%0 Conference Paper %1 WG2006DGPFc %A Weise, Thomas %A Geihs, Kurt %B Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Application, BIOMA 2006 %C Jozef Stefan International Postgraduate School, Ljubljana, Slovenia %D 2006 %E Filipic, Bogdan %E Silc, Jurij %I Jozef Stefan Institute %K Algorithms, DGPF, Genetic Network, Node Programming, Sensor %P 157--166 %T DGPF -- An Adaptable Framework for Distributed Multi-Objective Search Algorithms Applied to the Genetic Programming of Sensor Networks %U http://www.it-weise.de/documents/files/WG2006DGPFc.pdf %X We present DGPF, a framework providing multi-objective, auto-adaptive search algorithms with a focus on Genetic Programming. We first introduce a Common Search API, suitable to explore arbitrary problem spaces with different search algorithms. Using our implementation of Genetic Algorithms as an example, we elaborate on the distribution utilities of the framework which enable local, Master/Slave, Peer-To-Peer, and P2P/MS hybrid distributed search execution. We also discuss how heterogeneous searches consisting of multiple, cooperative search algorithms can be constructed. Sensor networks are distributed systems of nodes with scarce resources. We demonstrate how Genetic Programming based on our framework can be applied to create algorithms for sensor nodes that use these resources very efficiently.

@inproceedings{WG2006DGPFc, abstract = {We present DGPF, a framework providing multi-objective, auto-adaptive search algorithms with a focus on Genetic Programming. We first introduce a Common Search API, suitable to explore arbitrary problem spaces with different search algorithms. Using our implementation of Genetic Algorithms as an example, we elaborate on the distribution utilities of the framework which enable local, Master/Slave, Peer-To-Peer, and P2P/MS hybrid distributed search execution. We also discuss how heterogeneous searches consisting of multiple, cooperative search algorithms can be constructed. Sensor networks are distributed systems of nodes with scarce resources. We demonstrate how Genetic Programming based on our framework can be applied to create algorithms for sensor nodes that use these resources very efficiently.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Jo{\v{z}}ef Stefan International Postgraduate School, Ljubljana, Slovenia}, affiliation = {University of Kassel, FB-16, Distributed Systems Group, Wilhelmsh{\"o}her Allee 73, 34121 Kassel, Germany}, author = {Weise, Thomas and Geihs, Kurt}, biburl = {https://www.bibsonomy.org/bibtex/238c8f2341935f659a51cfb87a735dce8/brazovayeye}, booktitle = {Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Application, BIOMA 2006}, copyright = {unrestricted}, editor = {Filipi{\v{c}}, Bogdan and {\v{S}}ilc, Jurij}, interhash = {bc851fef2750bb08f37ab28d44fe8e98}, intrahash = {38c8f2341935f659a51cfb87a735dce8}, isbn13 = {978-961-6303-81-1}, keywords = {Algorithms, DGPF, Genetic Network, Node Programming, Sensor}, language = {en}, month = {9-10 October}, pages = {157--166}, publisher = {Jo{\v{z}}ef Stefan Institute}, timestamp = {2008-06-19T17:53:59.000+0200}, title = {{DGPF} -- An Adaptable Framework for Distributed Multi-Objective Search Algorithms Applied to the Genetic Programming of Sensor Networks}, type = {Research Talk Paper}, url = {http://www.it-weise.de/documents/files/WG2006DGPFc.pdf}, year = 2006 }