Documents

@conference{WG2006DGPFc,
  author        = {Thomas Weise, Kurt Geihs},
  title         = {DGPF - An Adaptable Framework for Distributed Multi-Objective
                   Search Algorithms Applied to the Genetic Programming of Sensor
                   Networks},
  month         = {Oct},
  year          = {2006},
  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.},
  keywords      = {Genetic Programming, Genetic Algorithms, DGPF, Sensor Network, Sensor Node},
  URL           = {http://dgpf.sourceforge.net/documents/013-2006-10-10-bioma_paper},
  pages         = {157--166},
  type          = {Resaerch Talk Paper},
  affiliation   = {University of Kassel,
                  Distributed Systems Group},
  location      = {Jo\v{z}ef Stefan Institute, Ljubljana, Slovenia},
  language      = {en},
  rights        = {unrestricted},
  booktitle     = {Proceedings of the Second International Conference on Bioinspired Optimization
                   Methods and their Application, BIOMA 2006},
  ISBN          = {ISBN-10: 961-6303-81-3, ISBN 13: 978-961-6303-81-1},
  editor        = {Bogdan Filipi\v{c} and Jurij \v{S}ilc},
  publisher     = {Jo\v{z}ef Stefan Institute, Ljubljana, Slovenia},
  series        = {International Conference on Bioinspired Optimization Methods and
                   their Application (BIOMA)}
}

@proceedings{WG2006DGPFb,
  author        = {Thomas Weise, Kurt Geihs},
  title         = {Genetic Programming Techniques for Sensor Networks},
  month         = {Jul},
  number        = {5},
  year          = {2006},
  abstract      = {In this paper we present an approach to automated program code generation
                   for sensor nodes and other small devices. Using Genetic Programming, we
                   are able to discover algorithms that solve certain problems. Furthermore,
                   non-functional properties like code size, memory usage, and communication
                   frequency can be optimized using multiobjective search techniques. The
                   evolution of algorithms requires program testing, which we perform using
                   a customized simulation environment for sensor networks. The simulation
                   model takes into account characteristic features of sensor nodes, such as
                   unreliable communication and resource constraints. An application example
                   is presented that demonstrates the feasibility of our approach and its
                   potential to create robust and adaptive code for sensor network
                   applications.},
  keywords      = {Genetic Programming, Genetic Algorithms, DGPF, Sensor Network, Sensor Node},
  URL           = {http://dgpf.sourceforge.net/documents/006-2006-07-17-kuvs_paper.pdf},
  pages         = {21-25},
  type          = {Resaerch Talk Paper},
  affiliation   = {University of Kassel,
                  Distributed Systems Group},
  location      = {Universit of Stuttgart},
  language      = {en},
  rights        = {unrestricted},
  booktitle     = {Proceedings of 5. GI/ITG KuVS Fachgespräch \"Drahtlose Sensornetze\"}
}

@unpublished{W2006DGPFa,
  author        = {Thomas Weise},
  title         = {Genetic Programming for Sensor Networks},
  month         = {Jan},
  year          = {2006},
  abstract      = {In this paper we present an approach to automated program code generation
                   for sensor nodes and other small devices using Genetic Programming. We give
                   a short introduction to Genetic Algorithms. Our new Distributed Genetic
                   Programming Framework facilitates the development of sensor network
                   applications. Genetic evolution of programs requires program testing.
                   Therefore we use a simulation environment for distributed systems of sensor
                   nodes. The simulation model takes into account characteristic features of
                   sensor nodes, such as unreliable communication and resource constraints.
                   Two application examples are presented that demonstrate the feasibility of
                   our approach and its potential to create robust and adaptive code for sensor
                   network applications.},
  keywords      = {Genetic Programming, Genetic Algorithms, DGPF, Sensor Network, Sensor Node},
  URL           = {http://dgpf.sourceforge.net/documents/001-2006-01-20-paper.pdf},
  affiliation   = {University of Kassel,
                  Distributed Systems Group},
  language      = {en},
  rights        = {unrestricted},
  }