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Emanuel Dar

dblp:35/4966 · DBLP profile ↗
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6ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 6Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Algorithms and data structures · 100%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Embedded and real-time systems · 69% Parallel and multicore computing · 31%

Topics — the 9 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › sequence algorithms
string algorithms
0.122004
The submatrices character count problem: an efficient solution using separable values · Inf. Comput. 2004
Separable attributes: a technique for solving the sub matrices character count problem · SODA 2002
Embedded and real-time systems › real-time scheduling
multiprocessor scheduling
0.022000
The Power of Migration in Multiprocessor Scheduling of Real-Time Systems · SIAM J. Comput. 2000
The Power of Migration in Multi-Processor Scheduling of Real-Time Systems · SODA 1998
Embedded and real-time systems
real-time scheduling
0.022000
The Power of Migration in Multiprocessor Scheduling of Real-Time Systems · SIAM J. Comput. 2000
The Power of Migration in Multi-Processor Scheduling of Real-Time Systems · SODA 1998
Algorithms and data structures › sequence algorithms › string algorithms
combinatorial pattern matching
0.012004
The submatrices character count problem: an efficient solution using separable values · Inf. Comput. 2004
Algorithms and data structures › sequence algorithms › string algorithms
string matching
0.012004
The submatrices character count problem: an efficient solution using separable values · Inf. Comput. 2004
Algorithms and data structures
numerical linear algebra
0.012002
Separable attributes: a technique for solving the sub matrices character count problem · SODA 2002
Parallel and multicore computing
competitive analysis
0.012000
The Power of Migration in Multiprocessor Scheduling of Real-Time Systems · SIAM J. Comput. 2000
Embedded and real-time systems › real-time scheduling
pre-run-time scheduling
0.012000
The Power of Migration in Multiprocessor Scheduling of Real-Time Systems · SIAM J. Comput. 2000
Parallel and multicore computing › load balancing › dynamic load balancing
task migration
0.012000
The Power of Migration in Multiprocessor Scheduling of Real-Time Systems · SIAM J. Comput. 2000

Methods — techniques the papers use, named apart from their topics

combinatorial algorithms · 0.0
YearPublicationVenuePosition
2004 The submatrices character count problem: an efficient solution using separable values
Amihood Amir, Kenneth Church 0001, Emanuel Dar
Inf. Comput.3
2002 Separable attributes: a technique for solving the sub matrices character count problem
Amihood Amir, Kenneth Church 0001, Emanuel Dar
SODA3
2000 The Power of Migration in Multiprocessor Scheduling of Real-Time Systems
abstract
In this paper we study the performance of off-line multiprocessor real-time schedules that allow task migration compared to those that forbid migration. We consider an off-line scheduling problem in which a given collection of tasks, each with a release time, computation time, and deadline, are to be run on a multiprocessor system. A preemptive schedule allows the execution of a task to be temporarily suspended and resumed at a later time. A migrative schedule allows the task to resume on any processor whereas a nonmigrative schedule allows the task to resume only on the processor in which it was initially started. A schedule value is the summation of all the values of all the tasks that were completed by their deadlines. In this paper we assume that a task's value is proportional to its computation time. We present lower and upper bound results. For a system with n processors, we construct a nonmigrative schedule that is guaranteed to achieve at least $1-( 1-\frac 1{2n}) ^n$ of the optimal migrative schedule value. In addition, we show task sets for which even an optimal nonmigrative schedule achieves at most n/(2n-1) of the optimal migrative value. Asymptotically (as $n\rightarrow \infty $) our upper bound approaches 1/2 and the lower bound approaches $1 - {1\over \sqrt{e}} \sim 0.3935$.
Gilad Koren, Emanuel Dar, Amihood Amir
SIAM J. Comput.2
1998 The Power of Migration in Multi-Processor Scheduling of Real-Time Systems
Gilad Koren, Amihood Amir, Emanuel Dar
SODA3
1997 An Improved Deterministic Algorithms for Generalized Random Sampling
Amihood Amir, Emanuel Dar
CIAC2
1997 An Improved Deterministic Algorithm for Generating Different Many-Element Random Samples
Amihood Amir, Emanuel Dar
Inf. Process. Lett.2