BDD Path Length Minimization Based on Initial Variable Ordering

Prasad, P. W. C.; Raseen, Mohamed; Assi, Ali; Senanayake, S. M. N. Arosha

doi:10.3844/jcssp.2005.521.529

Cited by 6 publications

(4 citation statements)

References 22 publications

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“…Alternatively, the existing BDD optimization algorithms in [10] [12] [28] [31] provide us with the theoretical foundation to reduce the size of ROBDD. Furthermore, JavaBDD [13], a Java library for manipulating BDDs, is the tool we chose for setting up the BDD handling and programming environment.…”

Section: Related Workmentioning

confidence: 99%

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Structural Optimization of Reduced Ordered Binary Decision Diagrams for SLA Negotiation in IaaS of Cloud Computing

Yahyapour

Yaqub

et al. 2012

Service-Oriented Computing

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In cloud computing, an automated SLA is an electronic contract used to record the rights and obligations of service providers and customers for their services. SLA negotiation can be a time-consuming process, mainly due to the unpredictable rounds of negotiation and the complicated possible dependencies among SLAs. The operation of negotiating SLAs can be facilitated when SLAs are translated into Reduced Ordered Binary Decision Diagrams (ROBDDs). Nevertheless, an ROBDD may not be optimally structured upon production. In this paper, we show how to reduce the number of 1-paths and nodes of ROBDDs that model SLAs, using ROBDD optimization algorithms. In addition, we demonstrate the reduction of 1-paths via the application of Term Rewriting Systems with mutually exclusive features. Using the latter, ROBDDs can be generated accurately without redundant 1-paths. We apply the principles onto the negotiation of IaaS SLAs via simulation, and show that negotiation is accelerated by assessing fewer SLA proposals (1-paths), while memory consumption is also reduced.

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Section: Related Workmentioning

confidence: 99%

“…In-memory, each decision node requires an index and pointers to the succeeding nodes [28]. Since each decision node in an ROBDD has two pointers, the memory size required to represent an ROBDD is given by Eq.…”

Section: Node Optimizationmentioning

confidence: 99%

Structural Optimization of Reduced Ordered Binary Decision Diagrams for SLA Negotiation in IaaS of Cloud Computing

Yahyapour

Yaqub

et al. 2012

Service-Oriented Computing

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“…In [16] we see a technique to minimize the BDD complexity and the time of evaluation of the function based on minimum path length which is decided by initial variable order. A detailed survey of static variable ordering heuristics (such as topological, influential, priority ordering and variable weighing etc.)…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Optimization of BDDs and Performance Evaluation for Multi-level Logic Circuits with Area and Power Trade-offs

Chaudhury¹,

Dutta²

2011

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Binary Decision Diagrams (BDDs) can be graphically manipulated to reduce the number of nodes and hence the area. In this context, ordering of BDDs play a major role. Most of the algorithms for input variable ordering of OBDD focus primarily on area minimization. However, suitable input variable ordering helps in minimizing the power consumption also. In this particular work, we have proposed two algorithms namely, a genetic algorithm based technique and a branch and bound algorithm to find an optimal input variable order. Of course, the node reordering is taken care of by the standard BDD package buddy-2.4. Moreover, we have evaluated the performances of the proposed algorithms by running an exhaustive search program. Experimental results show a substantial saving in area and power. We have also compared our techniques with other state-of-art techniques of variable ordering for OBDDs and found to give superior results.

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“…In general the minimization of the path length in Decision Diagrams (DDs) is important in database structures, pattern recognition, logic simulation and software synthesis [7] . The methods proposed for the minimization of APL [7][8][9][10] reduces the average evaluation time of logic functions. Most of these methods are based on either Static variable ordering [11,12] or dynamic variable ordering techniques [13] .…”

Section: Introductionmentioning

confidence: 99%

Empirical Analysis and Mathematical Representation of the Path Length Complexity in Binary Decision Diagrams

Assi¹,

Prasad²,

Mills³

et al. 2006

J. of Computer Science

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Information about the distribution of path-lengths in a Binary Decision Diagrams (BDDs) representing Boolean functions is useful in determining the speed of hardware and software implementations of the circuit represented by these Boolean functions. This study presents expressions produced from an empirical analysis of a representative collection of Boolean functions. The Average Path Length (APL) and the Shortest Path Length (SPL) have simple behavior as function of the number of variables and the number of terms used in the construction of the Sum of Products (SOPs) in Boolean expressions. We present a generic expression that is uniformly adaptable to each curve of path-length versus number of terms over all the empirical data. This expression makes it possible to estimate the performance characteristics of a circuit without building its BDD. This approach applies to any number of variables, number of terms, or variable ordering method.

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BDD Path Length Minimization Based on Initial Variable Ordering

Cited by 6 publications

References 22 publications

Structural Optimization of Reduced Ordered Binary Decision Diagrams for SLA Negotiation in IaaS of Cloud Computing

Structural Optimization of Reduced Ordered Binary Decision Diagrams for SLA Negotiation in IaaS of Cloud Computing

Algorithmic Optimization of BDDs and Performance Evaluation for Multi-level Logic Circuits with Area and Power Trade-offs

Empirical Analysis and Mathematical Representation of the Path Length Complexity in Binary Decision Diagrams

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