K
Kenneth A. Ross
Researcher at Columbia University
Publications - 194
Citations - 10626
Kenneth A. Ross is an academic researcher from Columbia University. The author has contributed to research in topics: Cache & Tuple. The author has an hindex of 51, co-authored 194 publications receiving 10254 citations. Previous affiliations of Kenneth A. Ross include Alcatel-Lucent & University of Melbourne.
Papers
More filters
Journal ArticleDOI
The well-founded semantics for general logic programs
TL;DR: It is shown that the class of programs possessing a total well-founded model properly includes previously studied classes of "stratified" and "locally stratified" programs, and is compared with other proposals in the literature.
Proceedings ArticleDOI
Filtering algorithms and implementation for very fast publish/subscribe systems
Françoise Fabret,H.-Arno Jacobsen,François Llirbat,João Pereira,Kenneth A. Ross,Dennis Shasha +5 more
TL;DR: In this article, the authors describe an attempt at the construction of such algorithms and its implementation using a combination of data structures, application-specific caching policies, and application specific query processing, which can handle 600 events per second for a typical workload containing 6 million subscriptions.
Journal ArticleDOI
Making B+- trees cache conscious in main memory
Jun Rao,Kenneth A. Ross +1 more
TL;DR: A new indexing technique called CSB+-Trees is proposed that stores all the child nodes of any given node contiguously, and keeps only the address of the first child in each node, and introduces two variants of CSB+, which can reduce the copying cost when there is a split and preallocate space for the full node group to reduce the split cost.
Proceedings ArticleDOI
Unfounded sets and well-founded semantics for general logic programs
TL;DR: It is shown that a program has a unique stable model if it has a well-founded model, in which case they are the same, and the converse is not true.
Proceedings ArticleDOI
Cache Conscious Indexing for Decision-Support in Main Memory
Jun Rao,Kenneth A. Ross +1 more
TL;DR: A new indexing technique called \Cache-Sensitive Search Trees" (CSS-trees) is proposed, to provide faster lookup times than binary search by paying attention to reference locality and cache behavior, without using substantial extra space.