Plethora: A Locality Enhancing Peer-to-Peer Network Ronaldo Alves Ferreira Advisor: Ananth Grama Co-advisor: Suresh Jagannathan Department of Computer Sciences – Purdue University July

Outline Introduction Motivation IP Addresses as Virtual IDs Autonomous Systems as Basis for Locality: Plethora Organization and Algorithms Simulation Results Conclusions Ongoing Work

Introduction Peer-to-Peer (P2P) networks are self-organizing distributed systems where participating nodes both provide and receive services from each other in a cooperative manner without distinguished roles as pure clients or pure servers. P2P Internet applications have recently been popularized by file sharing applications like Napster and Gnutella. P2P systems have many interesting technical aspects such as decentralized control, self-organization, adaptation and scalability. One of the key problems in large-scale P2P applications is to provide efficient algorithms for object location and routing within the network.

Location and Routing Central server (Napster) Controlled flooding (Gnutella) Sequential version of flooding (Freenet) Structured solution – “DHT” (Chord, Pastry, Tapestry, CAN)

Location and Routing - DHT All known proposals take as input a key and, in response, route a message to the node responsible for that key. The keys are strings of digits of some length (generally 128 bits). Nodes have identifiers taken from the same space as the keys (same number of digits). Each node maintains a routing table consisting of a small subset of nodes in the system. Nodes route queries to neighbor nodes that make the most “progress” towards resolving the query.

Location and Routing - DHT The notion of progress differs from algorithm to algorithm. Plaxton developed the first ideas that could be applied in a scalable manner. While intended for a static node population, Plaxton algorithm provides efficient routing of queries. The algorithm works by “correcting” a single digit at a time. Chord, Pastry, and Tapestry are variants of Plaxton algorithm.

Location and Routing - DHT 0XXX1XXX2XXX3XXX START 0112 routes a message to key First hop fixes first digit (2) Second hop fixes second digit (20) END 2001 closest live node to 2000.

Location and Routing - DHT

Location and Routing - DHT Node 0 Routing Table Leaf Set

Location and Routing - DHT Node 0 Routing Table

Location and Routing - Pastry Computers (nodes) have unique ID  Typically 128 bits long  Assignment should lead to uniform distribution in the node ID space, for example SHA-1 of node’s IP Primitive: route(msg, key)  Deliver msg to currently alive node with ID numerically closest to key Node state  Routing table  Neighborhood set  Leaf set Scalable, efficient  O(log(N)) routing table entries per node  Route in O(log(N)) number of hops

DHT Performance Issues Virtualization destroys locality. Messages may have to travel around the world to reach a node in the same LAN. Query responses do not contain locality information. Heuristics to minimize the problem:  Proximity routing  Topology-based node ID assignment  Proximity neighbor selection

Motivation Virtualization destroys locality. Query responses do not contain locality information. Recent studies show that queries for multiple keys in P2P networks follow a Zipf-like distribution. For many wide-are distributed applications, nodes in the same region share common interests. For example, music sharing applications.

IP Addresses as Virtual IDs A natural way of building locality in an overlay network is to explore the addressing scheme of the underlying network. In most cases, nodes with IP addresses that are numerically close are also physically close. Organization of the Internet in ASs. By correcting a few bits in each hop, the last hops would be inside an AS.

IP Addresses as Virtual IDs IP space is not uniformly populated by peers. Load imbalance at the peers. The upper bound of O(log n) can no longer be guaranteed.

IP Addresses as Virtual IDs How severe would be the load imbalance if we use the IP address of the node as its overlay identifier? Is it possible to find a boundary in the IP address such that distribution of peers is uniform and such that some form of locality is captured? Experimental Basis: Gnutella traces from June 2002 with 56M messages. 62,000 different IP addresses. Addresses were validated using a whois server and Ping.

IP Addresses as Virtual IDs

2,420 nodes. 20 keys per node.

IP Addresses as Virtual IDs

Average CIDR prefix length for the address over 19 bits. Negative result. Provides us with an insight to propose a two-level overlay architecture. One global overlay, and several local overlays. A local overlay is formed with nodes that share the first 8 bits.

IP Addresses as Virtual IDs

Plethora Two-level overlay  One global overlay  Several local overlays Global overlay is the main repository of data. Any DHT protocol can be used. Global overlay helps nodes organize themselves into local overlays. Local overlays explore the organization of the Internet in ASs. Local overlays use a modified version of Pastry. Size of the local overlay is controlled by a local overlay leader.  Uses efficient distributed algorithms for merging and splitting local overlays.

Plethora – Data Access

Plethora – LO Routing Information Corrects a single bit at each hop. Each node has a routing table and a leaf set as in Pastry. Each routing table entry has pointers to a primary and to a secondary neighbor. Primary neighbors are used to implement proximity neighbor selection. Secondary neighbors are used to implement the local overlay split operation.

Node Arrivals When joining the network, a node first joins the global overlay using the specific DHT protocol. After joining the global overlay, the new node contacts the rendezvous point of its AS to determine which local overlay it will join. A new node uses its AS neighborhood information to join other AS local overlays when there is no node of its own AS in the network.

Splitting Local Overlays AS Invariant Nodes of the same autonomous system must always stay in the same local overlay after a split operation.

Splitting Local Overlays Nodes use a hash function on their AS numbers to determine other nodes that will stay together in the same local overlay after a split operation. During network operation, nodes make secondary neighbor pointers in their routing tables point to nodes with the same AS hash value. Local overlay leader periodically circulates a message to determine the number of nodes in the LO. If the number of nodes exceeds the maximum threshold, the leader issues a split message to all nodes in the LO. On receiving a split message, a node n discards pointers to nodes whose hash values differ from it.

Splitting Local Overlays

Lemma: After a split operation, the two new local overlays are connected with high probability.  Set the leaf set to K log M, where M is the maximum number of nodes allowed in a local overlay, and K is a constant greater than 1.  Assuming that the hash values 0 and 1 are equally possible, the probability of a node n being disconnected is equal to:  The probability of n being in a connected overlay is:

Node Departures Node departures are handled lazily. If a node detects that one of its neighbors has left the network, it routes using alternative mechanisms (for example, leaf set) and tries to find a replacement for the missing node. If the local overlay leader leaves, the first node that detects its departure triggers a new leader election protocol.

Merging Local Overlays If the sizes of the two overlays differ for more than a constant factor α, simple insertions of the nodes of the smaller overlay are performed into the larger overlay. If the sizes of the two overlays are within a constant factor α, use distributed algorithm based on hypercube merging. Analogous to merging two hypercubes of dimension d to produce a hypercube of dimension d+1. On receiving a merge message, nodes add a new row to their routing table.

Merging Local Overlays

Node 0 Routing Table Leaf Set L L 1 2

Merging Local Overlays Node 0 Routing Table Leaf Set

Simulation Setup Internet topology generated using GT-ITM topology generator. 10 transit domains. 1,000 stub domains. 100,000 hosts Each stub domain is one AS. 10,000 overlay nodes selected randomly from the hosts. NLANR web proxy trace with 500,254 objects. Zipf distribution parameters: {0.70, 0.75, 0.80, 0.85, 0.90} Maximum overlay sizes: {200; 300; 400; 500; 1,000; 2,000} Local cache size: 5MB (LRU replacement policy).

Simulation Results Response Delay

Simulation Results Response Delay

Simulation Results Response Delay

Simulation Results Number of Messages

Simulation Results Number of Messages

Simulation Results Split Operation

Simulation Results Merge Operation

Conclusions Use of IP addresses as virtual IDs would probably produce overlays with good locality properties, but the non-uniform population of nodes in the IP space leads to severe load imbalances and no guarantees on the number of hops exist. Plethora is a two-level overlay architecture. Local overlays are created to cluster nodes that are close in the underlying network. Plethora uses efficient distributed algorithms for merging and splitting local overlays. The performance gains of a two-level architecture are significant, when compared with a single global overlay. The costs of maintaining the two-level architecture are very low.

Future Work Short term goal: develop a caching replacement policy using availability of the nodes as a parameter. Long term goal: implementation of a version-based wide- area read-write distributed file system using Plethora as its routing core.