Stefan Dulman

Trade-off between traffic overhead and reliability in multipath routing for wireless sensor networks

In wireless sensor networks (WSN) data produced by one or more sources usually has to be routed through several intermediate nodes to reach the destination. Problems arise when intermediate nodes to reach the destination. Problems arise when intermediate nodes fail to forward the incoming messages. The reliability of the system can be increased by providing several paths from source to destination and sending the same packet through each of them (the algorithm is known as multipath routing). Using this technique, the traffic increases significantly. In this paper, we analyze a new mechanism that enables the trade-off between the amount of traffic and the reliability. The data packet is split in k subpackets (k = number of disjoined paths from source to destination). If only E/sub k/ subpackets (E/sub k/ < k) are necessary to rebuild the original data packet (condition obtained by adding redundancy to each subpacket), then the trade-off between traffic and reliability can be controlled.

Range-Based localization in mobile sensor networks

Localization schemes for wireless sensor networks can be classified as range-based or range-free. They differ in the information used for localization. Range-based methods use range measurements, while range-free techniques only use the content of the messages. None of the existing algorithms evaluate both types of information. Most of the localization schemes do not consider mobility. In this paper, a Sequential Monte Carlo Localization Method is introduced that uses both types of information as well as mobility to obtain accurate position estimations, even when high range measurement errors are present in the network and unpredictable movements of the nodes occur. We test our algorithm in various environmental settings and compare it to other known localization algorithms. The simulations show that our algorithm outperforms these known range-oriented and range-free algorithms for both static and dynamic networks. Localization improvements range from 12% to 49% in a wide range of conditions.

On the hop count statistics for randomly deployed wireless sensor networks

In this paper we focus on exploiting the information provided by a generally accepted and largely ignored hypothesis (the random deployment of the nodes of an ad hoc or wireless sensor network) to design improved networking protocols. Specifically, we derive the relationship between the number of hops separating two nodes and the physical distance between them (one- and two- dimensional topologies). In this way, distance estimates between nodes are made available without the use of any distance measuring hardware. We conclude the paper showing how the obtained statistical results can be applied to improve the performance of distributed localisation protocols while simplifying their implementation.

Multi-channel support for dense wireless sensor networking

Currently, most wireless sensor network applications assume the presence of single-channel Medium Access Control (MAC) protocols. When sensor nodes are densely deployed, single-channel MAC protocols may be inadequate due to the higher demand for the limited bandwidth. To overcome this drawback, we propose multiple channel support for improving the performance. Our method allows the nodes to utilize new frequency channels which results in the significant increase on the number of nodes that are granted access to the wireless medium. The method requires only one half-duplex transceiver per node, which is capable of sending and receiving over distinguished frequency channels. Simulation results show that, method successfully utilizes multiple channels and increases the performance proportional to the number of available frequencies for an example single-channel MAC protocol, LMAC.

Collaborative algorithms for communication in wireless sensor networks

In this paper, we present the design of the communication in a wireless sensor network. The resource limitations of a wireless sensor network, especially in terms of energy, require an integrated, and collaborative approach for the different layers of communication. In particular, energy-efficient solutions for medium access control, clusterbased routing, and multipath creation and exploitation are discussed. The proposed MAC protocol is autonomous, decentralized and designed to minimize power consumption. Scheduling of operations, e.g. for the MAC protocol, is naturally supported by a clustered structure of the network. The multipath on-demand routing algorithm improves the reliability of data routing. The approaches taken and presented are designed to work together and support each other.

NetDetect: Neighborhood Discovery in Wireless Networks Using Adaptive Beacons

It is generally foreseen that the number of wirelessly connected networking devices will increase in the next decades, leading to a rise in the number of applications involving large-scale networks. A major building block for enabling self-* system properties in ad-hoc scenarios is the run-time discovery of neighboring devices and somewhat equivalently, the estimation of the local node density. This problem has been studied extensively before, mainly in the context of fully-connected, synchronized networks. In this paper, we propose a novel adaptive and decentralized solution, the NetDetect algorithm, to the problem of discovering neighbors in a dynamic wireless network. The main difference with existing state of the art is that we target dynamic scenarios, i.e., multihop mesh networks involving mobile devices. The algorithm exploits the beaconing communication mechanism, dynamically adapting the beacon rate of the devices in the network based on local estimates of neighbor densities. We evaluate NetDetect on a variety of networks with increasing levels of dynamics: fully-connected networks, static and mobile multi-hop mesh networks. Results show that NetDetect performs well in all considered scenarios, maintaining a high rate of neighbor discoveries and good estimate of the neighborhood density even in very dynamic situations. More importantly, the proposed solution is adaptive, tracking changes in the local environment of the nodes without any additional algorithmic reconfiguration. Comparison with existing approaches shows that the proposed scheme is efficient from both convergence time and energy perspectives.

Statistically enhanced localization schemes for randomly deployed wireless sensor networks

We address the localization problem for semi-static, randomly deployed, wireless sensor networks. The influence of the underlying random topology is discussed, and based on it we derive a distance estimations function of the number of hops two nodes are separated by, and characterize the precision of these estimations. The results are applied to two well-known localization schemes (DVHop and DVDistance) and improvements in the positioning error of roughly 26% for the first algorithm and 20% for the second algorithm are obtained. The introduced overhead is kept at a minimum as the resulting protocols are simpler than the original ones and only density information needs to be broadcast to the nodes.

A Distributed Precision Based Localization Algorithm for Ad-Hoc Networks

In this paper we introduce a new distributed algorithm for location discovery. It can be used in wireless ad-hoc sensor networks that are equipped with means of measuring the distances between the nodes (like the intensity of the received signal strength). The algorithm takes the reliability of measurements into account during calculation of the nodes positions. Simulation results are presented, showing the algorithms performance in relation to its accuracy, communication and calculation costs. The simulation results of our approach yield 2 to 4 times better results in position accuracy than other systems described previously. This level of performance can be reached using only few broadcast messages with small and constant size, for each node in the network.

ChurnDetect: a gossip-based churn estimator for large-scale dynamic networks

With the ever increasing scale of dynamic wireless networks (such as MANETs, WSNs, VANETs, etc.), there is a growing need for performing aggregate computations, such as online detection of network churn, via distributed, robust and scalable algorithms. In this paper we introduce the ChurnDetect algorithm, a novel solution to the distributed churn estimation problem. Our solution consists in a gossiping-based algorithm, which incorporates a periodic reset mechanism (introduced as DiffusionReset). The main difference with existing state-of-the-art is that ChurnDetect does not require nodes to advertise their departure from the network nor to detect neighbors leaving the network. In our solution, all the nodes are interacting with each other wirelessly, by using a gossip-alike approach, thus keeping the message complexity to a minimum. We only use easy accessible information (i.e., about new nodes joining the network) rather than presuming knowledge on nodes leaving the system since that is highly unfeasible for most distributed applications. We provide convergence proofs for ChurnDetect, and present a number of results based on simulations and implementation on our local testbed. We characterize the performance of the algorithm, showcasing its distributed light-weight characteristics. The analysis leads to the conclusion that ChurnDetect is an attractive alternative to existing work on online churn estimation for dynamic wireless networks.

FailDetect: Gossip-Based Failure Estimator for Large-Scale Dynamic Networks

Ubiquitous and wirelessly connected devices are the present status quo in terms of networks around us. With the ever increase of scale, there comes also the problem of various communication failures. They are usually caused by hardware, software, or any other medium access contention. For the case of mobile networks, path uncertainty comes also into picture due to node mobility. All this leads to low quality of service and reduced user experience. The main contribution of the paper is the introduction of a novel distributed algorithm called FailDetect for the statistical estimation of the average packet loss in large-scale wireless distributed systems. It is based on a gossip mechanism, with the adding of periodic resets of the exchanged values. FailDetect is a fully- distributed scheme that does not presume time synchronization among the reset intervals for various nodes. A model and an evaluation by means of simulation and experiments show that FailDetect succeeds in evaluating the average packet loss of the network, while exhibiting low message-complexity.