Scheduling in a Ring with Unit Capacity Links

We consider the problem of scheduling unit-sized jobs on a ring of processors with the objective of minimizing the completion time of the last job. Unlike much previous work we place restrictions on the capacity of the network links connecting processors. We give a polynomial time centralized algorithm that produces optimal length schedules. We also give a simple distributed 2-approximation algorithm

Distributed Scheduling in Finite Capacity Networks

We consider the problem of scheduling unit-sized jobs in a distributed network of processors. Each processor only knows the number of jobs it and its neighbors have. We give an analysis of intuitive algorithm and prove that the algorithm produces schedules that are within a logarithmic factor of the length of the optimal schedule given that the optimal schedule is sufficiently long

Treelicious: a System for Semantically Navigating Tagged Web Pages

Collaborative tagging has emerged as a popular and effective method for organizing and describing pages on the Web. We present Treelicious, a system that allows hierarchical navigation of tagged web pages. Our system enriches the navigational capabilities of standard tagging systems, which typically exploit only popularity and co-occurrence data. We describe a prototype that leverages the Wikipedia category structure to allow a user to semantically navigate pages from the Delicious social bookmarking service. In our system a user can perform an ordinary keyword search and browse relevant pages but is also given the ability to broaden the search to more general topics and narrow it to more specific topics. We show that Treelicious indeed provides an intuitive framework that allows for improved and effective discovery of knowledge.Comment: 6 pages, 3 figure

Scheduling on a Ring with Unit Capacity Links

We consider the problem of scheduling unit-sized jobs on a ring of processors with the objective of minimizing the completion time of the last job. Unlike much previous work we place restrictions on the capacity of the network links connecting processors. We give a polynomial time centralized algorithm that produces optimal length schedules. We also give a simple distributed 2approximation algorithm. 1 Preliminaries We consider the problem of scheduling unit sized jobs on a network of processors arranged in a ring. An instance, I, of network scheduling can be described by I = (G; J) where G = (V; E) is an undirected graph representing the network and J is the set of jobs to be processed. Using the scheduling nomenclature we say there are m processors (or machines) labeled p 1 ; p 2 ; : : : pm , and n jobs. Each vertex in V corresponds to a processor and each edge corresponds to a network link (notice this means there are m nodes in the graph). Each edge has an associated capacity w..

Distributed Scheduling in Finite Capacity Networks

this paper, we show that a simple distributed algorithm for network scheduling in arbitrary m processor networks with unit capacity links is an O(log m)-approximation algorithm if the optimal schedule length is sufficiently large. We will assume that there are m machines or processors labeled p 1 ; p 2 ; : : : ; p m , such that processor p i has j i jobs an

Distributed Job Scheduling in Rings

We give a distributed approximation algorithm for job scheduling in a ring architecture. In contrast to many other parallel scheduling models, the model we consider captures the influence of the underlying communications network by specifying that task migration from one processor to another takes time proportional to the distance between those two processors in the network. As a result, our algorithm must balance both computational load and communication time. The algorithm is simple, requires no global control, and yields schedules of length at most 4:22 times optimal. We also give a lower bound on the performance of any distributed algorithm, and the results of simulation experiments which suggest better performance than does our worst-case analysis

Job Scheduling in Rings

We give distributed approximation algorithms for job scheduling in a ring architecture. In contrast to almost all other parallel scheduling models, the model we consider captures the influence of the underlying communications network by specifying that task migration from one processor to another takes time proportional to the distance between those two processors in the network. As a result, our algorithms must balance both computational load and communication time. The algorithms are simple, require no global control, and work in a variety of settings. All come with small constant-factor approximation guarantees; the basic algorithm yields schedules of length at most 4:22 times optimal. We also give a lower bound on the performance of any distributed algorithm and the results of simulation experiments, which give better results than our worst-case analysis. Research partially supported by NSF grant CCR-9308701, a Walter Burke Research Initiation Award and a Dartmouth College Resear..

Distributed Job Scheduling in Rings

We give a distributed approximation algorithm for job scheduling in a ring architecture. In contrast to many other parallel scheduling models, the model we consider captures the influence of the underlying communications network by specifying that task migration from one processor to another takes time proportional to the distance between those two processors in the network. As a result, our algorithm must balance both computational load and communication time. The algorithm is simple, requires no global control, and yields schedules of length at most 4:22 times optimal. We also give a lower bound on the performance of any distributed algorithm, and the results of simulation experiments which suggest better performance than does our worst-case analysis