Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades
F. Dressler, I. Dietrich, R. German, B. Krueger, in: 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007), Association for Computing Machinery (ACM), Rome, Italy, 2007.
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Author
Dressler, Falko;
Dietrich, Isabel;
German, Reinhard;
Krueger, BettinaLibreCat
Abstract
The investigation and the development of self-organizing systems are especially needed for operation and control in massively distributed systems such as Sensor and Actor Networks (SANETs). The main issues addressed by self-organization techniques are scalability, network lifetime, and real-time support. In the literature, biological principles are often cited as inspirations for technical solutions, especially in the domain of self-organization. This concept already resulted in a good number of solutions with significant impact such as ant-based routing and immune system inspired network security solutions. In this paper, another specific biological field is investigated: cellular signaling cascades for event-specific reaction initiated by individual cells in collaboration with their direct neighbors. Information between cells are transmitted via proteins and result in the cascade of protein–protein or protein–DNA interactions to produce a specific cellular answer, e.g. the activation of cells or the transmission of mediators. These processes are programmed in every individual cell and lead to a coordinated reaction on a higher organization platform. We transferred these mechanisms to operation and control in SANETs. In particular, a rule-based processing scheme relying on the main concepts of cellular signaling cascades has been developed. It is relying on simple local rules and providing problem specific reaction such as local actuation control and data manipulation. We describe this Rule-based Sensor Network (RSN) technology and demonstrate comparative simulation results that show the feasibility of our approach.
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1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007)
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Dressler F, Dietrich I, German R, Krueger B. Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades. In: 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007). Association for Computing Machinery (ACM); 2007. doi:10.1145/1365562.1365572
Dressler, F., Dietrich, I., German, R., & Krueger, B. (2007). Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades. 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007). https://doi.org/10.1145/1365562.1365572
@inproceedings{Dressler_Dietrich_German_Krueger_2007, place={Rome, Italy}, title={Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades}, DOI={10.1145/1365562.1365572}, booktitle={1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007)}, publisher={Association for Computing Machinery (ACM)}, author={Dressler, Falko and Dietrich, Isabel and German, Reinhard and Krueger, Bettina}, year={2007} }
Dressler, Falko, Isabel Dietrich, Reinhard German, and Bettina Krueger. “Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades.” In 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007). Rome, Italy: Association for Computing Machinery (ACM), 2007. https://doi.org/10.1145/1365562.1365572.
F. Dressler, I. Dietrich, R. German, and B. Krueger, “Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades,” 2007, doi: 10.1145/1365562.1365572.
Dressler, Falko, et al. “Efficient Operation in Sensor and Actor Networks Inspired by Cellular Signaling Cascades.” 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007), Association for Computing Machinery (ACM), 2007, doi:10.1145/1365562.1365572.