RIDE & LEARN DTN Phase II

1. RIDE & LEARNDTN Phase II RIDE: Robust Internetworking in Disruptive Environments (PARC) J.J. Garcia-Luna-Aceves Ignacio (Nacho) Solis LEARN: Learning Algorithms for Robust Networking (SRI) Mark-Oliver Stehr Carolyn Talcott

2. t1 z Use Storage, Processing, and Communication Opportunistically t2 t3 Treat routes as functions of space and time Exploit longer-term storage of nodes Opportunistic “store-process-forward”

3. RIDE: Robust Internetworking in Disruptive Environments • Data should travel in a self-contained way. • If there is no connectivity, data can still be used. • Data should be referred to by name, not location. • Nodes can identify the data even if they don’t know the destination • Nodes should take advantage of their knowledge and resources • Previously seen nodes and data • Previous transfers • Previous requests • Link schedules/characteristics • Available storage

4. RIDE Technology • Content-based opportunistic routing • Adapt technologies from proactive, on-demand, and epidemic routing as well gossip and directed diffusion approaches • Name data and assign attributes • Maximize utilization of storage and processing • Transfer named data based on a “virtual potential” (interest/resistance)

5. Phase II Objectives • Design, Simulation and Evaluation • Basic Content Naming and Attributes • Signal distribution and scoping • Content transfer and caching • Content-based opportunistic routing • Implementation of a routing algorithm module for the MITRE DTN plug-in architecture

6. Phase III Objectives • Design, Simulation and Evaluation of routing with topology formation • Nodes have different roles • Manage traffic • Manage storage • Develop more efficient data coverage techniques • Advance “subscription” services and opportunistic transfers • Incorporate new designs into the module for the MITRE DTN plug-in architecture.

7. LEARN & RIDE DTN Phase II & III Learning Algorithms forRobust Networking Robust Internetworkingin Disruptive Environments A collaboration between SRI International and PARC Palo Alto Research Center • Concept of Operations • Objective: reliable communication • in highly disruptive environments • without end-to-end connectivity • Guiding visions: • content-based networking • knowledge-based networking • Approach • Opportunistic routing driven by virtual potentials • Learning-based routing with multi-level learning • Opportunistic virtual topology formation • Learning-based virtual topology formation • Hierarchical and agent-organizational techniques • Strengths & Impact • Paradigm shift towards higher level objectives, e.g. from message exchange to content dissemination driven by application goals • Addressing is application-defined and resolved incrementally (symbolic routing) • Multiparty communication becomes an emerging concept of content-based networking • Technology independence enables seamless interoperation with existing and future protocols • Enables use of network storage, a valuable resource virtually unutilized by current protocols • Wide-spread use facilitated by technology independence further increases available resources Interest in Content Content &Dissemination Goals • Core Technologies • New content-based routing algorithms for storage-rich disruptive environments • Distributed knowledge management and distributed learning as a cross-layer technology • Novel approaches to limit information flow • Content-based algorithms for self-forming and hierarchical virtual topologies

8. Thank You • PARC • J.J. Garcia-Luna-Aceves <jose.garcia-luna-aceves@parc.com> • Ignacio (Nacho) Solis <ignacio.solis@parc.com> • SRI International • Mark-Oliver Stehr <mark-oliver.stehr@sri.com> • Carolyn Talcott <carolyn.talcott>