environment
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Limitations
• Homogeneous requests (at application level)– All requests contribute to User’s State
• Simplified mobile access network model– Tangent, non-overlapping, square cells– No physical layer, channel provisioning and cell
load balancing
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Simulation Showcase Setup
• 16 Radio Base Stations (4x4 layout)• Catchment of Data Centers varies• Constant capacity of Data Centers• #VMs scales with the catchment• workload is balanced between VMs• 480 Mobile Devices
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Simulation requirements
• Scale (number of)– Mobile Devices – hundreds/thousands– Radio Base Stations – tens– Data Centers – several
• Length and granularity of simulation (time) – Minutes/hours for mobility patterns– Milliseconds for latency
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Why simulation?
• No existing Telco Cloud infrastructure
• Extremely high costs of building infrastructure for testing purposes
• Huge number of possible setups
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When to Offload?
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Kumar, K.; Yung-Hsiang Lu, "Cloud Computing for Mobile Users: Can Offloading Computation Save Energy?," Computer , vol.43, no.4, pp.51,56, April 2010
Multi-Model
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Multi-Model Parameters
• Workload– Request Generation
1010
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Multi-Model Parameters
1010
• Workload– Request Generation– Resource
Requirements
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• Workload– Request Generation– Resource Requirements– Mobility
Multi-Model Parameters
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Multi-Model Parameters
• Workload• Setup
– Mobile Network
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Multi-Model Parameters
• Workload• Setup
– Mobile Network– Internet
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• Workload• Setup
– Mobile Network– Internet– Data Center
Multi-Model Parameters
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• Workload• Setup
– Mobile Network– Internet– Data Center– Service Placement
Multi-Model Parameters
?
?
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Multi-Model Parameters
• Workload• Setup• Objectives
– Quality of Service
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Multi-Model Parameters
• Workload• Setup• Objectives
– Quality of Service– Costs
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