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Proximity detection in distributed simulation of wireless mobile systems
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Source International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems table of contents
Terromolinos, Spain
SESSION: Methodologies and tools table of contents
Pages: 44 - 51  
Year of Publication: 2006
ISBN:1-59593-477-4
Authors
Luciano Bononi  Università degli Studi di Bologna, Bologna, Italy
Michele Bracuto  Università degli Studi di Bologna, Bologna, Italy
Gabriele D'Angelo  Università degli Studi di Bologna, Bologna, Italy
Lorenzo Donatiello  Università degli Studi di Bologna, Bologna, Italy
Sponsors
SIGSIM: ACM Special Interest Group on Simulation and Modeling
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The distributed and the Grid Computing architectures for the simulation of massively populated wireless systems have recently been considered of interest, mainly for cost reasons. Solutions for generalized proximity detection for mobile objects is a relevant problem, with a big impact on the design and the implementation of parallel and distributed simulations of wireless mobile systems. In this paper, a set of solutions based on tailored data structures, new techniques and enhancements of the existing algorithms for generalized proximity detection are proposed and analyzed, to increase the efficiency of distributed simulations. The paper includes the analysis of computation complexity of the proposed solutions and the performance evaluation of a testbed distributed simulation of ad hoc network models. Recent works have shown that the performance of distributed simulation of dynamic complex systems could benefit from a runtime migration mechanism of model entities, which reduces the communication overheads. Such migration mechanisms may interfere with the generalized proximity detection implementations. The analysis performed in this paper illustrates the effects of many possible compositions of the proposed solutions, in a real testbed simulation framework.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Luciano Bononi: colleagues
Michele Bracuto: colleagues
Gabriele D'Angelo: colleagues
Lorenzo Donatiello: colleagues