ALGORITHMICA
2005
13 years 10 months ago
2005
ALGORITHMICA
2005
13 years 10 months ago
2005
In an adversarial queueing network, the incoming traffic is decided by an adversary, who operates under a reasonable rate restriction. This model provides a valuable, complementar...
ALGORITHMICA
2005
13 years 10 months ago
2005
We consider the setting of a web server that receives requests for documents from clients, and returns the requested documents over a multicast/broadcast channel. We compare the q...
ALGORITHMICA
2005
13 years 10 months ago
2005
Abstract. The Quality of Service Multicast Tree Problem is a generalization of the Steiner tree problem which appears in the context of multimedia multicast and network design. In ...
ALGORITHMICA
2005
13 years 10 months ago
2005
An optimal prefetching and I/O scheduling algorithm L-OPT, for parallel I/O systems, using a read-once model of block references is presented. The algorithm uses knowledge of the n...
ALGORITHMICA
2005
13 years 10 months ago
2005
A new priority queue structure, the queap, is introduced. The queap executes insertion in O(1) amortized time and extract-min in O(log(k+2)) amortized time if there are k items th...
ALGORITHMICA
2005
13 years 10 months ago
2005
A new form of optimality for comparison based static dictionaries is introduced. This type of optimality, keyindependent optimality, is motivated by applications that assign key v...
ALGORITHMICA
2005
13 years 10 months ago
2005
We present a new bit-parallel technique for approximate string matching. We build on two previous techniques. The first one, BPM [Myers, J. of the ACM, 1999], searches for a patte...
ALGORITHMICA
2005
13 years 10 months ago
2005
We consider history independent data structures as proposed for study by Naor and Teague [3]. In a history independent data structure, nothing can be learned from the memory repre...
ALGORITHMICA
2005
13 years 10 months ago
2005
We present polynomial upper and lower bounds on the number of iterations performed by the k-means method (a.k.a. Lloyd's method) for k-means clustering. Our upper bounds are ...