Niels Karowski

Optimized asynchronous multi-channel neighbor discovery

We consider the problem of neighbor discovery in wireless networks with nodes operating in multiple frequency bands and with asymmetric beacon intervals. This is a challenging task when considering such heterogenous operation conditions and when performed without any external assistance. We present linear programming (LP) optimization and two strategies, named OPT and SWOPT, allowing nodes performing fast, asynchronous, and passive discovery. Our optimization is slotted based and determines a listening schedule describing when to listen, for how long, and on which channel. We compare our strategies with the passive discovery of the IEEE 802.15.4 standard. The results confirm that our optimization improves the performance in terms of first, average, and last discovery time.

Optimized Asynchronous Multichannel Discovery of IEEE 802.15.4-Based Wireless Personal Area Networks

Network discovery is a fundamental task in different scenarios of IEEE 802.15.4-based wireless personal area networks. Scenario examples are body sensor networks requiring health- and wellness-related patient monitoring or situations requiring opportunistic message propagation. In this paper, we investigate optimized discovery of IEEE 802.15.4 static and mobile networks operating in multiple frequency bands and with different beacon intervals. We present a linear programming model that allows finding two optimized strategies, named OPT and SWOPT, to deal with the asynchronous and multichannel discovery problem. We also propose a simplified discovery solution, named SUBOPT, featuring a low-complexity algorithm requiring less memory usage. A cross validation between analytical, simulation, and experimental evaluation methods is performed. Finally, a more detailed simulation-based evaluation is presented, when considering varying sets of parameters (i.e., number of channels, network density, beacon intervals, etc.) and using static and mobile scenarios. The performance studies confirm improvements achieved by our solutions in terms of first, average, and last discovery time as well as discovery ratio, when compared to IEEE 802.15.4 standard approach and the SWEEP approach known from the literature.

Passive discovery of IEEE 802.15.4-based body sensor networks

In this paper we study passive discovery of IEEE 802.15.4 networks operating in the beacon-enabled mode. The task of discovery occurs in different scenarios. One example is a simple device that wishes to associate with a specific, pre-specified PAN coordinator (targeted discovery). Another example are opportunistic relaying applications, where arbitrary foreign coordinators should be discovered (untargeted discovery). We consider a simple class of listening strategies and provide different analytical models which allow to find optimal strategies for different listening scenarios. For the case of targeted discovery without constraints on the listening costs we give a dynamic programming formulation, for targeted discovery with bounded costs we present and validate a simple model and derive the desired performance measures. For untargeted discovery we present simulation results in a mobile scenario.

The ANGEL IEEE 802.15.4 enhancement layer: Coupling priority queueing and service differentiation

The EU FP6 ANGEL project considers the usage of IEEE 802.15.4-based wireless sensor network technology in medical applications. Some key requirements found in this class of applications are not well supported by IEEE 802.15.4. In this paper we propose a wrapper layer on top of IEEE 802.15.4 that adds, amongst others, a mechanism combining priority queueing and per-packet parameter control to provide (stochastic) service differentiation. In this paper we describe the design and implementation of this mechanism and present measurement results, showing its effectiveness.

The ANGEL WSN Architecture

In this paper we present an overview of the sensor network architecture as developed in the ANGEL project. We first specify the particular requirements found in healthcare and assisted-living applications, then introduce the general reference architecture and finally discuss some security-related aspects.

Meeting IoT platform requirements with open pub/sub solutions

The internet of things (IoT) will enable a range of applications providing enhanced awareness and control of the physical environment. Current systems typically sense and actuate physical phenomena locally and then rely on a cloud-based publish/subscribe infrastructure for distribution of sensor and control data to end-users and external services. Despite the popularity of pub/sub solutions in this context, it is still unclear which features such a middleware should have to successfully meet the specific requirements of the IoT domain. Questions like how a large number of connected devices that only sporadically send small sensor data messages affect the throughput, and how much additional delay cloud-based pub/sub systems typically introduce, that are very important for practitioners, have not been tackled in a systematic way. In this work, we address these limitations by analyzing the main requirements of IoT platforms and by evaluating which of those features are supported by prominent open pub/sub solutions. We further carry out a performance evaluation in the public cloud using four popular pub/sub implementations: rabbitMQ (AMQP), mosquitto (MQTT), ejabberd (XMPP), and ZeroMQ. We study the maximum sustainable throughput and delay under realistic load conditions using traces from real sensors. While the core features are similar, the analyzed pub/sub systems differ in their filtering capabilities, semantic guarantees, and encoding. Our evaluation indicates that those differences can have a notable impact on throughput and delay of cloud-based IoT platforms.

LoWS: A complete Open Source solution for Wi-Fi beacon stuffing based Location-based Services

Omnipresent Wi-Fi access points (APs) periodically broadcast beacon frames to inform potential stations (STAs) about their existence. Beacon frames can be extended by adding additional information (so-called beacon stuffing) making it possible to deliver this information to mobile devices (smart-phones, tablets, etc. equipped with 802.11 interfaces) without the need for association with the local infrastructure. This feature can be used to support location-based information services (LBS) related for e.g. advertising local opportunities, temporary obstacles and traffic disturbances or emergency notifications. In this paper we discuss technical solutions that support LBS using 802.11 beacon stuffing. For a selected approach we present the design, implementation details and performance evaluation for Location-based Wi-Fi Services (LoWS) - a complete open source solution. LoWS supports an original, highly efficient way to encode information. The LoWS system can be integrated in an existent 802.11 infrastructure while the receiver application can be installed on commercial off-the-shelf Android devices. The LoWS system is modular with well-defined interfaces making it an attractive tool for modifications, changes and improvements.

Cooperation in neighbor discovery

Neighbor discovery is a fundamental task in wireless networks in order to find potential communication partners, discover services, and to efficiently access the wireless resource. In this paper we focus on the passive neighbor discovery in multi-channel environments. We present different discovery approaches with low computational complexity that utilize cooperation between devices by exchanging discovery results in order to improve the discovery process. Furthermore, we present an optimized discovery approach that uses multiple transceivers and evaluate the bounds on the performance under idealized conditions. We analyze the impact of different network parameters such as number of channels and number of neighbors on the discovery times of the developed approaches by using a simulative evaluation. By putting the discovery times achievable with the cooperative or “gossiping” approaches into perspective with the multi-transceiver results, we can quantify the value of cooperation in terms of numbers of transceivers.