Gergely V. Záruba

Bluetrees-scatternet formation to enable Bluetooth-based ad hoc networks

Bluetooth is an open specification for short-range wireless communication and networking, mainly intended to be a cable replacement between portable and/or fixed electronic devices. The specification also defines techniques for interconnecting large number of nodes in scatternets, thus enabling the establishment of a mobile ad hoc network (MANET). While several solutions and commercial products have been introduced for one-hop Bluetooth communication, the problem of scatternet formation has not yet been dealt with. This problem concerns the assignment of the roles of master and slave to each node so that the resulting MANET is connected. We introduce two novel protocols for forming connected scatternets. In both cases, the resulting topology is termed a bluetree. In our bluetrees the number of roles each node can assume are limited to two or three (depending on the protocol), thus imposing low slave management overhead. The effectiveness of both protocols in forming MANETs is demonstrated through extensive simulations.

Indoor location tracking using RSSI readings from a single Wi-Fi access point

This paper describes research towards a system for locating wireless nodes in a home environment requiring merely a single access point. The only sensor reading used for the location estimation is the received signal strength indication (RSSI) as given by an RF interface, e.g., Wi-Fi. Wireless signal strength maps for the positioning filter are obtained by a two-step parametric and measurement driven ray-tracing approach to account for absorption and reflection characteristics of various obstacles. Location estimates are then computed using Bayesian filtering on sample sets derived by Monte Carlo sampling. We outline the research leading to the system and provide location performance metrics using trace-driven simulations and real-life experiments. Our results and real-life walk-troughs indicate that RSSI readings from a single access point in an indoor environment are sufficient to derive good location estimates of users with sub-room precision.

A Bayesian sampling approach to in-door localization of wireless devices using received signal strength indication

This paper describes a probabilistic approach to global localization within an in-door environment with minimum infrastructure requirements. Global localization is a flavor of localization in which the device is unaware of its initial position and has to determine the same from scratch. Localization is performed based on the received signal strength indication (RSSI) as the only sensor reading, which is provided by most off-the-shelf wireless network interface cards. Location and orientation estimates are computed using Bayesian filtering on a sample set derived using Monte-Carlo sampling. Research leading to the proposed method is outlined along with results and conclusions from simulations and real life experiments.

Static Path Planning for Mobile Beacons to Localize Sensor Networks

In this paper, we study the static path planning problem with wireless sensor network localization as the primary objective. We consider a model in which sensors are assumed to be uniformly deployed to a predefined deployment area. We then deploy a robot to serve as a mobile beacon to enable the localization of the sensor nodes. The robot follows a pre-determined static path while periodically broadcasting its current location coordinates to the nearby sensors. The static path planning problem looks for good paths that result in better localization accuracy and coverage of the sensor network while keeping the path length bounded. We propose two new path types, CIRCLES and S-CURVES, that are specifically designed to reduce the collinearity during localization. We compare our solution with existing ones using the Cramer Rao bound (CRB) as the evaluation tool, which gives an unbiased evaluation regardless of localization algorithm used. The evaluation shows that our solutions cope with collinearity in a more effective manner than previous solutions. Our solutions provide significantly better localization accuracy and coverage in the cases where collinearity is the greatest problem

ADAPT: a dynamically self-adjusting media access control protocol for ad hoc-networks

This paper presents a dynamically adaptive protocol for transmission (ADAPT) for ad hoc networks that combines, in a novel way, a collision-free allocation based protocol and a contention based protocol while retaining the advantages of each. At low loads, ADAPT uses its contention mechanism to reclaim/reuse bandwidth that would otherwise be wasted by a pure allocation based protocol. At high loads, ADAPT provides bounded delay guarantees by dynamically changing its operation to that of its allocation based protocol, avoiding the fundamental problem of instability associated with pure contention based protocols. Thus, ADAPT self-adjusts its behavior according to the prevailing network conditions. Both analysis and simulation results demonstrate that the two protocols interact in a positive way, showing that it is possible to combine the advantages of two fundamentally different design philosophies without suffering from their drawbacks.

Meta-MAC protocols: automatic combination of MAC protocols to optimize performance for unknown conditions

A systematic and automatic method to dynamically combine any set of existing MAC protocols into a single higher layer, or meta-MAC protocol, is presented. The new approach makes it possible to always achieve the performance of the best component protocol, without knowing in advance which protocol will match the potentially changing and unpredictable network conditions. Moreover, this dynamic optimization is entirely automatic and runs without any centralized control or any exchange of messages, using only local network feedback information. We describe the method and prove that the resulting meta-MAC protocol achieves optimal performance in a well-defined sense. Through simulation on different types of networks and with different component MAC protocols, we demonstrate that our simple and practical combination algorithm yields highly adaptive and scalable MAC solutions.

Incorporating Data from Multiple Sensors for Localizing Nodes in Mobile Ad Hoc Networks

The ad hoc network localization problem deals with estimating the geographical location of all nodes in an ad hoc network, focusing on those nodes that do not have a direct way (for example, GPS) to determine their own location. Proposed solutions to the ad hoc localization problem (AHLP) assume that nodes are capable of measuring received signal strength indication (RSSI) and/or are able to do coarse (sectoring) or fine signal angle-of-arrival (AoA) measurements. Existing algorithms exploit different aspects of such sensory data to provide either better localization accuracy or higher localization coverage. However, there is a need for a framework that could benefit from the interactions of nodes with mixed types of sensors. In this paper, we study the behavior of RSSI and AoA sensory data in the context of AHLP by using both geometric analysis and computer simulations. We show which type of sensor is better suited for which type of network scenario. We study how nodes using either, both, or none of these sensors could coexist in the same localization framework. We then provide a general particle-filtering framework, the first of its kind, that allows heterogeneity in the types of sensory data to solve the localization problem. We show that, when compared to localization scenarios where only one type of sensor is used, our framework provides significantly better localization results. Furthermore, our framework provides not only a location estimate for each nonanchor, but also an implicit confidence measure as to how accurate this estimate is. This confidence measure enables nodes to further improve on their location estimates using a local, iterative one-hop simple message exchange without having to rely on synchronized multiphase operations like in traditional multilateration methods.

Monte Carlo localization of wireless sensor networks with a single mobile beacon

One of the most important tasks in sensor networks is to determine the physical location of sensory nodes as they may not all be equipped with GPS receivers. In this paper we propose a localization method for wireless sensor networks (WSNs) using a single mobile beacon. The sensor locations are maintained as probability distributions that are sequentially updated using Monte Carlo sampling as the mobile beacon moves over the deployment area. Our method relieves much of the localization tasks from the less powerful sensor nodes themselves and relies on the more powerful beacon to perform the calculation. We discuss the Monte Carlo sampling steps in the context of the localization using a single beacon for various types of observations such as ranging, Angle of Arrival (AoA), connectivity and combinations of those. We also discuss the communication protocol that relays the observation data to the beacon and the localization result back to the sensors. We consider security issues in the localization process and the necessary steps to guard against the scenario in which a small number of sensors are compromised. Our simulation shows that our method is able to achieve less than 50% localization error and over 80% coverage with a very sparse network of degree less than 4 while achieving significantly better results if network connectivity increases.

An adaptive medium access control (MAC) protocol for reliable broadcast in wireless networks

This paper presents ABROAD, an adaptive medium access control (MAC) protocol for reliable broadcast packet transmission in wireless networks. ABROAD incorporates a collision-avoidance handshake within each slot of a synchronous transmission schedule, allowing nodes to reclaim and/or reuse idle slots while maintaining bounded access delay. Thus, ABROAD provides worst-case performance guarantees while remaining adaptive to local changes in traffic load and node connectivity. We analyze the optimal worst-case performance of ABROAD, and show that there is a strict increase in the number of broadcast packets per second over a pure time division multiple access (TDMA) protocol. Extensive simulation confirms our analysis, and also demonstrates that ABROAD outperforms broadcast protocols based on reliable unicast packet delivery schemes, such as the IEEE 802.11 MAC standard.

Simplified Bluetooth device discovery - analysis and simulation

Bluetooth is a promising wireless technology enabling (portable) devices to form short-range star-shaped wireless networks (or wireless personal area networks - PAN). Bluetooth relies on a frequency hopping physical layer, implying that hosts are not able to communicate unless they have previously discovered each by synchronizing their frequency hopping patterns. This further implies, that even if all nodes are within direct communication range, only those nodes that are synchronized within the personal area network can overhear a transmission. To support any-to-any communication such personal area networks (or in Bluetooth terminology piconets and possibly scatternets) need to be established among nodes. Thus, it is of utmost importance to be able to model or predict the time required for nodes to discover each other, i.e., to synchronize them. This paper provides a mathematical analysis and corresponding simulation results for the Bluetooth discovery (inquiry) time in a fully connected (personal area network) situation with the population as a parameter. The simplification to the analysis and simulation is due to the intermediate train changes in the inquiry process as it is outlined in the paper.