- author = "Ling Zhu and Sandeep S. Kulkarni",
- booktitle = "35th IEEE International Conference on Distributed Computing Systems Workshops",
- title = "Using Genetic Programming to Identify Tradeoffs in Self-Stabilizing Programs: A Case Study",
- year = "2015",
- pages = "29--34",
- abstract = "We focus on the use of genetic programming to identify trade-offs between closure and convergence properties of a stabilizing program. Closure property characterises the behaviour in the absence of faults whereas convergence property characterises the recovery from an arbitrary state to a legitimate state. We describe how genetic programming (GP) can be applied to identify a trade-off for the behaviours in the absence of faults and in the presence of faults. This approach uses BDD (Binary Decision Diagram) based techniques. Subsequently, we use two objectives: closure and maximum convergence time and use NSGA-II (a multi-objective optimisation algorithm) to identify the trade-off between the performances. We use the classic K-state token ring program to illustrate the trade-off and run experiments for three different approaches: (1) where we only consider trade-off based on process 0, (2) where only consider trade-off based on non-zero processes, and (3) where we consider both trade-offs. Several interesting results are found such as, special process (marked N - 3 in the K-state program) plays a critical role in providing the trade-off, while process 1 is the least important.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/ICDCSW.2015.17",
- ISSN = "1545-0678",
- month = jun,
-
notes = "Dept. of Comput. Sci. & Eng., Michigan State Univ.,
East Lansing, MI, USA
Also known as \cite{7165080}",
