2007/04/10 by Minkyu Kim, Kim, Minkyu, Varun Aggarwal +5
Computer Science · Engineering · #Advanced Wireless Communication Technologies #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Full-Duplex Wireless Communications #Networking and Internet Architecture (cs.NI) #Neural and Evolutionary Computing (cs.NE)
paper · pdf · doi:10.48550/arxiv.0704.1198
openalex publication_date 2007/04/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a genetic algorithm which is distributed in two novel ways: along genotype and temporal axes. Our algorithm first distributes, for every member of the population, a subset of the genotype to each network node, rather than a subset of the population to each. This genotype distribution is shown to offer a significant gain in running time. Then, for efficient use of the computational resources in the network, our algorithm divides the candidate solutions into pipelined sets and thus the distribution is in the temporal domain, rather that in the spatial domain. This temporal distribution may lead to temporal inconsistency in selection and replacement, however our experiments yield better efficiency in terms of the time to convergence without incurring significant penalties.