Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Increasing Application Performance In Virtual Environments Through Run-time Inference and Adaptation Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience Lab Department of Computer Science Northwestern University http://virtuoso.cs.northwestern.edu Summary • Dynamically adapt unmodified applications on unmodified operating systems in virtual environments to available resources • The adaptation mechanisms are application independent and controlled automatically without user or developer help • Demonstrate the feasibility of adaptation at the level of collection of VMs connected by Virtual Networks • Show that its benefits can be significant for two classes of applications 2 Outline • • • • • • • Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIFAdaptive virtual network Evaluation Summary 3 Virtual Machine Grid Computing 1 AimDeliver arbitrary amounts of computational power to perform distributed and parallel computations Traditional Paradigm New Paradigm 2 Resource multiplexing using Grid OS level mechanism Computing 3b 5 Grid Computing using virtual machines 4 3a 6a Problem1: 6b Complexity from resource Solution user’s perspective Problem2: Complexity from resource owner’s perspective Virtual Machines What are they? How to leverage them? 4 Virtual Machines Virtual machine monitors (VMMs) •Raw machine is the abstraction •VM represented by a single image •VMware GSX Server 5 The Simplified Virtuoso Model User’s LAN Virtual networking ties the machine back to user’s home network Orders a raw machine VM Specific hardware and performance Basic software installation available Virtuoso continuously monitors and adapts User 6 User’s View in Virtuoso Model User’s LAN VM User 7 Outline • • • • • • • Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIFAdaptive virtual network Evaluation Summary 8 Virtual Networks VM traffic going out on foreign LAN Foreign hostile LAN User’s friendly LAN X IP network Host Proxy Virtual Machine A machine is suddenly plugged into a foreign network. What happens? • Does it get an IP address? • Is it a routeable address? • Does firewall let its traffic through? To any port? VNET: A bridge with long wires 9 A VNET Link Ethernet Packet Captured by Interface in Promiscuous mode First link Second link (to proxy) VM 1 “eth0” ethy ethz “Host Only” Network VM 2 “eth0” vmnet0 vmnet0 VNET Host Ethernet Packet is Matched against the Forwarding Table on that VNET IP Network VNET Ethernet Packet Tunneled over TCP/SSL Connection Host Ethernet Packet is Matched against the Forwarding Table on that VNET Local traffic matrix inferred by VTTIF Periodically sent to the VNET on the Proxy 10 Virtual Topology and Traffic Inference Framework (VTTIF) Operation Ethernet-level traffic monitoring VNET daemons collectively aggregate a global traffic matrix for all VMs Application topology is recovered using normalization and pruning algorithms 11 Dynamic Topology Inference by VTTIF VNET Daemons on Hosts VNET Daemon at Proxy 1. Fast updates Aggregated Traffic Matrix Smoothed Traffic Matrix Topology change output 2. Low Pass Filter Aggregation 3. Threshold change detection 12 Outline • • • • • • • Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIFAdaptive virtual network Evaluation Summary 13 Applications Adaptation Application performance measure Monitoring and inference Optimization metric Adaptation algorithm Adaptation mechanisms 1. BSP 2. Transactional ecommerce 1. Application throughput 1. VTTIF 2. Network monitoring 1. Single hop 2. Worst fit 1. Single metric 2. Combined metric 1. Overlay topology 2. Forwarding rules 3. VM migration 14 Optimization Problem (1/2) Topology Only Informally stated: • Input – Network traffic load matrix of application • Output – Overlay topology connecting hosts – Forwarding rules on the topology Such that the application throughput is maximized The algorithm is described in detail in the paper15 Illustration of Topology Adaptation in Virtuoso Resilient Star Backbone Fast-path links amongst the VNETs hosting VMs User’s LAN Foreign host LAN 1 VM 1 IP network Proxy + Merged matrix as VNET inferred by VTTIF VM 4 Foreign host LAN 4 Host 1 + VNET Foreign host LAN 2 VM 2 Host 4 + VNET VM 3 Foreign host LAN 3 Host 3 + VNET Host 2 16 + VNET Evaluation • Reaction time of VNET • Patterns: A synthetic BSP benchmark • Benefits of adaptation (performance speedup) – Eight VMs on a single cluster, all-all topology – Eight VMs spread over WAN, all-all topology Wide-Area testbed DOT Network CMU Northwestern VM 6 Proxy VM 5 … VM 1 VM 8 University of Chicago VM 7 17 Reaction Time 3.5 3.23 2.92 3 Seconds 2.5 2.268 2 1.6 1.5 1 0.94 0.5 0 nt e ili s Re tar S th th st h a t a a p a p lf t p t l s t s -A ks as fa f a o f t n h s l li es s ng Al th Bu ks i M k R ks pa lin n i lin 18 Benefits of Adaptation Benefits accrued as a function of the number of fast-path links added 5 4.5 Full all-to-all from beginning of run 4 3 Full all-to-all network after startup measurement + reconfiguration cost 2.5 2 Dynamic measurement and reconfiguration 1.5 1 No Fast Path Topology •Patterns has an all-all topology •Eight VMs are used •All VMs are hosted on the same cluster 0.5 0 ideal complete star 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Iterations/second 3.5 Number of Fast Path Links in Virtual Topology 19 Benefits of Adaptation Benefits accrued as a function of the number of fast-path links added 2.5 Full all-to-all from beginning of run 1.5 Full all-to-all network after startup measurement + reconfiguration cost •Patterns has an all-all topology No Fast Path Topology 1 Dynamic measurement and reconfiguration 0 •Eight VMs are used • VMs are spread over WAN 0.5 ideal complete star 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Iterations/second 2 Number of Fast Path Links in Virtual Topology 20 Optimization Problem (2/2) Topology + Migration Informally stated: • Input – Network traffic load matrix of application – Topology of the network • Output – Mapping of VMs to hosts – Overlay topology connecting hosts – Forwarding rules on the topology Such that the application throughput is maximized The algorithm is described in detail in the paper21 Evaluation • Applications – Patterns: A synthetic BSP benchmark – TPC-W: Transactional web ecommerce benchmark • Benefits of adaptation (performance speedup) – Adapting to compute/communicate ratio – Adapting to external load imbalance 22 Effect on BSP Application Throughput of Adapting to Compute/Communicate Ratio 23 Effect on BSP Application Throughput of Adapting to External Load Imbalance 24 TPCW Throughput (WIPS) With Image Server Facing External Load No Topology Topology No Migration 1.216 1.76 Migration 1.4 2.52 25 Outline • • • • • • • Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIFAdaptive virtual network Evaluation Summary 26 Summary • Dynamically adapt unmodified applications on unmodified operating systems in virtual environments to available resources • The adaptation mechanisms are application independent and controlled automatically without user or developer help • Demonstrate the feasibility of adaptation at the level of collection of VMs connected by Virtual Networks • Show that its benefits can be significant for two classes of applications 27 For More Information • Future Work – Free network measurement (Wren) – Collaboration with CS, W&M – Applicability of a single optimization scheme • Related Talk at HPDC 2005 – J. Lange, A. Sundararaj, P. Dinda, “Automatic Dynamic Run-time Optical Network Reservations” – Wednesday, July 27, 2:00 P.M. • Please visit – Prescience Lab (Northwestern University) • http://plab.cs.northwestern.edu – Virtuoso: Resource Management and Prediction for Distributed Computing using Virtual Machines • http://virtuoso.cs.northwestern.edu • VNET is publicly available from above URL 28