Browsing by Subject "Wireless sensor network"
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Item Open Access Balancing energy loads in wireless sensor networks through uniformly quantized energy levels-based clustering(IEEE, 2010) Ali, Syed Amjad; Sevgi, Cüneyt; Kocyigit, A.Clustering is considered a common and an effective method to prolong the lifetime of a wireless sensor network. This paper provides a new insight into the cluster formation process based on uniformly quantizing the residual energy of the sensor nodes. The unified simulation framework provided herein, not only aids to reveal an optimum number of clusters but also the required number of quantization levels to maximize the network's lifetime by improving energy load balancing for both homogeneous and heterogeneous sensor networks. The provided simulation results clearly show that the uniformly quantized energy level-based clustering provides improved load balancing and hence, a longer network lifetime than existing methods. © 2010 IEEE.Item Open Access A concave-convex procedure for TDOA based positioning(IEEE, 2013) Gholami, M. R.; Gezici, Sinan; Strom, E. G.This letter investigates the time-difference-of-arrival based positioning problem in wireless sensor networks. We consider the least-mean absolute, i.e., the ℓ1 norm, minimization of the residual errors and formulate the positioning problem as a difference of convex functions (DC) programming. We then employ a concave-convex procedure to solve the corresponding DC programming. Simulation results illustrate the improved performance of the proposed approach compared to existing methods. © 1997-2012 IEEE.Item Open Access Coordinated movement of multiple mobile sinks in a wireless sensor network for improved lifetime(SpringerOpen, 2015) Koç, M.; Korpeoglu, I.Sink mobility is one of the most effective solutions for improving lifetime and has been widely investigated for the last decade. Algorithms for single-sink mobility are not directly applied to the multiple-sink case due to the latter’s specific challenges. Most of the approaches proposed in the literature use mathematical programming techniques to solve the multiple-sink mobility problem. However, doing so leads to higher complexities when traffic flow information for any possible sink-site combinations is included in the model. In this paper, we propose two algorithms that do not consider all possible sink-site combinations to determine migration points. We first present a centralized movement algorithm that uses an energy-cost matrix for a user-defined threshold number of combinations to coordinate multiple-sink movement. We also give a distributed algorithm that does not use any prior network information and has a low message exchange overhead. Our simulations show that the centralized algorithm gives better network lifetime performance compared to previously proposed MinDiff-RE, random movement, and static-sink algorithms. Our distributed algorithm has a lower network lifetime than centralized algorithms; sinks travel significantly less than in all the other schemes.Item Open Access Distributed bounding of feasible sets in cooperative wireless network positioning(IEEE, 2013) Gholami, M. R.; Wymeersch, H.; Gezici, Sinan; Ström, E. G.Locations of target nodes in cooperative wireless sensor networks can be confined to a number of feasible sets in certain situations, e.g., when the estimated distances between sensors are larger than the actual distances. Quantifying feasible sets is often challenging in cooperative positioning. In this letter, we propose an iterative technique to cooperatively outer approximate the feasible sets containing the locations of the target nodes. We first outer approximate a feasible set including a target node location by an ellipsoid. Then, we extend the ellipsoid with the measured distances between sensor nodes and obtain larger ellipsoids. The larger ellipsoids are used to determine the intersections containing other targets. Simulation results show that the proposed technique converges after a small number of iterations.Item Open Access Energy-efficient sink mobility algorithms for wireless sensor networks(Bilkent University, 2015-09) Koç, MetinA wireless sensor network consists of a large number of tiny sensor nodes which are capable of sensing an environment and sending the collected data to a sink node. For most scenarios, sensor nodes are powered with irreplaceable batteries and this dramatically limits the lifetime of the network, especially due to overloading of the sensor nodes neighboring sink node. Such nodes need to forward more traffic than other nodes in the network. Moving sink node and in this way distributing forwarding-load evenly among sensor nodes is one of the important techniques for improving lifetime of sensor networks. We propose different mobility algorithms for single-sink and multiple-sink mobility problem to efficiently move sink nodes through a predefined set of sink sites. We first provide packet-load and energy-load based sink mobility algorithms, called PLMA and ELMA, in which node-load parameters are incorporated into a table and this table is used to determine which sink site to visit in each round. We also give an integer programming model to get optimal results and do benchmarking. Since routing topology is an important component of sink mobility schemes, we also propose centralized and distributed routing topology construction algorithms to further increase network lifetime. Additionally, we propose an adaptive energy-load based sink movement algorithm, called A-ELMA, which does not require an initial training phase to learn about network topology. It incrementally constructs and updates energy-load table each time it visits a site location. Finally, besides proposing algorithms for single-sink mobility problem, we also propose two different algorithms for multiple-sink mobility problem. Our Multiple Sink Movement Algorithm (MSMA) is a centralized algorithm and effectively limits the sink site combinations to reduce computation and communication overhead in scheduling sink movements without harming network lifetime significantly. Our Prevent and Move Away (PMA) algorithm is a fully distributed algorithm and does not require topology information to be collected. It selects sites based on remaining energy values and distance metrics. We evaluated our algorithms and compared them to some basic approaches in the literature by conducting extensive simulation experiments. Our simulation results show that our algorithms can perform better than some other alternatives in terms of network lifetime, latency and travel distance. We also identify under which conditions our algorithms perform better for each of these metrics. We observed that our algorithms provide simple-to-use, efficient, and effective solutions for single- and multiple-sink mobility problems in wireless sensor networks.Item Open Access Improved position estimation using hybrid TW-TOA and TDOA in cooperative networks(Institute of Electrical and Electronics Engineers, 2012-04-13) Gholami, M. R.; Gezici, Sinan; Ström, E. G.This paper addresses the problem of positioning multiple target nodes in a cooperative wireless sensor network in the presence of unknown turn-around times. In this type of cooperative networks, two different reference sensors, namely, primary and secondary nodes, measure two-way time-of-arrival (TW-TOA) and time-difference-of-arrival (TDOA), respectively. Motivated by the role of secondary nodes, we extend the role of target nodes such that they can be considered as pseudo secondary nodes. By modeling turn-around times as nuisance parameters, we derive a maximum likelihood estimator (MLE) that poses a difficult global optimization problem due to its nonconvex objective function. To avoid drawbacks in solving the MLE, we linearize the measurements using two different techniques, namely, nonlinear processing and first-order Taylor series, and obtain linear models based on unknown parameters. The proposed linear estimator is implemented in three steps. In the first step, a coarse position estimate is obtained for each target node, and it is refined through steps two and three. To evaluate the performance of different methods, we derive the Cramér-Rao lower bound (CRLB). Simulation results show that the cooperation technique provides considerable improvements in positioning accuracy compared to the noncooperative scenario, especially for low signal-to-noise-ratios.