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Anomalies in Parallel BranchandBound Algorithms
, 1984
"... We consider the effects of parallelizing branchandbound algorithms by expanding several live nodes simultaneously. It is shown that it is quite possible for a parallel branchandbound algorithm using n 2 processors to take more time than one using n 1 processors even though n 1 < n 2 . Furthermor ..."
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Cited by 50 (3 self)
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We consider the effects of parallelizing branchandbound algorithms by expanding several live nodes simultaneously. It is shown that it is quite possible for a parallel branchandbound algorithm using n 2 processors to take more time than one using n 1 processors even though n 1 < n 2 . Furthermore, it is also possible to achieve speedups that are in excess of the ratio n 2 /n 1 . Experimental results with the 0/1Knapsack and Traveling Salesperson problems are also presented.
A Parametrized BranchandBound Strategy for Scheduling PrecedenceConstrained Tasks on a Multiprocessor System
 Proc. of the Int'l Conf. on Parallel Processing
, 1997
"... In this paper we experimentally evaluate the performance of a parametrized branchandbound (B&B) algorithm for scheduling realtime tasks on a multiprocessor system. The objective of the B&B algorithm is to minimize the maximum task lateness in the system. We show that a lastinfirstout (LIFO) ve ..."
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Cited by 20 (7 self)
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In this paper we experimentally evaluate the performance of a parametrized branchandbound (B&B) algorithm for scheduling realtime tasks on a multiprocessor system. The objective of the B&B algorithm is to minimize the maximum task lateness in the system. We show that a lastinfirstout (LIFO) vertex selection rule clearly outperforms the commonly used leastlowerbound (LLB) rule for the scheduling problem. We also present a new adaptive lowerbound cost function that greatly improves the performance of the B&B algorithm when parallelism in the application cannot be fully exploited on the multiprocessor architecture. Finally, we evaluate a set of heuristic strategies, one of which generates nearoptimal results with performance guarantees and another of which generates approximate results without performance guarantees. 1 Introduction Since its introduction in the field of artificial intelligence, the branchandbound (B&B) strategy has been successfully used for finding optimal ...
epsilonTransformation: Exploiting Phase Transitions to Solve Combinatorial Optimization Problems
 Artificial Intelligence
, 1994
"... It has been shown that there exists a transition in the averagecase complexity of tree search problems, from exponential to polynomial in the search depth. We develop a new method, called ffl transformation, which makes use of this complexity transition, to find a suboptimal solution. With a rando ..."
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Cited by 12 (3 self)
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It has been shown that there exists a transition in the averagecase complexity of tree search problems, from exponential to polynomial in the search depth. We develop a new method, called ffl transformation, which makes use of this complexity transition, to find a suboptimal solution. With a random tree model, we show that the expected number of nodes expanded by branchandbound (BnB) using ffltransformation is at most cubic in the search depth, and that the error of the solution cost found relative to the optimal solution cost is a small constant. We also present an iterative version of ffltransformation that can be used to find both optimal and suboptimal goal nodes. Depthfirst BnB (DFBnB) using iterative ffltransformation significantly improves upon truncated DFBnB on random trees with large branching factors and deep goal nodes, finding better solutions sooner on average. Our experiments on the asymmetric traveling salesman problem show that DFBnB using ffl transformati...
GAST: A Flexible and Extensible Tool for Evaluating Multiprocessor Assignment and Scheduling Techniques
 Proc. of the Int'l Conf. on Parallel Processing
, 1998
"... Automatic tool support for scheduling applications on multiprocessor platforms is of paramount importance both to guarantee critical application demands and to keep development costs down. In this paper, we present GAST, an objectoriented evaluation environment for multiprocessor assignment and sche ..."
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Cited by 11 (7 self)
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Automatic tool support for scheduling applications on multiprocessor platforms is of paramount importance both to guarantee critical application demands and to keep development costs down. In this paper, we present GAST, an objectoriented evaluation environment for multiprocessor assignment and scheduling techniques. GAST is based on a decomposition approach where existing assignment and scheduling techniques have been broken down into a set of common operations. By combining these operations into a complete scheduling process, GAST offers a powerful toolbox of existing assignment and scheduling techniques. GAST has been implemented on several popular operating systems and is accompanied by a graphic visualization tool that allows for flexible interaction with the application scheduling process. 1 Introduction For economical reasons, singleprocessor computers have traditionally been the only viable option for many computer system designers. This has, in turn, limited the sphere of f...
Effective Complexity Reduction for Optimal Scheduling of Distributed RealTime Applications
 Proc. of the IEEE Int'l Conf. on Distributed Computing Systems
, 1999
"... The application of optimal search strategies to scheduling for distributed realtime systems is, in general, plagued by an inherent computational complexity. This has effectively prevented the integration of strategies such as branchandbound (B&B) in scheduling frameworks and tools used in practice ..."
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Cited by 8 (6 self)
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The application of optimal search strategies to scheduling for distributed realtime systems is, in general, plagued by an inherent computational complexity. This has effectively prevented the integration of strategies such as branchandbound (B&B) in scheduling frameworks and tools used in practice today. To show that optimal scheduling is, in fact, a viable alternative for many realtime scheduling scenarios, we propose an approach that can reduce the average search complexity to levels comparable with that of a polynomialtime heuristic. Our approach is based on making intelligent choices in the selection of strategies for search tree vertex traversal and task deadline assignment. More specifically, we conjecture that effective complexity reduction is achieved by (i) traversing vertices in the search tree in a depthfirst fashion and (ii) assigning local task deadlines that are nonoverlapping fractions of the application endtoend deadline. Through an extensive experimental study, w...
ConstraintLogic Based Approach To Scheduling
, 1993
"... This work is an attempt to bring forward and amalgamate a number of different technologies. Our motivation originates in extending the classical Logic Programming paradigm for effective reasoning over disjunctive information. In doing so we take aboard notions from the area of constraint satisfactio ..."
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This work is an attempt to bring forward and amalgamate a number of different technologies. Our motivation originates in extending the classical Logic Programming paradigm for effective reasoning over disjunctive information. In doing so we take aboard notions from the area of constraint satisfaction. We generalise these notions by allowing userdefined constraint rules. The level of programming required from the user is further abstracted by allowing experimentation with different control strategies. The resulting framework although in certain respects enhances Logic Programming with Constraints, it still is quite distinct to other approaches which are termed as Constraint Logic Programming. Here scheduling is used as a means for illustrating the framework's potentialities. Our choice is based on the abundance with which disjunctive information occur in the particular area. Schedule : akin to Greek oeØ"i ffl', to split. Chapter 1 Introduction Our embarking point for this intellectu...
The Performance of Constraint Programming for Offline Scheduling of Distributed RealTime Systems
, 2002
"... Many realtime systems are distributed in the sense that they consist of tasks that execute on dierent nodes. As a consequence of the distribution, additional task constraints concerning communication and resource sharing are imposed to the traditional timing constraints. Unfortunately, these constr ..."
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Many realtime systems are distributed in the sense that they consist of tasks that execute on dierent nodes. As a consequence of the distribution, additional task constraints concerning communication and resource sharing are imposed to the traditional timing constraints. Unfortunately, these constraints increase the computational complexity involved in nding a feasible distributed schedule for the tasks, making an oline approach to the scheduling problem the only viable alternative. Oline analysis is also required if the constraints must be guaranteed to always hold and if the distributed schedule should be optimal regarding some objective. Stateoftheart scheduling algorithms for these kind of systems include the application of techniques such as branchandbound and simulated annealing. In this paper, we present a scheduling algorithm based on constraint programming which is a technique that originates from the area of arti cial intelligence. To demonstrate its usefulness for the scheduling of distributed realtime systems, we compare the performance of our algorithm with previously proposed algorithms through a number of experiments. The results from our evaluation show that the constraint programming approach not only results in faster average runtimes but also produces more and better solutions in terms of optimality.
Identi cation of ComplexityReduction Techniques for Optimal Scheduling in Embedded Distributed RealTime Systems
, 1999
"... The application of optimal search strategies to scheduling for distributed realtime systems is, in general, plagued by an inherent computational complexity. This has e ectively prevented the integration of search strategies such as branchandbound [1] in scheduling frameworks and tools used in pra ..."
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The application of optimal search strategies to scheduling for distributed realtime systems is, in general, plagued by an inherent computational complexity. This has e ectively prevented the integration of search strategies such as branchandbound [1] in scheduling frameworks and tools used in practice today. The integration of an optimal scheduling strategy could lead to, for example, higher application schedulability, better utilization of scarce resources, or higher system reliability, than can be attained for a suboptimal scheduling technique. Inspired by recent research results, this ARTES project aims at demonstrating that optimal scheduling is, in fact, a viable alternative for many realtime scheduling scenarios. Our approach is based on the hypothesis that, with detailed knowledge about the realtime application and its characteristics, it is possible to make intelligent choices in the con guration of the search algorithm in such a way that the time it takes to generate an optimal assignment of tasks to system resources is reduced to a tractable value.
Grid BranchandBound for Permutation Flowshop
"... Abstract. Flowshop is an example of a classic hard combinatorial problem. Branchandbound is a technique commonly used for solving such hard problems. Together, the two can be used as a benchmark of maturity of parallel processing environment. Grid systems pose a number of hurdles which must be ove ..."
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Abstract. Flowshop is an example of a classic hard combinatorial problem. Branchandbound is a technique commonly used for solving such hard problems. Together, the two can be used as a benchmark of maturity of parallel processing environment. Grid systems pose a number of hurdles which must be overcome in practical applications. We give a report on applying parallel branchandbound for flowshop in grid environment. Methods dealing with the complexities of the environment and the application are proposed, and evaluated.