Two-stage wireless network emulation

Testing and deploying mobile wireless networks and applications are very challenging tasks, due to the network size and administration as well as node mobility management. Well known simulation tools provide a more flexible environment but they do not run in real time and they rely on models of the developed system rather than on the system itself. Emulation is a hybrid approach allowing real application and traffic to be run over a simulated network, at the expense of accuracy when the number of nodes is too important. In this paper, emulation is split in two stages : first, the simulation of network conditions is precomputed so that it does not undergo real-time constraints that decrease its accuracy ; second, real applications and traffic are run on an emulation platform where the precomputed events are scheduled in soft real-time. This allows the use of accurate models for node mobility, radio signal propagation and communication stacks. An example shows that a simple situation can be simply tested with real applications and traffic while relying on accurate models. The consistency between the simulation results and the emulated conditions is also illustrated

A feedback based solution to emulate hidden terminals in wireless networks

Mobile wireless emulation allows the test of real applications and transport protocols over a wired network mimicking the behavior of a mobile wireless network (nodes mobility, radio signal propagation and specific communication protocols). Two-stage IP-level network emulation consists in using a dedicated offline simulation stage to compute an IPlevel emulation scenario, which is played subsequently in the emulation stage. While this type of emulation allows the use of accurate computation models together with a large number of nodes, it currently does not allow to deal with dynamic changes of the real traffic. This lack of reactivity makes it impossible to emulate specific wireless behaviors such as hidden terminals in a realistic way. In this paper we address the need to take into account the real traffic during the emulation stage and we introduce a feedback mechanism. During the simulation several emulation scenarios are computed, each scenario corresponding to alternative traffic conditions related to e.g. occurrence or not of hidden terminals. During the emulation stage, the traffic is observed and the currently played emulation scenario can be changed according to specific network conditions. We propose a solution based on multiple scenarios generation, traffic observers and a feedback mechanism to add a trafficbased dynamic behavior to a two-stage emulation platform. The solution will be illustrated with a simple experiment based on hidden terminals

Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed

Cloud Radio Access Network (C-RAN) is emerging as a transformative architecture for the next generation of mobile cellular networks. In C-RAN, the Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in a centralized processing center. While the potential benefits of C-RAN have been studied extensively from the theoretical perspective, there are only a few works that address the system implementation issues and characterize the computational requirements of the virtualized BBU. In this paper, a programmable C-RAN testbed is presented where the BBU is virtualized using the OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment (UEs) are implemented using USRP boards. Extensive experiments have been performed in a FDD downlink LTE emulation system to characterize the performance and computing resource consumption of the BBU under various conditions. It is shown that the processing time and CPU utilization of the BBU increase with the channel resources and with the Modulation and Coding Scheme (MCS) index, and that the CPU utilization percentage can be well approximated as a linear increasing function of the maximum downlink data rate. These results provide real-world insights into the characteristics of the BBU in terms of computing resource and power consumption, which may serve as inputs for the design of efficient resource-provisioning and allocation strategies in C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC), July 201