Virtual Network Services As Enabler of Dynamic Application-Aware Traffic Engineering Masato Tsuru

Transcription

1 Virtual Network Services As Enabler of Dynamic Application-Aware Traffic Engineering Masato Tsuru Network Design Research Center, Kyushu Institute of Technology, Japan

2 Ultimate Goal (or Problems already faced...) Support huge network traffic sustainably From YouTube, software updates, to Cloud, M2M, ITS, Smartgrid,... in cost and energy efficient ways Enable/support diverse, innovative network applications (in diverse environments) Distributed, Collaborative, Cyber-physical, Wireless, Mobile, Ad hoc,... Diverse demands and conditions: e.g., Throughput v.s. latency, Security, Mission criticalness,... Resilient for extra. situations Disaster or cyber-attack damage tolerance and fast recovery (We cannot assume perfect protection) 2

3 Internet Traffic Monitoring in Japan: Still Growing From Report by Ministry of Internal Affairs and Communications, Japan 3

4 Mobile Traffic Growth Forecasts... exponential? (from Report ITU-R M.2243: Assessment of the global mobile broadband deployments and forecasts for International Mobile Telecommunications) 4

5 Network Access Infra. Diversity: Still Growing IF multiple different networks can be used for a single transfer task in an integrated fashion, the efficiency can be increased and/or the cost decreased Bandwidth narrow Satellite Cellular phone WIFI WIFI WIFI WIFI E-Mai l VOIP C HAT Store-carry-forward scheme based network infrastructure UP DATE WIFI WIFI Optical /ADSL AUDIO WEB DOWNL OAD STREAM ING IPTV broad rural urban rural Population density 5

6 Where and How Can We Solve the Problems? Applications/Users (L7) Save an unnecessary use of resource Life can change; But do not discourage economy Networking (L2-6) -- It's OUR field. Allocate physical resources efficiently for sufficient functionality and performance of each application TE (Traffic Engineering) in a widest sense Physical Communication Media (L1) Increase network capacities by deployments or new complex technologies Often costly. Theoretical limits may be approaching 6

7 Networking Solutions Effective and Efficient Resource Sharing (TE) More application-aware and physical media-aware dynamic, flexible, adaptive allocations are needed 3 New technology trends (involving each other) 1. Asynchronism (non-realtime/non-interactive) Typically seen in DTN and CCN (ICN) Freedom of Time and Space for Optimization: Store and scheduling, Multi-network-path, Prefetch and cache, Information Coding, Further In-network processing, Multiple time and space-scale control. E.g., Packet-level Scheduling and processing Flow Scheduling for simultaneous competition Synthetic mechanism for traffic peak shift in large Phase change for extraordinary situations (less resources) 3. User/Social Activity Interaction Assist and Inducement, Mobility, Cyber-physical apps.,,, 7

8 Two Players in a Basic Model InP (Infrastructure Provider) Provide physical resources: Regional and Global, Backbone and Wireless,.. Like a public service; Suffer flat rate Know and control physical resources SP (Service Provider) Contents and/or applications: Google, Yahoo!, Amazon, Apple, Skype, navigation services, game services,... Cause huge and diverse traffic Know and control applications and users Effective M InPs by N SPs collaboration required 8

9 Architecture/Model for Design/Implementation To allow diverse design choices Trade-off on Performance, Efficiency, Resiliency, Fairness,. Strict/Probabilistic optimization, Heuristics, Game-theoretic,...; Centralized/Decentralized New application interfaces and user interaction To solve real world requirements Business Model, Standardization, Regulation, ID/Locator separation, Distributed Security/AAA Can Network Virtualization Help us? Virtual Network (VN) per app/service differentiated VN for extraordinary situation change Incremental Deployment, Extensibility, Programmability,.. Management of End-host locators needed 9

10 Network Virtualization Enabling Application-Aware TE Traditional Internet Diverse Services/Users Shif to Save Demand Flexible Internet Diverse Services/Users アプリ 1 アプリ アプリ アプリ N アプリ 1 アプリ アプリ アプリ N TCP/IP = A single Virtualized Network by integrating M resources Do Optimal Matching Provide N diverse Virtual Networks by combining M resources 通 信 1環 境 通 信 環 境 通 信 環 境 通 信 M環 境 通 信 1環 境 通 信 環 境 通 信 環 境 通 信 M環 境 Diverse Network Infra/Resources Increase Capacity Diverse Network Infra/Resources Assume (almost) realtime, bidirectional data exchange along a single (almost) stable path between fixed end-hosts Be Flexible, Extensible, Robust, and Open 10

11 A Middle Layer Model (Virtual Network Provider) VN for SP (1) InP (1) VN for SP (2) VN for SP (3) InP (2) Service Provider (SP) Has a proprietary VN to provide its services to end users The VN is provided by VNP Virtual Network Provider (a Reliable Middle Layer) Coordinator between SPs and InPs Provide a SP's VN in cooperation with InPs (Abstraction, Integration. Separation,..) Operated by a union of InPs?? Infrastracture Provider (InP) Provide resources (network, storage, computation) to SPs via VNP 11

12 Our Research Plan Application-Aware New Generation TE Huge traffic, Diverse apps, Resiliency, and Fairness By introducing Asynchronism, Multiple scale control, and User Interaction Intra-VN TE and Inter-VN TE; the latter is more challenging Virtual Network Service Architecture enabling new TE A Middle Layer Model -- A proof-of-concept development of Control and (perfsonar-based) Management planes InP: OpenFlow + In-Network servers (storage and proc.) OpenFlow has a potential of very flexible TE We use Trema-based controler (may be easy to use?:-) SP: Use case of realtime and non-realtime applications Experimental Analysis & Evaluation JGN-X and OpenFlow testbed on it Large-scale simulation and emulation testbed (STARBED) 12

13 A Simple Flow Scheduling (Just a Serialization) Normal parallel transfer 100 Bandwidth Allocation Transmission Completion Time[s] average Elapsed Time Serialized transfer 100 Bandwidth Allocation Transmission Completion Time[s] average Wait Elapsed Time 1st Flow's and Averaged Transmission Completion Times are reduced 13

14 A Simple Flow Scheduling (Simulation settings) Preliminary estimation of the effect of a simple scheduling: When sender A wants to send a new file to receiver B, A declares the file size and WAITS IF Some other shorter flow is running/wants to run on the bottle neck link for A's new flow. Simulation Model At time 0, each sender (at Left-side) wants to send TWO files to different randomly chosen receivers (at Right-side) side). So EIGHT flows compete in total. Each file has a random size(50[mbit]~500[mbit]) Each flow traverse a single path which is randomly chosen among the shortest paths from the sender to the receiver.. Each link is 100 [Mbps] unless otherwise noted. Repeat 100 simulations with different seeds. 14

15 A Simple Flow Scheduling (Results of 100 trials) Effective Rate = Transmission completion time / File size X: Effective Rate by the normal parallel transfer Y: Effective Rate by a simple (serialized) scheduling 70 グループSCHによる 実 効 転 送 レート[Mbps] Case 1: All 25 links are homogeneous (100 [Mbps]) Case 2: 通 3 常 links 転 送 in による 25 are 実 効 narrow 転 送 レート[Mbps] (60 [Mbps]) 15

16 Middle Layer Model: A proof-of-concept development Resource View Mapping (DBs) SP-VNP, VNP-InP Interface (API) -- Topology, Link capacity Endhost mapping Use case app -- multicast delivery サービスレイヤ ミドルレイヤ インフラレイヤ トポロジ 情 報 DB S1 S1 VX C3 C3 SS VY C3 Y3 C2 C2 VZ C1 C1 トポロジ 情 報 DB トポロジ 情 報 DB 資 源 情 報 DB 資 源 情 報 DB トポロジ 情 報 DB 資 源 対 応 表 DB 資 源 情 報 DB Application server S1 X1 InP X Y1 X2 X3 InP Y Y2 C2 Z1 InP Z Application client C1 トポロジ 情 報 DB 資 源 情 報 DB 16

17 Middle Layer Model: A proof-of-concept development (2) 17