Deniz Üstebay

Distributed auxiliary particle filters using selective gossip

This paper introduces a distributed auxiliary particle filter for target tracking in sensor networks. Nodes maintain a shared particle filter by coming to a consensus about the likelihoods associated with each particle using the selective gossip procedure. Selective gossip provides a mechanism to efficiently identify the particles with largest weights and focus communication on sharing these important weights. We demonstrate through simulations that the algorithm performs well; compared to state-of-the-art approaches it either significantly improves the accuracy at the expense of a small increase in communication overhead, or achieves comparable accuracy with much lower communication overhead.

Efficient Decentralized Approximation via Selective Gossip

Recently, gossip algorithms have received much attention from the wireless sensor network community due to their simplicity, scalability and robustness. Motivated by applications such as compression and distributed transform coding, we propose a new gossip algorithm called Selective Gossip. Unlike traditional randomized gossip which computes the average of scalar values, we run gossip algorithms in parallel on the elements of a vector. The goal is to compute only the entries which are above a defined threshold in magnitude, i.e., significant entries. Nodes adaptively approximate the significant entries while abstaining from calculating the insignificant ones. Consequently, network lifetime and bandwidth are preserved. We show that with the proposed algorithm nodes reach consensus on the values of the significant entries and on the indices of insignificant ones. We illustrate the performance of our algorithm with a field estimation application. For regular topologies, selective gossip computes an approximation of the field using the wavelet transform. For irregular network topologies, we construct an orthonormal transform basis using eigenvectors of the graph Laplacian. Using two real sensor network datasets we show substantial communication savings over randomized gossip. We also propose a decentralized adaptive threshold mechanism such that nodes estimate the threshold while approximating the entries of the vector for computing the best m -term approximation of the data.

Comparison of PI controllers designed for the delay model of TCP/AQM networks

One of the major problems of communication networks is congestion. In order to address this problem in TCP/IP networks, Active Queue Management (AQM) scheme is recommended. AQM aims to minimize the congestion by regulating the average queue size at the routers. To improve upon AQM, recently, several feedback control approaches were proposed. Among these approaches, PI controllers are gaining attention because of their simplicity and ease of implementation. In this paper, by utilizing the fluid-flow model of TCP networks, we study the PI controllers designed for TCP/AQM. We compare these controllers by first analyzing their robustness and fragility. Then, we implement these controllers in ns-2 platform and conduct simulation experiments to compare their performances in terms of queue length. Taken together, our results provide a guideline for choosing a PI controller for AQM given specific performance requirements.

Greedy gossip with eavesdropping

This paper presents greedy gossip with eavesdropping (GGE), a new average consensus algorithm for wireless sensor network applications. Consensus algorithms have recently received much attention in the sensor network community because of their simplicity and completely decentralized nature which makes them robust to changes in the network topology and unreliable wireless networking environments. In the sensor network, each node has a measurement value and the aim of average consensus is computing the average of these node values in the absence of a central authority. We prove that GGE converges to the average consensus with probability one. We also illustrate the performance of the algorithm via simulations and conclude that GGE provides a significant performance improvement compared to existing average consensus algorithms such as randomized gossip and geographic gossip.

Switching Resilient PI Controllers for Active Queue Management of TCP Flows

Active Queue Management (AQM) is used in computer networks to increase link utilization with less queueing delays. The fluid flow model of TCP based on delay differential equations supplies the mathematical background for modelling the AQM as a feedback system. Recently various PI and PID controllers are designed for this feedback system, [7], [18]. In this paper, we consider the case for which the Round Trip Time (RTT) is time varying and we propose switching resilient PI controllers using the design method introduced in [18].

Distributed underwater acoustic source localization and tracking

We consider the problem of localizing and tracking an acoustic noise source under water using bearing measurements taken from a small collection of acoustic sensors. Nodes must cooperate in order to improve their estimates and overcome significant noise levels and spurious measurements from clutter. However the underwater communication channel is highly unreliable, which makes coordination challenging. We evaluate the performance of distributed particle filtering methods in the setting where nodes communicate over unreliable links. Our results are validated using data from an experiment conducted at sea.

Distributed ensemble Kalman filtering

We address the problem of distributed filtering in a wireless sensor network and develop distributed approximations of three variants of the ensemble Kalman filter. We express the update equations in an alternative information form in order to formulate a distributed measurement update mechanism. The distributed filters use randomized gossip to reach consensus on the statistics needed to perform an update. Simulation results suggest that in the case of linear measurements and high-dimensional nonlinear measurements (with measurement model parameters known network-wide) with nonlinear state dynamics the proposed schemes achieve accuracy comparable to state-of-the-art distributed filters while significantly reducing the communication overhead.

Distributed Approximation and Tracking Using Selective Gossip

This chapter presents selective gossip which is an algorithm that applies the idea of iterative information exchange to vectors of data. Instead of communicating the entire vector and wasting network resources, our method adaptively focuses communication on the most significant entries of the vector. We prove that nodes running selective gossip asymptotically reach consensus on these significant entries, and they simultaneously reach an agreement on the indices of entries which are insignificant. The results demonstrate that selective gossip provides significant communication savings in terms of the number of scalars transmitted. In the second part of the chapter we propose a distributed particle filter employing selective gossip. We show that distributed particle filters employing selective gossip provide comparable results to the centralized bootstrap particle filter while decreasing the communication overhead compared to using randomized gossip to distribute the filter computations.

TOP-K selective gossip

Many distributed signal processing problems involve aggregating vectors of data, and often we are interested in the largest entries of the aggregate vector. For example, in distributed particle filtering one may be interested in fusing information about particles with the largest weights. Gossip algorithms are an attractive method for distributed processing in unreliable networks. We propose top-k selective gossip, an algorithm which reduces the amount of information communicated by updating only the highest k entries at each iteration. We derive convergence properties for this algorithm, and simulation results illustrate significant communication savings compared to randomized gossip.

Comparing PI Controllers for Delay Models of TCP/AQM Networks

Abstract In this paper, ns-2 simulations and related comparisons of four different PI controllers designed for TCP/AQM networks will be presented. The simulations are performed for various scenarios. IFAC