Pricing in Computer Network: Reshaping the Research Agenda Authors: S. Shenker, D. Clark, D. Estrin and S. Herzog Presenter: Lihua Yuan Feb 15, 2004, ECS.

Slides:



Advertisements
Similar presentations
Information Technology Phones, Faxes, , etc. all have the following property: –Network externalities: The more people using it the more benefit it.
Advertisements

Routing and Congestion Problems in General Networks Presented by Jun Zou CAS 744.
Resource Management §A resource can be a logical, such as a shared file, or physical, such as a CPU (a node of the distributed system). One of the functions.
SCENARIO Suppose the presenter wants the students to access a file Supply Credenti -als Grant Access Is it efficient? How can we make this negotiation.
Internet Economics: the use of Shapley value for ISP settlement Richard T.B. Ma Columbia University Dah-ming Chiu, John C.S. Lui The Chinese University.
Seminar In Game Theory Algorithms, TAU, Agenda  Introduction  Computational Complexity  Incentive Compatible Mechanism  LP Relaxation & Walrasian.
Bandwidth Management Framework for IP based Mobile Ad Hoc Networks Khalid Iqbal ( ) Supervisor: Dr. Rajan Shankaran ITEC810 June 05, 2009.
CS 408 Computer Networks Congestion Control (from Chapter 05)
Mathematical models of the Internet Frank Kelly Hood Fellowship Public Lecture University of Auckland 3 April 2012.
Resource Pooling A system exhibits complete resource pooling if it behaves as if there was a single pooled resource. The Internet has many mechanisms for.
Network Capacity Planning IACT 418 IACT 918 Corporate Network Planning.
Pricing for wireless network: Review, Classification and Comparison of Relevant Models Qi Liu, Miklos Vasarhelyi Rutgers University 19 th AAA Annual Meeting.
Web Caching Schemes1 A Survey of Web Caching Schemes for the Internet Jia Wang.
Traffic Engineering Jennifer Rexford Advanced Computer Networks Tuesdays/Thursdays 1:30pm-2:50pm.
Detecting Network Intrusions via Sampling : A Game Theoretic Approach Presented By: Matt Vidal Murali Kodialam T.V. Lakshman July 22, 2003 Bell Labs, Lucent.
Bandwidth sharing: objectives and algorithms Jim Roberts France Télécom - CNET Laurent Massoulié Microsoft Research.
The Price Of Stability for Network Design with Fair Cost Allocation Elliot Anshelevich, Anirban Dasgupta, Jon Kleinberg, Eva Tardos, Tom Wexler, Tim Roughgarden.
Presented by Henning Schulzrinne Columbia University
UCB Implementing QoS Jean Walrand EECS. UCB Outline What? Bandwidth, Delay Where? End-to-End, Edge-to-Edge, Edge-to-End, Overlay Mechanisms Access Control.
Current Research Topics -Sigcomm Sessions -QoS -Network analysis & security -Multicast -giga/tera bit routers /fast classification -web performance -TCP.
A Congestion Pricing User Study Using a a Wireless LAN Jimmy Shih, Randy Katz, Anthony Joseph.
Vickrey Prices and Shortest Paths What is an Edge Worth? By John Hershberger and Subhash Suri Carlos Esparza and Devin Low 3/5/02.
Distributed-Dynamic Capacity Contracting: A congestion pricing framework for Diff-Serv Murat Yuksel and Shivkumar Kalyanaraman Rensselaer Polytechnic Institute,
On Multi-Path Routing Aditya Akella 03/25/02. What is Multi-Path Routing?  Dynamically route traffic Multiple paths to a destination Path taken dependant.
CS 268: Future Internet Architectures Ion Stoica May 6, 2003.
1 Routing as a Service Karthik Lakshminarayanan (with Ion Stoica and Scott Shenker) Sahara/i3 retreat, January 2004.
Using Prices to Allocate Resources at Access Points Jimmy Shih, Randy Katz, Anthony Joseph One Administrative Domain Access Point A Access Point B Network.
Efficient agent-based selection of DiffServ SLAs over MPLS networks Thanasis G. Papaioannou a,b, Stelios Sartzetakis a, and George D. Stamoulis a,b presented.
10th Workshop on Information Technologies and Systems 1 A Comparative Evaluation of Internet Pricing Schemes: Smart Market and Dynamic Capacity Contracting.
Building a Strong Foundation for a Future Internet Jennifer Rexford ’91 Computer Science Department (and Electrical Engineering and the Center for IT Policy)
A Simulation Approach for Internet QoS Market Analysis Bruno Pereira Miguel Martins.
Sechang Son Computer Sciences Department University of Wisconsin-Madison Network Bandwidth Regulation.
Chapter 3 Supply and Demand: In Introduction. Basic Economic Questions to Answer What: variety and quantity How: technology For whom: distribution.
MATE: MPLS Adaptive Traffic Engineering Anwar Elwalid, et. al. IEEE INFOCOM 2001.
Internet Infrastructure and Pricing. Internet Pipelines Technology of the internet enables ecommerce –Issues of congestion and peak-load pricing –Convergence.
SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY San Francisco DTA Project: Model Integration Options Greg Erhardt DTA Peer Review Panel Meeting July 25 th,
Robust Regression for Minimum-Delay Load-Balancing F. Larroca and J.-L. Rougier 21st International Teletraffic Congress (ITC 21) Paris, France, September.
Minimum-Delay Load-Balancing Through Non-Parametric Regression F. Larroca and J.-L. Rougier IFIP/TC6 Networking 2009 Aachen, Germany, May 2009.
Controlling Internet Quality with Price Market Managed Multi-service Internet Bob Briscoe BTexact Research, Edge Lab, University College London & M3I Technical.
Sharanya Eswaran, Penn State University Matthew Johnson, CUNY Archan Misra, Telcordia Technolgoies Thomas La Porta, Penn State University Utility-driven.
Feb 20, 2001CSCI {4,6}900: Ubiquitous Computing1 Announcements.
Integrated Services Advanced Multimedia University of Palestine University of Palestine Eng. Wisam Zaqoot Eng. Wisam Zaqoot December 2010 December 2010.
DaVinci: Dynamically Adaptive Virtual Networks for a Customized Internet Jennifer Rexford Princeton University With Jiayue He, Rui Zhang-Shen, Ying Li,
A Fair and Dynamic Load Balancing Mechanism F. Larroca and J.L. Rougier International Workshop on Traffic Management and Traffic Engineering for the Future.
By Sylvia Ratnasamy, Andrey Ermolinskiy, Scott Shenker Presented by Fei Jia Revisiting IP Multicast.
Higashino Lab. Maximizing User Gain in Multi-flow Multicast Streaming on Overlay Networks Y.Nakamura, H.Yamaguchi and T.Higashino Graduate School of Information.
1 Min-Cost Live Webcast under Joint Pricing of Data, Congestion and Virtualized Servers Rui Zhu 1, Di Niu1, Baochun Li 2 1 Department of Electrical and.
Network Architecture: Design Philosophies IS250 Spring 2010 John Chuang
Distributed Algorithms Rajmohan Rajaraman Northeastern University, Boston May 2012 Chennai Network Optimization WorkshopDistributed Algorithms1.
FAIR CHARGES FOR INTERNET CONGESTION Damon Wischik Statistical Laboratory, Cambridge Electrical Engineering, Stanford
Michael Schapira Yale and UC Berkeley Joint work with P. Brighten Godfrey, Aviv Zohar and Scott Shenker.
MIDDLEWARE SYSTEMS RESEARCH GROUP Adaptive Content-based Routing In General Overlay Topologies Guoli Li, Vinod Muthusamy Hans-Arno Jacobsen Middleware.
DaVinci: Dynamically Adaptive Virtual Networks for a Customized Internet Jiayue He, Rui Zhang-Shen, Ying Li, Cheng-Yen Lee, Jennifer Rexford, and Mung.
Markets Markets – exchanges between buyers and sellers. Supply – questions faced by sellers in those exchanges are related to how much to sell and at.
6 December On Selfish Routing in Internet-like Environments paper by Lili Qiu, Yang Richard Yang, Yin Zhang, Scott Shenker presentation by Ed Spitznagel.
Interconnect QoS settlements & impairments Bob Briscoe BT Group CTO.
1 Protecting Network Quality of Service against Denial of Service Attacks Douglas S. Reeves S. Felix Wu Chandru Sargor N. C. State University / MCNC October.
Jennifer Rexford Fall 2014 (TTh 3:00-4:20 in CS 105) COS 561: Advanced Computer Networks TCP.
Scalable Laws for Stable Network Congestion Control Fernando Paganini UCLA Electrical Engineering IPAM Workshop, March Collaborators: Steven Low,
Chapter 6 outline r 6.1 Multimedia Networking Applications r 6.2 Streaming stored audio and video m RTSP r 6.3 Real-time, Interactive Multimedia: Internet.
Indian Institute of Technology Bombay 1 Communication Networks Prof. D. Manjunath
UNDERSTAND HOW WE GRAPHICALLY REPRESENT CONSUMERS DEMAND A COMPETITIVE MARKET CONSUMER DEMAND.
Internet Traffic Engineering Motivation: –The Fish problem, congested links. –Two properties of IP routing Destination based Local optimization TE: optimizing.
Optimization-based Cross-Layer Design in Networked Control Systems Jia Bai, Emeka P. Eyisi Yuan Xue and Xenofon D. Koutsoukos.
SUPPLY AND DEMAND CH 4 SEC 2 CH 5 SEC 1 CH 6 SEC 2.
What have we modeled? Is it unstable? e.g. processor sharing when ρ>1 If the system is unstable then it’s useless to take measurements; we need to think.
Performance Study of Congestion Price Based Adaptive Service
Potential Areas of Research Activity – March 2000
IT351: Mobile & Wireless Computing
Principles/Paradigms Of Pervasive Computing
Presentation transcript:

Pricing in Computer Network: Reshaping the Research Agenda Authors: S. Shenker, D. Clark, D. Estrin and S. Herzog Presenter: Lihua Yuan Feb 15, 2004, ECS 289L Network Pricing

The Authors Scott Shenker: Integrated Service Dave Clark: E2E argument vs. the brave new world Deborah Estrin: Routing Arbitor, VINT S. Herzog: ? The Blind Men and the Elephant

Outline Current research – the optimality paradigm Critiques –Is marginal cost relevant? –Accessible? –Is optimality the only goal? New pricing paradigm – Edge Pricing Architecture Issues

Current Research Flat pricing <> Usage-based pricing Assume usage-based pricing is necessary Find “optimal” in a simplified model Price  marginal congestion costs

Critiques 1 – Is marginal congestion cost relevant? 1.Marginal cost is a function of demand and supply, –marginal cost > facility cost + operation cost ? –Stable competitive equilibrium –Total charge = attachment fee + usage fee 2.Marginal cost could be different from different sub populations of users Every subset has its own utility function Competition aimed at a certain subset? eg. Mobile phone service plans?

Critiques 2 – Is Marginal Costs Accessible? Does a simple utility function exist in reality? –E.g. Utility a function of bandwidth or delay, Anybody doing this in real life? Different users  different requirements Per-packet based charge vs. Flow-based utility –Users don’t think at packet level Packet-utility relationship ever changing –Adaptive applications, improved TCP

Critique 3 – Is Optimality the Only Goal? Optimality in simplified model  ignored too many basic structural issues Pricing should be compatible with structure of network applications Encourage multicast Charge receiver or sender? Compatible with network service market –Multilateral vs. Bilateral

Critique 3 – Is Optimality the Only Goal? Local control more important than absolute optimal –Optimality  single pricing scheme across the network –Locality in pricing –No truly optimal scheme anyway

Edge Pricing – Approximating congestion costs 1. Replace the current congestion condition by expected congestion condition  QoS-sensitive time-of-day pricing  Insensitive to instant fluctuation  Not encourage dynamic adaptation, but time- shift  User monitoring and adaptatio (Mobile phone again )  Variability at Edge – Difficult for network to access

Edge Pricing – Approximating congestion costs 2.Replace the cost of the actual path with the cost of the expected path Depends only on Source-Destination pair Dependency on routing brings extra dynamics Easier for user to adapt

Edge Pricing – Local Determination Prices determined locally at access point (network edge) –Not distributed computed alone the entire path –May depend on information collected from the whole network –Bilateral relationship –Billing structure completely local

Edge Pricing – Forms Usage-constraining prices –Two extreme cases Flat rate (up to certain capacity, this assumption often hidden) Per-packet/per-reservation charge

Architectural Issues – Multicast AddressPath stability Path graph Receive rs UnicastIDstablelinefixed Multicastlogical name notreevarying Approach 1: identify every receiver Approach 2: compute cost on-the-fly

Architectural Issues – Charging Receivers How does a receiver indicate its willingness to pay? –RSVP How to bill the receiver? –At the receiver’s access point –Charges are accumulated along the path

Architectural Issues – Open Issues How to charge? –S/D pair (go Dutch?) –multicast price depend on # of audience? Free ride? (A  B  C)

Questions? I got one! –Why network engineers need to worry about sender-pay or receiver-pay scheme? Can’t sender bill the receiver later/beforehand?