Virtual Network Services As Enabler of Dynamic Application-Aware Traffic Engineering Masato Tsuru Network Design Research Center, Kyushu Institute of Technology, Japan
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
Internet Traffic Monitoring in Japan: Still Growing From Report by Ministry of Internal Affairs and Communications, Japan 3
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
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
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
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,... 2. 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
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
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
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
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
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
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
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
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] 60 50 40 30 20 10 Case 1: All 25 links are homogeneous (100 [Mbps]) 0 0 10 20 30 40 50 60 70 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
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
Middle Layer Model: A proof-of-concept development (2) 17