Overhearing the Wireless Interface for 802.11-based Positioning Systems

Not only the proliferation of 802.11, but also the capability to determine the position of mobile devices make 802.11 highly appealing for many application areas. Typically, a mobile device that wants to know its position regularly performs active or passive scans to obtain the signal strength measurements of neighboring access points. Active and passive scanning are survey techniques originally intended to be performed once in a while to learn about the presence and signal reception quality of access points within communication range. Based on this survey the best suitable access point is selected as the gateway to the wired network. However, so far, no investigations are known to have been launched into how regular scanning affects concurrent data transmissions from an end-user point of view. In this paper, we explore how common data communication is affected while actively or passively scanning at the same time. We found that with an active scanning interval of less than 2 seconds the network conditions such as throughput and round trip delay are insufficient for interactive applications. The same is true for passive scanning if a scanning interval of less than 7 seconds is chosen. Furthermore, we present a novel scan scheme called Monitor Sniffing to reduce client service disruptions. Monitor Sniffing exploits the fact that 802.11 operates on overlapping channels by overhearing the wireless interface. We have implemented our Monitor Sniffing algorithm using commodity 802.11g hardware, and we demonstrate that it is faster than active and passive scanning and does not disturb concurrent data communication. Finally, our approach only requires software modifications on the client side, making the adoption process quite easy

Load-aware Channel Selection for 802.11 WLANs with Limited Measurement

It has been known that load unaware channel selection in 802.11 networks results in high level interference, and can significantly reduce the network throughput. In current implementation, the only way to determine the traffic load on a channel is to measure that channel for a certain duration of time. Therefore, in order to find the best channel with the minimum load all channels have to be measured, which is costly and can cause unacceptable communication interruptions between the AP and the stations. In this paper, we propose a learning based approach which aims to find the channel with the minimum load by measuring only limited number of channels. Our method uses Gaussian Process Regressing to accurately track the traffic load on each channel based on the previous measured load. We confirm the performance of our algorithm by using experimental data, and show that the time consumed for the load measurement can be reduced up to 46% compared to the case where all channels are monitored.Comment: accepted to IC

IoT-Based Smart Management of Healthcare Services in Hospital Buildings during COVID-19 and Future Pandemics

The paper aims to design and develop an innovative solution in the Smart Building context that increases guests' hospitality level during the COVID-19 and future pandemics in locations like hotels, conference locations, campuses, and hospitals. The solution supports features intending to control the number of occupants by online appointments, smart navigation, and queue management in the building through mobile phones and navigation to the desired location by highlighting interests and facilities. Moreover, checking the space occupancy, and automatic adjustment of the environmental features are the abilities that can be added to the proposed design in the future development. The proposed solution can address all mentioned issues regarding the smart building by integrating and utilizing various data sources collected by the internet of things (IoT) sensors. Then, storing and processing collected data in servers and finally sending the desired information to the end-users. Consequently, through the integration of multiple IoT technologies, a unique platform with minimal hardware usage and maximum adaptability for smart management of general and healthcare services in hospital buildings will be created

A heterogeneous short-range communication platform for internet of vehicles

The automotive industry is rapidly accelerating toward the development of innovative industry applications that feature management capabilities for data and applications alike in cars. In this regard, more internet of vehicles solutions are emerging through advancements of various wireless medium access-control technologies and the internet of things. In the present work, we develop a short-range communication–based vehicular system to support vehicle communication and remote car control. We present a combined hardware and software testbed that is capable of controlling a vehicle’s start-up, operation and several related functionalities covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino and Raspberry Pi 3, each of which individually controls certain functions to improve the overall vehicle control. The implementation of the heterogeneous communication module is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 and IEEE 802.15 medium access control technologies. Further, a control module on a smartphone was designed and implemented for efficient management. Moreover, we study the system connectivity performance by measuring various important parameters including the coverage distance, signal strength, download speed and latency. This study covers the use of this technology setup in different geographical areas over various time spans

WLAN-paikannuksen elinkaaren tukeminen

The advent of GPS positioning at the turn of the millennium provided consumers with worldwide access to outdoor location information. For the purposes of indoor positioning, however, the GPS signal rarely penetrates buildings well enough to maintain the same level of positioning granularity as outdoors. Arriving around the same time, wireless local area networks (WLAN) have gained widespread support both in terms of infrastructure deployments and client proliferation. A promising approach to bridge the location context then has been positioning based on WLAN signals. In addition to being readily available in most environments needing support for location information, the adoption of a WLAN positioning system is financially low-cost compared to dedicated infrastructure approaches, partly due to operating on an unlicensed frequency band. Furthermore, the accuracy provided by this approach is enough for a wide range of location-based services, such as navigation and location-aware advertisements. In spite of this attractive proposition and extensive research in both academia and industry, WLAN positioning has yet to become the de facto choice for indoor positioning. This is despite over 20 000 publications and the foundation of several companies. The main reasons for this include: (i) the cost of deployment, and re-deployment, which is often significant, if not prohibitive, in terms of work hours; (ii) the complex propagation of the wireless signal, which -- through interaction with the environment -- renders it inherently stochastic; (iii) the use of an unlicensed frequency band, which means the wireless medium faces fierce competition by other technologies, and even unintentional radiators, that can impair traffic in unforeseen ways and impact positioning accuracy. This thesis addresses these issues by developing novel solutions for reducing the effort of deployment, including optimizing the indoor location topology for the use of WLAN positioning, as well as automatically detecting sources of cross-technology interference. These contributions pave the way for WLAN positioning to become as ubiquitous as the underlying technology.GPS-paikannus avattiin julkiseen käyttöön vuosituhannen vaihteessa, jonka jälkeen sitä on voinut käyttää sijainnin paikantamiseen ulkotiloissa kaikkialla maailmassa. Sisätiloissa GPS-signaali kuitenkin harvoin läpäisee rakennuksia kyllin hyvin voidakseen tarjota vastaavaa paikannustarkkuutta. Langattomat lähiverkot (WLAN), mukaan lukien tukiasemat ja käyttölaitteet, yleistyivät nopeasti samoihin aikoihin. Näiden verkkojen signaalien käyttö on siksi alusta asti tarjonnut lupaavia mahdollisuuksia sisätilapaikannukseen. Useimmissa ympäristöissä on jo valmiit WLAN-verkot, joten paikannuksen käyttöönotto on edullista verrattuna järjestelmiin, jotka vaativat erillisen laitteiston. Tämä johtuu osittain lisenssivapaasta taajuusalueesta, joka mahdollistaa kohtuuhintaiset päätelaitteet. WLAN-paikannuksen tarjoama tarkkuus on lisäksi riittävä monille sijaintipohjaisille palveluille, kuten suunnistamiselle ja paikkatietoisille mainoksille. Näistä lupaavista alkuasetelmista ja laajasta tutkimuksesta huolimatta WLAN-paikannus ei ole kuitenkaan pystynyt lunastamaan paikkaansa pääasiallisena sisätilapaikannusmenetelmänä. Vaivannäöstä ei ole puutetta; vuosien saatossa on julkaistu yli 20 000 tieteellistä artikkelia sekä perustettu useita yrityksiä. Syitä tähän kehitykseen on useita. Ensinnäkin, paikannuksen pystyttäminen ja ylläpito vaativat aikaa ja vaivaa. Toiseksi, langattoman signaalin eteneminen ja vuorovaikutus ympäristön kanssa on hyvin monimutkaista, mikä tekee mallintamisesta vaikeaa. Kolmanneksi, eri teknologiat ja laitteet kilpailevat lisenssivapaan taajuusalueen käytöstä, mikä johtaa satunnaisiin paikannustarkkuuteen vaikuttaviin tietoliikennehäiriöihin. Väitöskirja esittelee uusia menetelmiä joilla voidaan merkittävästi pienentää paikannusjärjestelmän asennuskustannuksia, jakaa ympäristö automaattisesti osiin WLAN-paikannusta varten, sekä tunnistaa mahdolliset langattomat häiriölähteet. Nämä kehitysaskeleet edesauttavat WLAN-paikannuksen yleistymistä jokapäiväiseen käyttöön