Partitioning bin-packing algorithms for distributed real-time systems

Partitioning bin-packing algorithms for distributed real-time systems

Embedded real-time systems must satisfy not only logical functional requirements but also para-functional properties such as timeliness, Quality of Service (QoS) and reliability. We have developed a model-based tool called Time Weaver which enables the modeling of functional and para-functional behaviors of real-time systems. It also performs automated schedulability analysis, and generates glu...

Linear time-approximation algorithms for bin packing

Simchi-Levi (Naval Res. Logist. 41 (1994) 579–585) proved that the famous bin packing algorithms FF and BF have an absolute worst-case ratio of no more than 4 , and FFD and BFD have an absolute worst-case ratio of 3 2 , respectively. These algorithms run in time O(n log n). In this paper, we provide a linear time constant space (number of bins kept during the execution of the algorithm is const...

Improved Bin Completion for Optimal Bin Packing and Number Partitioning

The bin-packing problem is to partition a multiset of n numbers into as few bins of capacity C as possible, such that the sum of the numbers in each bin does not exceed C. We compare two existing algorithms for solving this problem: bin completion (BC) and branch-and-cut-and-price (BCP). We show experimentally that the problem difficulty and dominant algorithm are a function of n, the precision...

An Evaluation of Bin-Packing Algorithms Using Real Program Traces

Parallel Approximation Algorithms for Bin Packing

We study the parallel complexity of polynomial heuristics for the bin packing problem. We show that some well-known (and simple) methods like first-fit-decreasing are P-complete, and it is hence very unlikely that they can be efficiently parallelized. On the other hand, we exhibit an optimal NC algorithm that achieves the same performance bound as does FFD. Finally, we discuss parallelization o...