Towards A Maximum-Flow-Based Service Composition (for Multiple & Concurrent Service Composition)

1. 2009-03-28 Lab seminar Towards A Maximum-Flow-Based Service Composition(for Multiple & Concurrent Service Composition) Han, Sang Woo Networked Media Lab. Dept. of Information and Communications Gwangju Institute of Science and Technology

2. Contents • Ph.D. Research Topics • Introduction • Motivation • Related Work • Research Outline • Proposed Service Composition Scheme • System Model & Problem Statement • Problem Solving Methods • Discussion • Summary

3. Ph.D. Research Topics • Workflow-driven Control and Management Framework for Dynamic Service Composition • Hierarchical Abstraction Structure for Programmable Network and Computing Environments •  Workflow-driven Dynamic Service Composition • Capability-based Service Matchmaking and Negotiation

4. Live Content Sharingover Mobile P2P Networks • Mobile multimedia services • Live media streaming • Personalized internet broadcasting • Multi-party video conferencing • Full Web Browsing • Challenges • QoS support between devices having heterogeneous network & device capability Your Content Your Device Your Friends Mobile P2P Networks Media Producers Media Consumers capability gap QoS-aware service composition

5. [HPDC 04] Spidernet: An integrated peer-to-peer service composition framework • BCP (bounded composition probing protocol) • Hop-by-hop probing processing & optimal composition selection • Not supporting multiple composition in same time

6. [MSC-WS@ACM MM 05] Seamless Service Composition (SeSCo) in Pervasive Environments • SeSCo (seamless service composition) • Hierarchical service overlay network configuration • Discovery + matching + coordination

7. Research Outline • Goal • Multiple & concurrent service composition (modeling) • Challenges • Existing schemes does not consider multiple & concurrent service composition • Thus, next composition requests have to be blocked in processing a composition job  composition processing time become longer! • Approach • Casting the composition problem into maximum flow network problem • Multiple sources, multiple sinks • Possible maximum flow out of certain sources or into all sinks • Expected Result • Automated Service Composition Graph (in Polynomial-Time)

8. Media-Service-Oriented Virtualized Computing & Networking Testbed Telecommunication service Storage service Networked Cameras Video producing service Presence service Encoding, transcoding, and decoding services Content servers Replica facilities Web servers

9. Use Case content providers Application #1 interactive & personalized broadcasting Application #2 users Application #3 3) application-on-demand Apps portal 5) quotation 1) request for interactive broadcasting 6) reservation & payment video conferencing 8) commit 2) posting & announcement multimedia mashup 4K cinema 4) query & negotiation Service path 1 7) service path reservation & payment Transcoding service Video scaling service Multicast connector service Text embedding service … network services offered by service providers

10. Preliminary System Model Application Testbed Topology • Input: Multiple applications and testbed topology • Output: The graphs of service composition for the applications

11. Step 1. Service Finding (DHT-based) Service Discovery Service Instantiating (according to # of apps)

12. Step 2. Configuring Network Unit Capacity Maximum Flow Network

13. Step 3. Service Paths Finding

14. Service Path FindingUsing Maximum Flow Algorithm • Input: Graph G with flow capacity c, a source node s, and a sink node t • Output: A flow f from s to t which is a maximum • f(u,v)  0 for all edges (u,v) • While there is a path p from s to t in Gf, such that cf(u,v)>0 for all edges (u,v)∈ p: • f(u,v)  f(u,v) + cf(p) • f(v,u)  f(v,u) – cf(p) Ford-Fulkerson Algorithm

15. Discussion • How to evaluate? • To measure service composition processing time per application in large-scale virtualized computing & networking testbed • Need more criteria… • Network capacities consideration • System model update using weighted maximum flow algorithm • Adaptive composition • Feedback-driven resource/service adaptation • Stabilization in dynamic situation • Load balancing • Complex application design • Workflow-pattern-based specification

16. Summary • Preliminary system model for multiple & concurrent service composition • Service composition approach based on network optimization method • Haven’t I done an evaluation yet.

17. References • J. Jin and K. Nahrstedt, “Source-based QoS Service Routing in Distributed Service Networks,” in Proc. ICC, Paris, France, 2004. • N. J.A. Harvey, R. E. Ladner, L. Lovász, and T. Tamir, “Semi-matchings for Bipartite Graphs and Load Balancing,” Algorithms and Data Structures, 2003. • L. R. Ford, and D. R. Fulkerson, “Solving the Transportation Problem,” Management Science, Vol. 3, pp. 24-32. • S. Kalasapur, M. Kumar, and B. Shirazi, “Seamless service composition (SeSCo) in pervasive environments,” in Proc. ACM int’l workshop on Multimedia Service Composition, New York, NY, 2005. • X. Gu and K. Nahrstedt, “Distributed Multimedia Service Composition with Statistical QoS Assurances,” IEEE Trans. on Multimedia, Vol. 8, No. 1, Feb. 2006.