%0 Conference Paper %1 WGB2007DGPFb %A Weise, Thomas %A Geihs, Kurt %A Baer, Philipp Andreas %B Proceedings of Adaptive and Natural Computing Algorithms, 8th International Conference, ICANNGA 2007, Part I %C Warsaw University of Technology, Warsaw, Poland %D 2007 %E Beliczyński, Bartłomiej %E Dzieliński, Andrzej %E Iwanowski, Marcin %E Ribeiro, Bernardete %I Springer Berlin Heidelberg New York %K Aggregation Aggregation, DGPF, Networks, Proactive Protocols, Regression Sensor Symbolic algorithms, genetic programming, %P 167--173 %R doi:10.1007/978-3-540-71618-1 %T Genetic Programming for Proactive Aggregation Protocols %U http://www.springerlink.com/content/978-3-540-71589-4/?p_o=10 %V 4431 %X We present an approach for automated generation of proactive aggregation protocols using Genetic Programming. First a short introduction into aggregation and proactive protocols is given. We then show how proactive aggregation protocols can be specified abstractly. To be able to use Genetic Programming to derive such protocol specifications, we describe a simulation based fitness assignment method. We have applied our approach successfully to the derivation of aggregation protocols. Experimental results are presented that were obtained using our own Distributed Genetic Programming Framework. The results are very encouraging and demonstrate clearly the utility of our approach.

@inproceedings{WGB2007DGPFb, abstract = {We present an approach for automated generation of proactive aggregation protocols using Genetic Programming. First a short introduction into aggregation and proactive protocols is given. We then show how proactive aggregation protocols can be specified abstractly. To be able to use Genetic Programming to derive such protocol specifications, we describe a simulation based fitness assignment method. We have applied our approach successfully to the derivation of aggregation protocols. Experimental results are presented that were obtained using our own Distributed Genetic Programming Framework. The results are very encouraging and demonstrate clearly the utility of our approach.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Warsaw University of Technology, Warsaw, Poland}, affiliation = {University of Kassel, FB-16, Distributed Systems Group, Wilhelmsh{\"o}her Allee 73, 34121 Kassel, Germany}, author = {Weise, Thomas and Geihs, Kurt and Baer, Philipp Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2191725b4c777da005d4d66161e65ecd1/brazovayeye}, booktitle = {Proceedings of Adaptive and Natural Computing Algorithms, 8th International Conference, ICANNGA 2007, Part I}, contents = {We present an approach for automated generation of proactive aggregation protocols using Genetic Programming. First a short introduction into aggregation and proactive protocols is given. We then show how proactive aggregation protocols can be specified abstractly. To be able to use Genetic Programming to derive such protocol specifications, we describe a simulation based fitness assignment method. We have applied our approach successfully to the derivation of aggregation protocols. Experimental results are presented that were obtained using our own Distributed Genetic Programming Framework. The results are very encouraging and demonstrate clearly the utility of our approach.}, copyright = {restricted}, doi = {doi:10.1007/978-3-540-71618-1}, editor = {Beliczy{\'n}ski, Bart{\l}omiej and Dzieli{\'n}ski, Andrzej and Iwanowski, Marcin and Ribeiro, Bernardete}, interhash = {9a28c975178e5ee0eef4b358924c1aec}, intrahash = {191725b4c777da005d4d66161e65ecd1}, isbn13 = {978-3-540-71589-4}, issn = {0302-9743}, keywords = {Aggregation Aggregation, DGPF, Networks, Proactive Protocols, Regression Sensor Symbolic algorithms, genetic programming,}, language = {en}, month = {April~11-14,}, note = {see http://icannga07.ee.pw.edu.pl/ and http://www.springerlink.com/content/978-3-540-71590-0/}, pages = {167--173}, publisher = {Springer Berlin Heidelberg New York}, series = {Lecture Notes in Computer Science}, timestamp = {2008-06-19T17:54:00.000+0200}, title = {Genetic Programming for Proactive Aggregation Protocols}, type = {Conference Paper}, url = {http://www.springerlink.com/content/978-3-540-71589-4/?p_o=10}, volume = 4431, year = 2007 }