International audienceIEEE 802.11 networks are the most popular option to have wireless access to the Internet. The popularity of these networks have raised a costly topology discovery and connection process, in which any device has to pass through an expensive scanning process of available Access Points. In order to improve the connection process, we propose a novel architecture for asynchronous assistance for topology discovery. We discuss the role of a Topology Manager that uses computational intelligence for generating optimal scanning sequences. Preliminary results show that this approach results in 30% to 70% improvements on AP discovery rate in chaotic deployments
International audienceToday WiFi networks are widely deployed all over the world, with high Access Point (AP) density in urban areas. Both end-users and network operators are trying to exploit this density by combining multiple APs into "community networks," in order to share Internet connectivity, and possibly other services. WiFi networks suffer from decentralized management and a lack of coordination in frequency allocation and power control. In order to better use and configure these uncoordinated deployments, the first step is to characterize them. This paper presents a collaborative platform, where mobile stations collect simple network measurements (e.g., the presence of an AP) and send these measurements to a central system. By gathering and processing several network measurements from different mobile users, the platform characterizes the network deployment. This paper presents two applications: 1) minimal AP set, to reduce the energy needed to provide WiFi coverage in a given area, and 2) optimal scanning parameters, to minimize the time a mobile station needs for the network discovery. These two applications show the system's viability to solve particular problems of community networks
No abstract
International audienceEvery day large number of users connect to IEEE 802.11 networks in order to access the Internet and all sort of services. But, due to their unplanned and unregulated nature, and to the lack of admission control and Quality of Service Guarantees, these wireless networks can be confronted to a traffic demand that can exceed the network capacity. In this case, if a device tries to send more traffic, or if a new device joins the network, the aggregate throughput does not necessarily increase. In this paper we show that it is possible for IEEE 802.11 Stations to detect a saturated channel by passively monitoring the beacon frames. Access Points send beacon frames periodically and encode them using the strongest modulation and coding scheme, so that even stations further away from the sending Access Points can decode them correctly. When sending beacons, Access Points sense the channel first and, if it is busy, delay sending the frame, resulting in unevenly spaced beacon frames, whenever other transmitters are active. We present several experiments, under varying traffic loads, and analyze the distribution of the beacon jitter, whose variance increases as the offered load increases. We show that it is possible to determine, with an acceptable error rate, whether a channel is saturated by comparing the distribution of the beacon jitter with a reference distribution corresponding to a saturated channel
The Bluetooth Low Energy (BLE) networks use three channels to broadcast advertisements. These advertisements and other BLE frames are subject to collisions. The collision probability increases as the number of devices increases. Nonetheless, because of the capture effect, receivers may correctly decode some of the frames involved in a collision. Recent studies proposed models and simulations for the BLE discovery process, showing the impact of the advertisement collisions as well as the importance of an appropriate selection of the parameters related to the discovery process. The impact of the capture effect in these studies is unclear. Here we report the impact of the capture effect on the BLE advertisements. In particular, we show that the capture effect systematically increases the advertisement reception rate. We establish upper and lower bounds to quantify the contribution of the capture effect to the packet delivery ratio in dense scenarios. We make measurements in a controlled environment (a Faraday box) to show the presence of the capture effect in networks with 2 to 14 advertisers. Empirical results show that for 14 devices the capture effect increases the advertisement delivery rate by 2.95 % on average, with a peak of 7.8 %. Using simulations to recreate dense scenarios (up to 1000 advertisers) we show that the capture effect can increase the packet delivery ratio by up to 25 %. Our results have implications in the performance analysis of the discovery process and provide insights for the design of BLE applications and protocols that leverage on BLE advertisements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.