Petar Maymounkov

Kademlia: A Peer-to-Peer Information System Based on the XOR Metric

We describe a peer-to-peer distributed hash table with provable consistency and performance in a fault-prone environment. Our system routes queries and locates nodes using a novel XOR-based metric topology that simplifies the algorithm and facilitates our proof. The topology has the property that every message exchanged conveys or reinforces useful contact information. The system exploits this information to send parallel, asynchronous query messages that tolerate node failures without imposing timeout delays on users.

Rateless Codes and Big Downloads

This paper presents a novel algorithm for downloading big files from multiple sources in peer-to-peer networks. The algorithm is simple, but offers several compelling properties. It ensures low hand-shaking overhead between peers that download files (or parts of files) from each other. It is computationally efficient, with cost linear in the amount of data transfered. Most importantly, when nodes leave the network in the middle of uploads, the algorithm minimizes the duplicate information shared by nodes with truncated downloads. Thus, any two peers with partial knowledge of a given file can almost always fully benefit from each other’s knowledge. Our algorithm is made possible by the recent introduction of linear-time, rateless erasure codes.

Global computation in a poorly connected world: fast rumor spreading with no dependence on conductance

In this paper, we study the question of how efficiently a collection of interconnected nodes can perform a global computation in the GOSSIP model of communication. In this model, nodes do not know the global topology of the network, and they may only initiate contact with a single neighbor in each round. This model contrasts with the much less restrictive LOCAL model, where a node may simultaneously communicate with all of its neighbors in a single round. A basic question in this setting is how many rounds of communication are required for the information dissemination problem, in which each node has some piece of information and is required to collect all others. In the LOCAL model, this is quite simple: each node broadcasts all of its information in each round, and the number of rounds required will be equal to the diameter of the underlying communication graph. In the GOSSIP model, each node must independently choose a single neighbor to contact, and the lack of global information makes it difficult to make any sort of principled choice. As such, researchers have focused on the uniform gossip algorithm, in which each node independently selects a neighbor uniformly at random. When the graph is well-connected, this works quite well. In a string of beautiful papers, researchers proved a sequence of successively stronger bounds on the number of rounds required in terms of the conductance φ and graph size n, culminating in a bound of O(φ-1 log n). In this paper, we show that a fairly simple modification of the protocol gives an algorithm that solves the information dissemination problem in at most O(D + polylog (n)) rounds in a network of diameter D, with no dependence on the conductance. This is at most an additive polylogarithmic factor from the trivial lower bound of D, which applies even in the LOCAL model. In fact, we prove that something stronger is true: any algorithm that requires T rounds in the LOCAL model can be simulated in O(T + polylog(n)) rounds in the GOSSIP model. We thus prove that these two models of distributed computation are essentially equivalent.

Routing with Probabilistic Delay Guarantees in Wireless Ad-Hoc Networks

In many wireless ad-hoc networks it is important to find a route that delivers a message to the destination within a certain deadline (delay constraint). We propose to identify such routes based on average channel state information (CSI) only, since this information can be distributed more easily over the network. Such cases allow probabilistic QoS guarantees i.e., we maximize and report the probability of on-time delivery. We develop a convolution-free lower bound on probability of on-time arrival, and a scheme to rapidly identify a path that maximizes this bound. This analysis is motivated by a class of infinite variance subexponential distributions whose properties preclude the use of deviation bounds and convolutional schemes. The bound then forms the basis of an algorithm that finds routes that give probabilistic delay guarantees. Simulations demonstrate that the algorithm performs better than shortest-path algorithm based on statistics of path loss or CSI.

Electric Routing and Concurrent Flow Cutting

We investigate an oblivious routing scheme amenable to distributed computation and resilient to graph changes, based on electrical flow. Our main technical contribution is a new rounding method which we use to obtain a bound on the L 1?L 1 operator norm of the inverse graph Laplacian.

Rumor Spreading with No Dependence on Conductance

In this paper, we study how a collection of interconnected nodes can efficiently perform a global computation in the

A peer-to-peer information system based on the XOR metric

\mathcal{GOSSIP}

Electric routing and concurrent flow cutting

model of communication. In this model nodes do not know the global topology of the network and may only initiate contact with a single neighbor in each round. This contrasts with the much less restrictive

Blendenpik: Supercharging LAPACK's Least-Squares Solver

\mathcal{LOCAL}

BLENDENPIK: SUPERCHARGING LAPACK'S LEAST-SQUARES

model, where a node may simultaneously communicate with all of its neighbors in a single round. A basic question in this setting is how many rounds of communication are required for the information dissemination problem, in which each node has some piece of information and is required to collect all others. In the