Tom Leighton

Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the World Wide Web

We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe, and where it is not feasible for every server to have complete information about the current state of the entire network. The protocols are easy to implement using existing network protocols such as TCP/IP, and require very little overhead. The protocols work with local control, make efficient use of existing resources, and scale gracefully as the network grows. Our caching protocols are based on a special kind of hashing that we call consistent hashing. Roughly speaking, a consistent hash function is one which changes minimally as the range of the function changes. Through the development of good consistent hash functions, we are able to develop caching protocols which do not require users to have a current or even consistent view of the network. We believe that consistent hash functions may eventually prove to be useful in other applications such as distributed name servers and/or quorum systems.

Multicommodity max-flow min-cut theorems and their use in designing approximation algorithms

In this paper, we establish max-flow min-cut theorems for several important classes of multicommodity flow problems. In particular, we show that for any n-node multicommodity flow problem with uniform demands, the max-flow for the problem is within an O(log n) factor of the upper bound implied by the min-cut. The result (which is existentially optimal) establishes an important analogue of the famous 1-commodity max-flow min-cut theorem for problems with multiple commodities. The result also has substantial applications to the field of approximation algorithms. For example, we use the flow result to design the first polynomial-time (polylog n-times-optimal) approximation algorithms for well-known NP-hard optimization problems such as graph partitioning, min-cut linear arrangement, crossing number, VLSI layout, and minimum feedback arc set. Applications of the flow results to path routing problems, network reconfiguration, communication in distributed networks, scientific computing and rapidly mixing Markov chains are also described in the paper. Categories and Subject Descriptors: F.2.2 (Analysis of Algorithms and Problem Complexity):

An approximate max-flow min-cut theorem for uniform multicommodity flow problems with applications to approximation algorithms

A multicommodity flow problem is considered where for each pair of vertices (u, v) it is required to send f half-units of commodity (u, v) from u to v and f half-units of commodity (v, u) from v to u without violating capacity constraints. The main result is an algorithm for performing the task provided that the capacity of each cut exceeds the demand across the cut by a Theta (log n) factor. The condition on cuts is required in the worst case, and is trivially within a Theta (log n) factor of optimal for any flow problem. The result can be used to construct the first polylog-times optimal approximation algorithms for a wide variety of problems, including minimum quotient separators, 1/3-2/3 separators, bifurcators, crossing number, and VLSI layout area. It can also be used to route packets efficiently in arbitrary distributed networks.<<ETX>>

Protein folding in the hydrophobic-hydrophilic ( HP ) is NP-complete

One of the simplest and most popular biophysical models of protein folding is the hydrophobic-hydrophilic (HP) model. The HP model abstracts the hydrophobic interaction in protein folding by labeling the amino acids as hydrophobic (H for nonpolar) or hydrophilic (P for polar). Chains of amino acids are configured as self-avoiding walks on the 3D cubic lattice, where an optimal conformation maximizes the number of adjacencies between Hs. In this paper, the protein folding problem under the HP model on the cubic lattice is shown to be NP-complete. This means that the protein folding problem belongs to a large set of problems that are believed to be computationally intractable.

Protein folding in the hydrophobic-hydrophilic (HP) model is NP-complete.

One of the simplest and most popular biophysical models of protein folding is the hydrophobic-hydrophilic (HP) model. The HP model abstracts the hydrophobic interaction in protein folding by labeling the amino acids as hydrophobic (H for nonpolar) or hydrophilic (P for polar). Chains of amino acids are configured as self-avoiding walks on the 3D cubic lattice, where an optimal conformation maximizes the number of adjacencies between Hs. In this paper, the protein folding problem under the HP model on the cubic lattice is shown to be NP-complete. This means that the protein folding problem belongs to a large set of problems that are believed to be computationally intractable.

Resource discovery in distributed networks

In large distributed networks of computers, it is often the case that a subset of machines wants to cooperate to perform a task. Before they can do so, these machines need to learn of the existence of each other. In this paper we are interested in distributed algorithms whereby machines in a network learn of other machines in the network by making queries to machines they already know. The algorithms should be efficient both in terms of the time required and in terms of the total network communication required until all machines have discovered all other machines. We propose a very simple algorithm called Name-Dropper whereby all machines learn about each other within O(log’ n) rounds with high probability, where n is the number of machines in the network. The total number of connections required is O(n log2 n) and the total number of pointers which must be communicated is O(n2 log2 n), with high probability. Each of the preceding bounds is optimal to within polylogarithmic factors.

Universal packet routing algorithms

The packet-routing problem is examined in a network-independent context. The goal is to devise a strategy for routing that works well for a wide variety of networks. To achieve this goal, the routing problem is partitioned into two stages: a path-selection stage and a scheduling stage. In the first stage, paths for the packets are found with small maximum distance and small maximum congestion. Once the paths are fixed, both are lower bounds on the time required to deliver the packets. In the second stage, a schedule is found for the movement of each packet along its path so that no two packets traverse the same edge at the same time and the total time and maximum queue size required to route all of the packets to their destinations are minimized. The second stage is more challenging and is the focus of this study.<<ETX>>

Improved approximation algorithms for the multi-commodity flow problem and local competitive routing in dynamic networks

Improved Approximation Algorithms the Multi-Commodity Flow Problem and Competitive Routing in Dynamic Networks

Universal-stability results and performance bounds for greedy contention-resolution protocols

In this paper, we analyze the behavior of packet-switched communication networks in which packets arrive dynamically at the nodes and are routed in discrete time steps across the edges. We focus on a basic adversarial model of packet arrival and path determination for which the time-averaged arrival rate of packets requiring the use of any edge is limited to be less than 1. This model can reflect the behavior of connection-oriented networks with transient connections (such as ATM networks) as well as connectionless networks (such as the Internet). We concentrate on greedy (also known as work-conserving) contention-resolution protocols. A crucial issue that arises in such a setting is that of stability—will the number of packets in the system remain bounded, as the system runs for an arbitrarily long period of time? We study the universal stability of network (i.e., stability under all greedy protocols) and universal stability of protocols (i.e., stability in all networks). Once the stability of a system is granted, we focus on the two main parameters that characterize its performance: maximum queue size required and maximum end-to-end delay experienced by any packet. Among other things, we show: (i) There exist simple greedy protocols that are stable for all networks.(ii) There exist other commonly used protocols (such as FIFO) and networks (such as arrays and hypercubes) that are not stable.(iii) The n-node ring is stable for all greedy routing protocols (with maximum queue-size and packet delay that is linear in n).(iv) There exists a simple distributed randomized greedy protocol that is stable for all networks and requires only polynomial queue size and polynomial delay.Our results resolve several questions posed by Borodin et al., and provide the first examples of (i) a protocol that is stable for all networks, and (ii) a protocol that is not stable for all networks.

Analysis of Backoff Protocols for Mulitiple AccessChannels

In this paper, we analyze the stochastic behavior of backoff protocols for multiple access channels such as the Ethernet. In particular, we prove that binary exponential backoff is unstable if the arrival rate of new messages at each station is