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Optimizing Distributed Application Performance Using Logistical Networking

Optimizing Distributed Application Performance Using Logistical Networking. Micah Beck Jack Dongarra James S. Plank Rich Wolski Computer Science Dept. University of Tennessee, Knoxville. Logistical Networking.

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Optimizing Distributed Application Performance Using Logistical Networking

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  1. Optimizing Distributed Application Performance Using Logistical Networking Micah Beck Jack DongarraJames S. PlankRich Wolski Computer Science Dept. University of Tennessee, Knoxville

  2. Logistical Networking • The use of storage resources as part of the network’s communicative infrastructure. • Examples: • mail, news, FTP, HTTP • file and database caches, replication • remote buffer managment • distributed shared state

  3. The “Logistical Computing & Internetworking” (LoCI) Hypothesis • If network resources (distributed storage, communication and computation) can be predictably allocated and flexibly coscheduled, • Then advanced applications can be implemented with higher performance and/or lower overall use of communication, computational, and storage resources.

  4. Management of State in the Network: Motivation • The design of distributed systems for performance and modularity requires management of state • The TCP/IP protocols implement data transmission in a stateless network. • State management functions are currently pushed up to the application layer using application-specific protocols.

  5. The Internet Backplane Protocol • The network is a “commons” used by a community to enable communication. • Data transmission is currently the only resource held in common. • IBP adds storage to the commons. • Substantial storage resources are owned by the network and allocated to endpoints.

  6. IBP Client API: Allocation • IBP_allocate(char *host, int size, IBP_attributes attr) • Open allocation is key to networking • Attributes key to avoiding denial-of-use • time limitation • volatile (server can revoke) • Circular, FIFO

  7. Dimensions in Communication • The Internet allows spatial flexibility through transmission and routing • no temporal flexibility: as quick as possible • Storage allows temporal flexibility through storage for retrieval at later time(s) • no spatial flexibility: the bits stay put • IBP allows flexibility in both dimensions

  8. Dimensions in Communication Networking (spatial) Storage (temporal) Logistical Networking

  9. Example: NetSolve State Management • The Problem: NetSolve calls are functional • Excessive data transfers Client A,B Server 1 F A Client A,B Server 2 F A For example: Client A = F(A, B); A = F(A, B);

  10. Caching Dependence Flow A,B Client Client Server 1 A A,B Server 1 B A F F B B A IBP Cache A,B Server 2 Server 2 A F F A A Client Client

  11. Allocation policy Security Prediction Co-scheduling Network Routing Dynamic control Peering Reliability Disaster recovery Resource discovery Garbage collection Cost recovery Quality of Service Performance Logistical NetworkingResearch Issues

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