Plaxton Routing. - From a peer - to - peer network point of view. Lars P. Wederhake



Similar documents
Plaxton routing. Systems. (Pastry, Tapestry and Kademlia) Pastry: Routing Basics. Pastry: Topology. Pastry: Routing Basics /3

Distributed Computing over Communication Networks: Topology. (with an excursion to P2P)

International Journal of Scientific & Engineering Research, Volume 4, Issue 11, November ISSN

Storage Systems Autumn Chapter 6: Distributed Hash Tables and their Applications André Brinkmann

P2P Storage Systems. Prof. Chun-Hsin Wu Dept. Computer Science & Info. Eng. National University of Kaohsiung

- Easy to insert & delete in O(1) time - Don t need to estimate total memory needed. - Hard to search in less than O(n) time

PEER-TO-PEER (P2P) systems have emerged as an appealing

RELOAD Usages for P2P Data Storage and Discovery

Security in Structured P2P Systems

A Survey of Peer-to-Peer File Sharing Technologies

The Goldberg Rao Algorithm for the Maximum Flow Problem

Load Balancing in Structured Overlay Networks. Tallat M. Shafaat

DPTree: A Balanced Tree Based Indexing Framework for Peer-to-Peer Systems

International journal of Engineering Research-Online A Peer Reviewed International Journal Articles available online

Full and Complete Binary Trees

A Survey and Comparison of Peer-to-Peer Overlay Network Schemes

5. Peer-to-peer (P2P) networks

How To Create A P2P Network

Content Delivery Networks. Shaxun Chen April 21, 2009

A binary search tree is a binary tree with a special property called the BST-property, which is given as follows:

Analysis of Algorithms I: Binary Search Trees

Acknowledgements. Peer to Peer File Storage Systems. Target Uses. P2P File Systems CS 699. Serving data with inexpensive hosts:

New Algorithms for Load Balancing in Peer-to-Peer Systems

Peer-to-Peer Networks. Chapter 6: P2P Content Distribution

Join and Leave in Peer-to-Peer Systems: The DASIS Approach

Mobile Security Wireless Mesh Network Security. Sascha Alexander Jopen

Approximation Algorithms

query enabled P2P networks Park, Byunggyu

Using Peer to Peer Dynamic Querying in Grid Information Services

6.852: Distributed Algorithms Fall, Class 2

T he Electronic Magazine of O riginal Peer-Reviewed Survey Articles ABSTRACT

Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web

How Asymmetry Helps Load Balancing

Lecture 1: Course overview, circuits, and formulas

B+ Tree Properties B+ Tree Searching B+ Tree Insertion B+ Tree Deletion Static Hashing Extendable Hashing Questions in pass papers

Lecture 4 Online and streaming algorithms for clustering

Universal hashing. In other words, the probability of a collision for two different keys x and y given a hash function randomly chosen from H is 1/m.

The Advantages and Disadvantages of Network Computing Nodes

In-Network Coding for Resilient Sensor Data Storage and Efficient Data Mule Collection

Tornado: A Capability-Aware Peer-to-Peer Storage Network

6 March Array Implementation of Binary Trees

Department of Computer Science Institute for System Architecture, Chair for Computer Networks. File Sharing

Multiple-Choice Random Network for Server Load Balancing

Introduction to IP v6

root node level: internal node edge leaf node Data Structures & Algorithms McQuain

Chord - A Distributed Hash Table

Lecture 6 Online and streaming algorithms for clustering

Sorting revisited. Build the binary search tree: O(n^2) Traverse the binary tree: O(n) Total: O(n^2) + O(n) = O(n^2)

LOOKING UP DATA IN P2P SYSTEMS

Varalakshmi.T #1, Arul Murugan.R #2 # Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam

Chord. A scalable peer-to-peer look-up protocol for internet applications

Lecture 3: Scaling by Load Balancing 1. Comments on reviews i. 2. Topic 1: Scalability a. QUESTION: What are problems? i. These papers look at

Entropy-Based Collaborative Detection of DDoS Attacks on Community Networks

1. Comments on reviews a. Need to avoid just summarizing web page asks you for:

Binary Search Trees. Data in each node. Larger than the data in its left child Smaller than the data in its right child

Network File Storage with Graceful Performance Degradation

CS5412: TIER 2 OVERLAYS

recursion, O(n), linked lists 6/14

! Solve problem to optimality. ! Solve problem in poly-time. ! Solve arbitrary instances of the problem. !-approximation algorithm.

Databases and Information Systems 1 Part 3: Storage Structures and Indices

Lecture 6: Binary Search Trees CSCI Algorithms I. Andrew Rosenberg

Distributed Computing over Communication Networks: Maximal Independent Set

Chapter 3. Enterprise Campus Network Design

Heterogeneity and Load Balance in Distributed Hash Tables


RVS-Seminar Overlay Multicast Quality of Service and Content Addressable Network (CAN)

Methods & Tools Peer-to-Peer Jakob Jenkov

Digital Signatures. What are Signature Schemes?

A Survey on Distributed Hash Table (DHT): Theory, Platforms, and Applications. Hao Zhang, Yonggang Wen, Haiyong Xie, and Nenghai Yu

CMSC 858T: Randomized Algorithms Spring 2003 Handout 8: The Local Lemma

A P2P SERVICE DISCOVERY STRATEGY BASED ON CONTENT

Binary Search Trees. A Generic Tree. Binary Trees. Nodes in a binary search tree ( B-S-T) are of the form. P parent. Key. Satellite data L R

Comparison on Different Load Balancing Algorithms of Peer to Peer Networks

2015 Internet Traffic Analysis

Overlay Networks. Slides adopted from Prof. Böszörményi, Distributed Systems, Summer 2004.

Persistent Data Structures and Planar Point Location

Unit Storage Structures 1. Storage Structures. Unit 4.3

! Solve problem to optimality. ! Solve problem in poly-time. ! Solve arbitrary instances of the problem. #-approximation algorithm.

Middleware and Distributed Systems. Peer-to-Peer Systems. Martin v. Löwis. Montag, 30. Januar 12

A binary heap is a complete binary tree, where each node has a higher priority than its children. This is called heap-order property

HBase Schema Design. NoSQL Ma4ers, Cologne, April Lars George Director EMEA Services

Scalable Prefix Matching for Internet Packet Forwarding

Classification/Decision Trees (II)

Physical Data Organization

Virtual Landmarks for the Internet

GISP: Global Information Sharing Protocol a distributed index for peer-to-peer systems

Identity Theft Protection in Structured Overlays

PSON: A Scalable Peer-to-Peer File Sharing System Supporting Complex Queries

Transcription:

Plaxton Routing - From a peer - to - peer network point of view Lars P. Wederhake Ferienakademie im Sarntal 2008 FAU Erlangen-Nürnberg, TU München, Uni Stuttgart September 2008

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 2 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 3 / 81

The Basic Problem... We want to: Share content with others Make content unavailable to others Search for content And that in fact as fast as possible... but... Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 4 / 81

Desirable Properties of a P2P - Net There s more than mere performance When evaluating a P2P - Net it is a good idea to consider the following criteria: Scalability Maintenance Reliability Security Anonymity Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 5 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 6 / 81

Origin and original intention Part I The W-Questions: Who: C. Greg Plaxton, Rajmohan Rajaraman, Andrea W. Richa Where: @ University of Texas in Austin What: Accessing Nearby Copies of Replicated Objects in a Distributed Environment When: April 1997 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 7 / 81

Origin and original intention Part II Why: (i) High speed networks, (ii) large numbers of geographically dispersed computers Cooperation & Sharing Content (iii) Rapidly growing demand of users... overloading network resources Main goal: Efficient usage of network resources Not intention: A P2P-Net Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 8 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 9 / 81

Overlay Network PR defines a routing mechanism and a virtual network structure: A virtual network with Neighbor Concept Messaging via TCP/IP Routing between nodes on application level Nodes usally are no routers in the underlay network Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 10 / 81

The Underlying Network To make their network model work: Cost function c : N R +, c(1) = 1 non-decreasing Symmetry: c(u, v) = c(v, u) Triangle inequaltiy: c(u, ω) c(u, v) + c(v, ω) ball with radius r around u is M(u, r) Regularity of metric: min{δ M(u, r), n} M(u, 2r) { M(u, r) } Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 11 / 81

Regularity of metric: Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 12 / 81

Overview on the Plaxton Model Part I The Plaxton Mesh is a distributed data structure with these properties Naming: random fixed length and unique bit-sequence. Typically hash of host/object name names independent of location and semanctics Structuring: Each node owns a neighbor list which is separated in a (i,j)- primary neighbor (i,j) secondary neighbors reverse neighbors pointer list of entries like: (A, Y, k), A: some object, Y: node Y, k: costs on accessing A on Y. Tree structure: every object is rooted at node with the bit-string nearest to object s one. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 13 / 81

Neighconcept: Visualization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 14 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 15 / 81

The Routing Procedure Message M Destination address D A Plaxton mesh routes M to the node whose name is numerically closest to D. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 16 / 81

Routing illustrated 5 hex digits Namespace: 2 20 Routing from 04234 to 99999 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 17 / 81

Routing Mechanism Part I Each node has a neighbor map Multiple levels log(n) level i - matching prefix entries for i digits Number of entries per level = the ID base = b Table Size: b log(n) At each entry the closest prefix matching node Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 18 / 81

Routing Mechanism Part II Route to node x e.g.: (A5F42) Shared prefix i Look at level i + 1 Match the next digit in destination Send message Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 19 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 20 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) A client C wants to find object O. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 21 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 22 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) A client C wants to find object O. Evaluates H(O), using same algorithm as the server Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 23 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 24 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) A client C wants to find object O. Evaluates H(O), using same algorithm as the server Sends a QUERY message to H(O) Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 25 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 26 / 81

Accessinging Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 27 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) A client C wants to find object O. Evaluates H(O), using same algorithm as the server Sends a QUERY message to H(O) Forwarded to X, the object root. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 28 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 29 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 30 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 31 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) The object root forwards the message to S. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 32 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 33 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 34 / 81

Content Accessing Locating H(O) := Hash of an object O S := Host of file (Server) Shortcut - Nodes in the tree of O also know location of O If QUERY message reaches one of these nodes, it is forwarded directly to S. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 35 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 36 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 37 / 81

Accessing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 38 / 81

Publishing & Sharing Content Exemplifying the algorithm H(O) := Hash of an object O S := Host of file (Server) Server S wants to publish object O S computes H(O), the object ID of O (hash of the name). Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 39 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 40 / 81

Publishing & Sharing Content Exemplifying the algorithm Server S wants to publish object O S computes H(O), the object ID of O (hash of the name). S sends a PUBLISH message to node H(O). Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 41 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 42 / 81

Publishing & Sharing Content Exemplifying the algorithm Server S wants to publish object O S computes H(O), the object ID of O (hash of the name). S sends a PUBLISH message to node H(O). Nodes visited by the PUBLISH message associate H(O) with physical address of S (including root node) These nodes are the tree of the object O Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 43 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 44 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 45 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 46 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 47 / 81

Publishing & Sharing Content Exemplifying the algorithm Node H(O) might not exist. No problem. Message forwarded deterministically to node X with address closest to H(O). X - root node for object O Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 48 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 49 / 81

Making Content Unavailable Demonstrating the algorithm Server S wants to unshare object O Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 50 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 51 / 81

Making Content Unavailable Demonstrating the algorithm Server S wants to unshare object O S deletes the entry (O, S, 0) from its pointer list Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 52 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 53 / 81

Making Content Unavailable Demonstrating the algorithm Server S wants to unshare object O S deletes the entry (O, S, 0) from its pointer list S asks its reverse neighbors for a copy of O S chooses that node/entry with smallest costs Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 54 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 55 / 81

Making Content Unavailable Demonstrating the algorithm Server S wants to unshare object O S deletes the entry (O, S, 0) from its pointer list S asks its reverse neighbors for the nearest copy of O If copy of O S receives success messages. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 56 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 57 / 81

Making Content Unavailable Demonstrating the algorithm S passes the delete request along the S Stops on not finding an entry or when on root. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 58 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 59 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 60 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 61 / 81

Publishing Visulization Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 62 / 81

Theorem 1 Hypothesis Theorem 1: Let x be any node in V and let A be any object in A. If y is the nearest node to x that holds a shared copy of A, then the expected cost of a read operation is: O(f (l(a)) c(x, y)). Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 63 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 64 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 65 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 66 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 67 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 68 / 81

Sketch of Proof Theorem 1 Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 69 / 81

Sketch of Proof - Theorem 1 Let k be = M(u, c(u, v)). What is the probability that u is a primary (i,j)-neighbor of v, if distance is c(u,v) Cancel nodes in ball within that radius until only those two are left Pr[P j (u)holds] = (1/2) (i+1)b (1 (1/2) (i+1)b ) NumberofNodesinarea Nodes in area are k/ 2. k minus v and u. upper bounded by e (k/ 2)/2(i+1)b Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 70 / 81

Sketch of Proof - Theorem 1 Corrollary: N(u, 2 ib log(n)) contains (i,j)-primary neighbor of v whp. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 71 / 81

Sketch of Proof - Theorem 1 We will proove u V, i [log(n)/b] Numberofi leaves(u) = O(2 ib log(n)) v i leaf (u) v N(u, c 0 2 ib log(n)); c R Corol. 1 j [i], v j N(v j+1, c 1 2 j+1 log(n)) Proof by Induction: Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 72 / 81

Sketch of Proof - Theorem 1 Hypothesis: j [i + 1], v = v 0 N(v j, c 0 2 jb log(n)) whp Induction base j=0 trivial Induction step : Assumption: v N(v j, c 0 2 jb log(n)) By Corol1 : v j N(v j+1, c 0 2 ib log(n) remember if v N(u, k 0 )andω N(v, k 1 ) w N(u, 2 k 0 + k 1 ) but set u = v j+1, v = v j and ω = v j 1 v N(v j+1, ( 2 k 0 + k 1 ) 2 jb log(n) Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 73 / 81

Sketch fo Proof - Theorem 1 set ( 2 k 0 + k 1 ) = c, that is a constant factor finally v N(v j+1, c 2 (j+1) b ) N(u, O(2 ib log(n)) Since by reg. of metric we can derive that the radius increases only by a constant factor, too. only finite number of steps => O(c(x, y) we won t proove: E[ c(x i, x i+1 ) + c(y i, y i+1 ))] O(c(x, y)) 0 i<τ Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 74 / 81

Theorem 2 Hypothesis Theorem 2: The expected cost of an insert operation is O(C), and that of a delete operation is O(C logn). Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 75 / 81

Theorem 3 Hypthesis Theorem 3: Let q be the number of objects that can be stored in the main memory of each node. The size of the auxiliary memory at each node is O(q log 2 n) words whp. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 76 / 81

Theorem 4 Hypothesis Definition 4.1: Adaptability: The number of nodes whose auxiliary memory is updated upon the addition or removal of a node. Theorem 4 The adaptability of our scheme is O(logn) expected and O(log 2 n) whp. Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 77 / 81

Overview 1 Introduction Motivation for studying PR The Background of PR 2 General Ideas and Concepts Plaxton Mesh under the Overlay The Routing Algorithm Content Related Operations 3 Results Advantages and Drawbacks of PR Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 78 / 81

Benefits of PR Locality Simple fault handling Scalable Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 79 / 81

Shortcomings of PR Global knowledge required to build routing tables Expensive to initialize the network Static network Bad for P2P Root node vulnerability Causes moderate maitenance Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 80 / 81

Conclusion PR provides a scalable, quite realiable, static network structure PR exploits locality Outlook How does it acquit itself on arbitrary cost functions? Is there any chance to improve the adaptability? How about hotspots or taking network bandwith into account? Lars (Ferienakademie im Sarntal 2008) Plaxton Routing Sept. 2008 81 / 81