基于遗传算法的多用户并发映射器
Genetic Algorithm-based Mapper to Support Multiple Concurrent Users on Wireless Testbeds
摘要：
通信和网络研究引入了新的协议和标准，越来越多的研究人员依靠真实实验而不是模拟来评估新协议的性能。目前有一些测试平台可用于此目的，越来越多的用户正在请求访问这些测试平台。这激发了通过允许并行实验来更好地利用测试台的需要。在这项工作中，我们介绍了一种新的映射算法，旨在最大限度地利用无线测试平台的频谱资源的频率切片。映射器采用遗传算法，以找到最佳的组合，可以并发服务的请求，通过一个诱导子图同构阶段得到所有可能的映射后，每个请求。建议的映射器进行了测试网格测试床和随机生成的拓扑结构。我们的映射器的解决方案相比，最佳的，通过暴力搜索，并能够在82.96%的测试场景中提供相同数量的请求。此外，我们展示了精心设计的测试床拓扑结构的效果，通过将我们的映射器应用于精心定位的8节点测试床，提高了测试床的利用率。此外，我们提出的测试床切片和请求映射方法在总服务请求方面表现出了改进的性能，与没有切片的简单分配策略相比，大约提高了五倍。
英文摘要：
Communication and networking research introduces new protocols and standards with an increasing number of researchers relying on real experiments rather than simulations to evaluate the performance of their new protocols. A number of testbeds are currently available for this purpose and a growing number of users are requesting access to those testbeds. This motivates the need for better utilization of the testbeds by allowing concurrent experimentations. In this work, we introduce a novel mapping algorithm that aims to maximize wireless testbed utilization using frequency slicing of the spectrum resources. The mapper employs genetic algorithm to find the best combination of requests that can be served concurrently, after getting all possible mappings of each request via an induced sub-graph isomorphism stage. The proposed mapper is tested on grid testbeds and randomly generated topologies. The solution of our mapper is compared to the optimal one, obtained through a brute-force search, and was able to serve the same number of requests in 82.96% of testing scenarios. Furthermore, we show the effect of the careful design of testbed topology on enhancing the testbed utilization by applying our mapper on a carefully positioned 8-nodes testbed. In addition, our proposed approach for testbed slicing and requests mapping has shown an improved performance in terms of total served requests, about five folds, compared to the simple allocation policy with no slicing.
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