Browsing by Subject "Sensor networks"
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Item Open Access Accelerating the HyperLogLog cardinality estimation algorithm(Hindawi Limited, 2017) Bozkus, C.; Fraguela, B. B.In recent years, vast amounts of data of different kinds, from pictures and videos from our cameras to software logs from sensor networks and Internet routers operating day and night, are being generated. This has led to new big data problems, which require new algorithms to handle these large volumes of data and as a result are very computationally demanding because of the volumes to process. In this paper, we parallelize one of these new algorithms, namely, the HyperLogLog algorithm, which estimates the number of different items in a large data set with minimal memory usage, as it lowers the typical memory usage of this type of calculation from O(n) to O(1). We have implemented parallelizations based on OpenMP and OpenCL and evaluated them in a standard multicore system, an Intel Xeon Phi, and two GPUs from different vendors. The results obtained in our experiments, in which we reach a speedup of 88.6 with respect to an optimized sequential implementation, are very positive, particularly taking into account the need to run this kind of algorithm on large amounts of data. © 2017 Cem Bozkus and Basilio B. Fraguela.Item Open Access Adaptive decision fusion based cooperative spectrum sensing for cognitive radio systems(IEEE, 2011) Töreyin, B. U.; Yarkan, S.; Qaraqe, K. A.; Çetin, A. EnisIn this paper, an online Adaptive Decision Fusion (ADF) framework is proposed for the central spectrum awareness engine of a spectrum sensor network in Cognitive Radio (CR) systems. Online learning approaches are powerful tools for problems where drifts in concepts take place. Cooperative spectrum sensing in cognitive radio networks is such a problem where channel characteristics and utilization patterns change frequently. The importance of this problem stems from the requirement that secondary users must adjust their frequency utilization strategies in such a way that the communication performance of the primary users would not be degraded by any means. In the proposed framework, sensing values from several sensor nodes are fused together by weighted linear combination at the central spectrum awareness engine. The weights are updated on-line according to an active fusion method based on performing orthogonal projections onto convex sets describing power reading values from each sensor. The proposed adaptive fusion strategy for cooperative spectrum sensing can operate independent from the channel type between the primary user and secondary users. Results of simulations and experiments for the proposed method conducted in laboratory are also presented. © 2011 IEEE.Item Open Access Autonomous multiple teams establishment for mobile sensor networks by SVMs within a potential field(2012) Nazlibilek, S.In this work, a new method and algorithm for autonomous teams establishment with mobile sensor network units by SVMs based on task allocations within a potential field is proposed. The sensor network deployed into the environment using the algorithm is composed of robot units with sensing capability of magnetic anomaly of the earth. A new algorithm is developed for task assignment. It is based on the optimization of weights between robots and tasks. The weights are composed of skill ratings of the robots and priorities of the tasks. Multiple teams of mobile units are established in a local area based on these mission vectors. A mission vector is the genetic and gained background information of the mobile units. The genetic background is the inherent structure of their knowledge base in a vector form but it can be dynamically updated with the information gained later on by experience. The mission is performed in a magnetic anomaly environment. The initial values of the mission vectors are loaded by the task assignment algorithm. The mission vectors are updated at the beginning of each sampling period of the motion. Then the teams of robots are created by the support vector machines. A linear optimal hyperplane is calculated by the use of SVM algorithm during training period. Then the robots are classified as teams by use of SVM mechanism embedded in the robots. The support vector machines are implemented in the robots by ordinary op-amps and basic logical gates. Team establishment is tested by simulations and a practical test-bed. Both simulations and the actual operation of the system prove that the system functions satisfactorily. © 2012 Elsevier Ltd. All rights reserved.Item Open Access Autonomous navigation of robotic units in mobile sensor network(2012) Nazlibilek, S.This work is motivated by the problem of detecting buried anti-tank and anti-personnel mines in roads or some border regions. The problem is tried to be solved by use of small mobile robotic sensors and their some abilities such as measurement of local fields, navigation around a region, communications with each other, and constituting team within a mission area. The aim of this work is to investigate the navigation problem for the team behavior of mobile sensors within a potential field available in a small-scale environment such as an indoor area or an outdoor region. The mobile sensor network here is a collection of robotic units with sensing capability of earth magnetic field anomalies. A new kind of positioning system is needed for their collective behavior. In this work, a new method of navigation is proposed as a local positioning system. It utilizes ultrasound and radio frequency information to determine the coordinates of the points inside the operational area. The method proposed here is compared with the ultra wideband ranging ping-pong method that is used widely in recent applications. A time division multiple access method is used for the communications among the mobile sensors. The results on the positioning methods together with several simulations and experimental works are given. It is shown that the positioning method utilizing ultrasound-radio frequency method can give fairly good results. © 2012 Elsevier Ltd. All rights reserved.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 Bluetooth or 802.15.4 technologies to optimise lifetime of wireless sensor networks: Numerical comparison under a common framework(IEEE, 2008-04) Buratti, C.; Körpeoğlu, İbrahim; Karasan, Ezhan; Verdone, R.This paper aims at comparing through simulations the network lifetime of a wireless sensor network using Bluetooth-enabled or IEEE802.15.4 compliant devices. The evaluation is performed under a common reference framework, namely the EMORANS scenario for wireless sensor networks. Since the two enabling technologies rely on different MAC paradigms, suitable definition of the performance metrics is needed, in order to make the comparison meaningful. Thus, the paper has also a methodological objective. In particular, three different definitions of network lifetime are introduced, and a comparison of performance obtained by applying the different definitions is provided. Then, the comparison between the two standards is introduced: it is shown that there are no orders of magnitude of difference in network lifetime when the two technologies are used and the choice of the technology depends on the application requirements.Item Open Access Centralized and decentralized detection with cost-constrained measurements(Bilkent University, 2016-05) Laz, ErayIn this thesis, optimal detection performance of centralized and decentralized detection systems is investigated in the presence of cost constrained measurements. For the evaluation of detection performance, Bayesian, Neyman-Pearson and J- divergence criteria are considered. The main goal for the Bayesian criterion is to minimize the probability of error (more generally, the Bayes risk) under a constraint on the total cost of the measurement devices. In the Neyman-Pearson framework, the probability of detection is to be maximized under a given cost constraint. In the distance based criterion, the J-divergence between the distributions of the decision statistics under di erent hypotheses is maximized subject to a total cost constraint. The probability of error expressions are obtained for both centralized and decentralized detection systems, and the optimization problems are proposed for the Bayesian criterion. The probability of detection and probability of false alarm expressions are obtained for the Neyman-Pearson strategy and the optimization problems are presented. In addition, J-divergences for both centralized and decentralized detection systems are calculated and the corresponding optimization problems are formulated. The solutions of these problems indicate how to allocate the cost budget among the measurement devices in order to achieve the optimum performance. Numerical examples are presented to discuss the results.Item Open Access Centralized and decentralized detection with cost-constrained measurements(Elsevier B.V., 2017) Laz, E.; Gezici, SinanOptimal detection performance of centralized and decentralized detection systems is investigated in the presence of cost constrained measurements. For the evaluation of detection performance, Bayesian, Neyman–Pearson and J-divergence criteria are considered. The main goal for the Bayesian criterion is to minimize the probability of error (more generally, the Bayes risk) under a constraint on the total cost of the measurement devices. In the Neyman–Pearson framework, the probability of detection is to be maximized under a given cost constraint. In the distance based criterion, the J-divergence between the distributions of the decision statistics under different hypotheses is maximized subject to a total cost constraint. The probability of error expressions are obtained for both centralized and decentralized detection systems, and the optimization problems are proposed for the Bayesian criterion. The probability of detection and probability of false alarm expressions are obtained for the Neyman–Pearson strategy and the optimization problems are presented. In addition, J-divergences for both centralized and decentralized detection systems are calculated and the corresponding optimization problems are formulated. The solutions of these problems indicate how to allocate the cost budget among the measurement devices in order to achieve the optimum performance. Numerical examples are presented to discuss the results.Item Open Access Computing localized power-efficient data aggregation trees for sensor networks(Institute of Electrical and Electronics Engineers, 2011) Tan, H. O.; Korpeoglu, I.; Stojmenovic, I.We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for sensor networks, which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies, such as LMST and RNG, that can approximate minimum spanning tree and canbeefficiently computed using only position or distance information ofone-hop neighbors. The actual routing tree is constructed over these topologies. We also consider different parent selection strategies while constructing a routing tree. We compare each topology and parent selection strategy and conclude that the best among them is the shortest path strategy over LMST structure. Our solution also involves route maintenance procedures that will beexecuted whenasensor node fails ora new node is added to the network. The proposed solution is also adapted to consider the remaining power levels ofnodes in orderto increase the network lifetime. Our simulation results show that byusing our power-aware localized approach, we can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here. © 2011 IEEE.Item Open Access A distributed and dynamic data gathering protocol for sensor networks(IEEE, 2007-05) Tan, Hüseyin Özgür; Körpeoğlu, İbrahim; Stojmenović, I.In this paper we propose a distributed, self organizing, robust and energy efficient data gathering algorithm for sensor networks operating in environments where all the sensor nodes are not in direct communication range of each other and data aggregation is used while routing. Proposed algorithm is based on local minimum spanning tree (LMST) structure, which nodes can construct from the position of their 1-hop neighbors. Reporting tree is constructed from the sink by allowing only edges of LMST to join the tree, plus possibly some direct links to the sink. Each node selects as parent the LMST neighbor so that the total energy cost of route to the sink is minimal. We also describe route maintenance protocols to respond to predicted sensor failures and addition of new sensors. Our simulation results show that our algorithm prolongs the network lifetime significantly compared to some alternative schemes. © 2007 IEEE.Item Open Access Distributed and location-based multicast routing algorithms for wireless sensor networks(SpringerOpen, 2009-01) Korpeoglu, I.; Bagci, H.Multicast routing protocols in wireless sensor networks are required for sending the same message to multiple different destinations. In this paper, we propose two different distributed algorithms for multicast routing in wireless sensor networks which make use of location information of sensor nodes. Our first algorithm groups the destination nodes according to their angular positions and forwards the multicast message toward each group in order to reduce the number of total branches in multicast tree which also reduces the number of messages transmitted. Our second algorithm calculates an Euclidean minimum spanning tree at the source node by using the positions of the destination nodes. The multicast message is forwarded to destination nodes according to the calculated MST. This helps in reducing the total energy consumed for delivering the message to all destinations by decreasing the number of total transmissions. Evaluation results show that the algorithms we propose are scalable and energy efficient, so they are good candidates to be used for multicasting in wireless sensor networks. Copyright © 2009 H. Bagci and I. Korpeoglu.Item Open Access A distributed positioning algorithm for cooperative active and passive sensors(IEEE, 2010) Gholami, M.R.; Gezici, Sinan; Rydström, M.; Ström, E.G.The problem of positioning a target node is studied for wireless sensor networks with cooperative active and passive sensors. Two-way time-of-arrival and time-difference-of-arrival measurements made by both active and passive nodes are used to estimate the position of the target node. A maximum likelihood estimator (MLE) can be employed to solve the problem. Due to the nonlinear nature of the cost function in the MLE, an iterative search might converge to local minima which often results in large estimation errors. To avoid this drawback, we instead formulate the problem of positioning as finding the intersection of a number of convex sets derived from measurements. To obtain this intersection, we apply the projection onto convex sets approach, which is robust and can be implemented in a distributed manner. Simulations are performed to compare the performance of the MLE and the proposed method. ©2010 IEEE.Item Open Access EHPBS: Energy harvesting prediction based scheduling in wireless sensor networks(IEEE, 2013) Akgun, B.; Aykın, IrmakThe clustering algorithms designed for traditional sensor networks have been adapted for energy harvesting sensor networks (EHWSN). However, in these algorithms, the intra-cluster MAC protocols to be used were either not defined at all or they were TDMA based. These TDMA based MAC protocols are not specified except for the fact that cluster heads assign time slots to their members in a random manner. In this paper, we will modify this TDMA based scheduling as follows: members will request a time slot depending on their energy prediction and the cluster heads will assign these slots to members. This method will increase the network lifetime. The proof will be given with simulations. © 2013 IEEE.Item Open Access An energy efficient scatternet formation algorithm for Bluetooth-based sensor networks(IEEE, 2005-02) Saginbekov, Sain; Körpeoğlu, İbrahimIn this paper, we propose an energy-efficient scatternet formation algorithm for Bluetooth based sensor networks. The algorithm is based on first computing a shortest path tree from the base station to all sensor nodes and then solving the degree constraint problem so that the degree of each node in the network is not greater than seven, which is a Bluetooth constaint. In this way, less amount of energy is spent in each round of communication in the sensor network. The algorithm also tries to balance the load evenly on the high-energy consuming nodes which are the nodes that are close to the base station. In this way, the lifetime of the first dying node is also prolonged. We obtained promising results in the simulations. © 2005 IEEE.Item Open Access Irregular repetition slotted ALOHA with energy harvesting nodes(Bilkent University, 2017-07) Demirhan, UmutThe importance of wireless networking schemes originating from ALOHA has rapidly risen with the wide-spread use of Internet, advancements in the communications systems and increasing number of wireless devices. Internet-of-Things and machine-to-machine communications concepts have drawn further attention to ALOHA since it is a low-complexity protocol. However, the classical ALOHA is not e cient and cannot handle massive number of users in an e cient manner. Therefore, many improvements have been proposed for over the years. Irregular Repetition Slotted ALOHA (IRSA) is an advanced ALOHA protocol in which each user sends a variable number of copies of their packets in each xed length medium access control (MAC) frame. The collisions may be resolved via successive interference cancellation (SIC) using the copies that are received cleanly. In this way, asymptotic throughputs close to the maximum normalized throughput value of one on the collision channel may be achieved. In this thesis, to reap the bene ts of IRSA for energy harvesting sensor networks, we propose an IRSA based uncoordinated random access scheme for energy harvesting (EH) nodes. Speci cally, we consider the case in which each user has a nite-sized battery which is recharged in a probabilistic manner in each slot with harvested energy from the environment. We analyze this scheme by deriving asymptotic throughput expressions, and obtain optimized probability distributions for the number of packet replicas for each user. We demonstrate that the optimized distributions perform considerably better than those of slotted ALOHA (SA), contention resolution diversity slotted ALOHA (CRDSA) and plain IRSA which do not take into account EH for both asymptotic and nite frame length scenarios.Item Open Access Multiperson tracking with a network of ultrawideband radar sensors based on gaussian mixture PHD filters(Institute of Electrical and Electronics Engineers Inc., 2015) Gulmezoglu, B.; Guldogan, M. B.; Gezici, SinanIn this paper, we investigate the use of Gaussian mixture probability hypothesis density filters for multiple person tracking using ultrawideband (UWB) radar sensors in an indoor environment. An experimental setup consisting of a network of UWB radar sensors and a computer is designed, and a new detection algorithm is proposed. The results of this experimental proof-of-concept study show that it is possible to accurately track multiple targets using a UWB radar sensor network in indoor environments based on the proposed approach. © 2014 IEEE.Item Open Access PSAR: Power-source-aware routing in ZigBee networks(2012) Tekkalmaz, M.; Korpeoglu I.ZigBee is a recent wireless networking technology built on IEEE 802.15.4 standard and designed especially for low-data rate and low-duty cycle applications such as home and building automation and sensor networks. One of the primary goals of ZigBee is low power consumption and therefore long-living networks. Despite this goal, current network formation and routing protocols described in the ZigBee specification do not fully address power consumption issues. In this work, we propose a distributed routing algorithm to reduce power consumption of battery-powered devices by routing the communication through mains-powered devices whenever possible and consequently increasing the overall network lifetime. The proposed algorithm works on tree topologies supported by ZigBee and requires only minor modifications to the current specification. Our ns-2 simulation results showed that the algorithm is able to reduce the power consumption of battery-powered devices significantly with minimal communication overhead. © Springer Science+Business Media, LLC 2012.Item Open Access Rule-based in-network processing in wireless sensor networks(IEEE, 2009-07) Şanlı, Ö.; Körpeoğlu, İbrahim; Yazıcı, A.Wireless sensor networks are application-specific networks, and usually a new network design is required for a new application. In event-driven wireless sensor network applications, the sink node of the network is generally concerned with the higher level information describing the events happening in the network, not the raw sensor data of individual sensor nodes. As the communication is a costly operation in wireless sensor networks, it is important to process the raw data triggering the events inside the network instead of bringing the raw data to the sink and processing it there. This helps reducing the total amount of packets transmitted and total energy consumed in the network. In this paper, we propose a new method that distributes the information processing into the sensor network for event-driven applications. We also describe an application scenario, healthcare monitoring application, that can benefit from our approach. © 2009 IEEE.Item Open Access A run-time verification framework for smart grid applications implemented on simulation frameworks(IEEE, 2013-05) Çıracı, Selim; Sözer, Hasan; Tekinerdoğan, BedirSmart grid applications are implemented and tested with simulation frameworks as the developers usually do not have access to large sensor networks to be used as a test bed. The developers are forced to map the implementation onto these frameworks which results in a deviation between the architecture and the code. On its turn this deviation makes it hard to verify behavioral constraints that are described at the architectural level. We have developed the ConArch toolset to support the automated verification of architecture-level behavioral constraints. A key feature of ConArch is programmable mapping for architecture to the implementation. Here, developers implement queries to identify the points in the target program that correspond to architectural interactions. ConArch generates runtime observers that monitor the flow of execution between these points and verifies whether this flow conforms to the behavioral constraints. We illustrate how the programmable mappings can be exploited for verifying behavioral constraints of a smart grid application that is implemented with two simulation frameworks. © 2013 IEEE.Item Open Access Target classification with simple infrared sensors using artificial neural networks(IEEE, 2008-10) Aytaç, T.; Barshan, BillurThis study investigates the use of low-cost infrared (IR) sensors for the determination of geometry and surface properties of commonly encountered features or targets in indoor environments, such as planes, corners, edges, and cylinders using artificial neural networks (ANNs). The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting target in a way which cannot be represented by a simple analytical relationship, therefore complicating the localization and classification process. We propose the use of angular intensity scans and feature vectors obtained by modeling of angular intensity scans and present two different neural network based approaches in order to classify the geometry and/or the surface type of the targets. In the first case, where planes, 90° corners, and 90° edges covered with aluminum, white cloth, and Styrofoam packaging material are differentiated, an average correct classification rate of 78% of both geometry and surface over all target types is achieved. In the second case, where planes, 90° edges, and cylinders covered with different surface materials are differentiated, an average correct classification rate of 99.5% is achieved. The method demonstrated shows that ANNs can be used to extract substantially more information than IR sensors are commonly employed for. © 2008 IEEE.