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The SIGACT Community and the NetSE Program: A Match Made in Heaven!

The SIGACT Community and the NetSE Program: A Match Made in Heaven!. Joan Feigenbaum http://www.cs.yale.edu/homes/jf/ Arlington VA ; September 2008. CISE’s “Cross-Cutting” Solicitation Says:.

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The SIGACT Community and the NetSE Program: A Match Made in Heaven!

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  1. The SIGACT Community and the NetSE Program:A Match Made in Heaven! Joan Feigenbaum http://www.cs.yale.edu/homes/jf/ Arlington VA ; September 2008

  2. CISE’s “Cross-Cutting” Solicitation Says: • “The NetSE program seeks proposals focused on developing new theoretical foundations, principles and methodologies to understand and reason about the dynamics and behavior of current and future large-scale networks, the interdependence among the physical, informational and social networks they embody, and the tradeoffs among communication, computation and storage.”  • “The emphasis is on creating theoretically grounded architectures that address fundamental policy and design engineering trade-offs, support healthy economic models and promote social benefits.” MUSIC TO MY EARS!

  3. Theory of Networked Computation (ToNC) • NSF Small Grant for Exploratory Research supported two ToNC workshops in 2006. • 1st ToNC Workshop: Nassau Inn in Princeton NJ, February 2006, chaired by Rexford and Feigenbaum • 2nd ToNC Workshop: ICSI in Berkeley CA, March 2006, chaired by Shenker and Feigenbaum • Participants articulated a broad, eclectic research agenda that anticipated NetSE goals. • Slides, workshop report, and other information at http://www.cs.yale.edu/homes/jf/ToNC.html

  4. ToNC (2) • ToNC agenda has three major components. • Realizing better networks • Computing on networks • Algorithmic and combinatorial problems created or exacerbated by networks • ToNC report advocates collaboration by • Sigact people and Sigcomm people • Theorists and experimentalists • Sample ToNC research challenges follow – not an exhaustive list!

  5. Complexity Theory ofNetworked Computation • Machine model(s) that capture(s), e.g., massive scale, user self-interest, device heterogeneity, and emergent behavior • Resources • Reductions • Hardness results (for better and for worse) • Questions: • “Cook’s Theorem of Networked Computation”? • Computational model ≈ Network architecture?

  6. Economic and Strategic Considerations • “Ownership, operation, and use by many self-interested, independent parties give the Internet characteristics of an economy as well as those of a computer.” • Progress on “algorithmic mechanisms,” including ones for digital-good auctions, combinatorial auctions, load balancing, cost sharing, and routing • Questions: • Are “equilibrium” concepts from Econ appropriate? • Are non-monetary exchanges useful? (Think BitTorrent) • Is “irrational” behavior recognizable and manageable?

  7. Interdomain Routing • IDR: Paradigmatic problem in networked computation • Exemplifies crucial requirements (subnetwork autonomy, subnetwork heterogeneity, massive scale, attack resistance, etc.) • Widely deployed • Hard but unavoidable (and interesting!) • Current state of affairs is unsatisfactory. • Wilfong at ToNC Workshop 1: “BGP Horror Story” • Progress over last 10 years (SPP, robustness, economic analysis, etc.) • Still many difficulties • Small changes in policies lead to big changes in behavior. • Hard to realize some natural goals and requirements

  8. Interdomain Routing (2) • General challenge: Develop a Grand Unified Theory of Interdomain Routing. • Some specific goals: • Identify operating regimes in which current approaches work well (ref. Gao-Rexford). • Separate “essential IDR” from BGP. • Clarify relationship to other networked-computational goals. • Transitions and paths to adoption

  9. Massive-Dataset Computation • Progress over the last 10 years • Useful computational models (e.g., streaming, spot checking, property testing) • Many algorithmic results (especially randomized, approximate, and near-linear) • Massive datasets abound in networked computation • Grand Challenge: Next-generation search • Adversarial behavior (“google bombing”) • Complex data formats • Personalization: Utility vs. privacy

  10. Peer-Produced Information Services • Peer production (Benkler 2001) • High modularity • High granularity • Low cost of integration • Examples abound in the Internet age. - Blogs, wikis, bulletin boards, etc. • Uncoordinated, “egoistic” development • Commercial successes such as Google, eBay, FaceBook, etc. “leverage peer production.” • General challenge: Rigorously define and investigate peer production. • Accuracy/quality of peer-produced information • Computational vs. economic cost of discovery • Computational vs. economic cost of privacy

  11. Security of Network Computation • Assess security at the network level, not the agent level. • Consider quantitative measures of security, not just worst case guarantees. • Consider incentives for deployment and adoption. • Questions: • After 30+ wildly successful years of security and cryptology research, why is our computing environment so insecure? • Potential users should be able to get meaningful answers when they ask, “How much will it cost me to use this security technology? What will I gain if I use it? What will I lose if I don’t?”

  12. Privacy in Networked Computation • Robust technological and social trends have led to a dramatic increase in the amount of sensitive information about people and organizations that is created, captured, stored, and traded. • Past: “Privacy”  “Confidentiality of info.” • Future: “Privacy”  “Appropriate use of info.”? • Questions: • New crypto-theory formulations, e.g., “Privacy in public dbs” (Dwork et al.) “Group privacy” (Shmatikov et al.) • Is any meaningful notion of “privacy” compatible with ubiquitous powerful computers and networks?

  13. Progress Already! • Increasing numbers of papers on NetSE themes at STOC, FOCS, SODA, ICALP, STACS, PODC, DISC, EC, etc. • SIGACT researchers have participated in the SING and FIND programs. Questions?

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