VERTEX COVER BASED LINK MONITORING TECHNIQUES FOR WIRELESS SENSOR NETWORKS

VERTEX COVER BASED LINK MONITORING TECHNIQUES FOR WIRELESS SENSOR NETWORKSAbstractWireless sensor networks (WSNs) are generally composed of numerous battery-powered tiny nodes that can sense from the environment and send this data through wireless communication. WSNs have wide range of application areas such as military surveillance, healthcare, miner safety, and outer space exploration. Inherent security weaknesses of wireless communication may prone WSNs to various attacks such as eavesdropping, jamming and spoofing. This situation attracts researchers to study countermeasures for detection and prevention of these attacks. Graph theory provides a very useful theoretical basis for solving WSN problems related to communication and security issues. One of the important graph theoretic structures is vertex cover (VC) in which a set of nodes are selected to cover the edges of the graph where each edge is incident to at least one node in VC set. Finding VC set having the minimum cardinality for a given graph is an NP-hard problem. In this paper, we describe VC algorithms aiming link monitoring where nodes in VC are configured as secure points. We investigate variants of VC problems such as weight and capacity constrained versions on different graph types to meet the energy-efficiency and load-balancing requirements of WSNs. Moreover, we present clustering and backbone formation operations as alternative applications of different VC infrastructures. For each VC sub-problem, we propose greedy heuristic based algorithms.Keywords: Wireless Sensor Networks, Link Monitoring, Graph Theory, Vertex Cover, NP-Hard Problem.KABLOSUZ SENSÖR AĞLARI İÇİN KÖŞE ÖRTME TABANLI BAĞLANTI İZLEME TEKNİKLERİÖzetKablosuz sensor ağlar (KSAlar) genellikle ortamdan algılayabilen ve bu verileri kablosuz iletişim yoluyla gönderebilen pille çalışan çok sayıda küçük düğümden oluşur. KSAlar askeri gözetim, sağlık hizmetleri, madenci güvenliği ve uzay keşfi gibi çok çeşitli uygulama alanlarına sahiptir. Kablosuz iletişimin doğasında var olan güvenlik zayıflıkları, KSAları gizli dinleme, sinyal bozma ve sahtekarlık gibi çeşitli saldırılara eğilimli hale getirebilmektedir. Bu durum, araştırmacıları bu saldırıların tespiti ve önlenmesine yönelik karşı önlemleri incelemeye yöneltmektedir. Çizge teorisi, iletişim ve güvenlik sorunları ile ilgili KSA sorunlarını çözmek için çok yararlı bir teorik temel sağlar. Önemli çizge teorik yapılardan biri köşe örtmedir (KÖ), bu yapıda her bir kenarın KÖ kümesindeki en az bir düğüme bitişik olacak şekilde çizgenin tüm kenarlarını kapsayacak bir dizi düğüm seçilmektedir. Verilen bir çizge için en az elemana sahip KÖ kümesini bulmak NP-zor bir problemdir. Bu makalede, KÖdeki düğümlerin güvenli noktalar olarak yapılandırıldığı bağlantı izlemeyi amaçlayan KÖ algoritmaları açıklanmaktadır. KSAların enerji verimliliği ve yük dengeleme gereksinimlerini karşılamak için, farklı çizge yapılarında KÖ problemlerinin ağırlık ve kapasite kısıtlı versiyonları gibi çeşitli türleri çalışılmaktadır. Ayrıca kümeleme ve omurga oluşturma işlemlerini farklı KÖ altyapılarının alternatif uygulamaları olarak sunulmaktadır. Her KÖ alt problemi için, açgözlü sezgisel tabanlı algoritmalar önerilmektedir.Anahtar Kelimeler: Kablosuz Sensör Ağları, Bağlantı İzleme, Çizge Teorisi, Kenar Örtme, NP-Zor Problem.

A Metaheuristic Algorithm for Vertex Cover based Link Monitoring and Backbone Formation in Wireless Ad hoc Networks

Wireless ad hoc networks (WANETs) are infrastructureless networks and are used in various applications such as habitat monitoring, military surveillance, and disaster relief. Data transmission is achieved through radio packet transfer, thus it is prone to various attacks such as eavesdropping, spoofing, and etc. Monitoring the communication links by secure points (monitors) is an essential precaution against these attacks. Also, deploying monitors provides a virtual backbone for multi-hop data transmission. However, adding secure points to a WANET can be costly in terms of price and time, so minimizing the number of secure points is of utmost importance. Graph theory provides a great foundation to tackle the emerging problems in WANETs. A vertex cover (VC) is a set of vertices where every edge is incident to at least one vertex. The minimum weighted connected VC (MWCVC) problem can be defined as finding the VC of connected nodes having the minimum total weight. MWCVC is a very suitable infrastructure for energy-efficient link monitoring and virtual backbone formation. In this paper, we propose a novel metaheuristic algorithm for MWCVC construction in WANETs. Our algorithm is a population-based iterated greedy (PBIG) approach that is very effective against graph theoretical problems. We explain the idea of the algorithm and illustrate its operation through sample examples. We implement the proposed algorithm with its competitors on a widely used dataset. From extensive measurements, we obtain that the algorithm produces WCVC with less weight at the same time its monitor count and time performances are reasonable

Automatic Registration of Structural Brain MR Images to MNI Image Space

23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYWOS: 000380500900068Disease diagnosis has been made by experts examining the images obtained by magnetic resonance imaging (MRI) technique, the disease process is observed using images taken at different times. Brain MR images are registered to the standard brain atlases because the human brain has a complex structure and varies from person to person. Corpus Callosum (CC) has a big importance for medical image registration because it can be easily distinguished on T1-weighted structural brain MR images and does not vary prominently between individuals. In this study, from the midsagittal brain MR image that belongs to the patient CC is detected fully automatically via Valley Matching (VM) Algorithm. The contribution of this study is registration of patient's MR image onto the Montreal Neurological Institute (MNI) image space by using automatically detected reference points.Dept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Uni

PINC : pickup non-critical node based k-connectivity restoration in wireless sensor networks

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors

Design and implementation of asset tracking system based on Internet of Things

7th International Conference on Electrical, Electronics and Information Engineering (ICEEIE) -- OCT 02, 2021 -- Malang, INDONESIAThe demand for accurate and real-time indoor positioning systems with a limited margin of error is increasing day by day. However, the insufficiency of global positioning system and other outdoor positioning systems in indoor environments complicates the development of indoor tracking and positioning systems. In this paper, an indoor tracking and monitoring system has been designed using the new generation devices for the Internet of Things. By using WiFi and bluetooth low energy (BLE) signals at the same time, we developed an accurate and precise positioning system. In the developed system, we have used the NodeMCU-ESP-32 module to receive the broadcasted WiFi and BLE signals from smartphones. The NodeJS-based HTTP server combines the received information from ESPs and determines the location of the mobile device with the proposed algorithm based on the weighted average method. NodeJS server provides instant information about anchors and mobile nodes to the users over a web application. The proposed weighted average-based method can determine the real-time room-based location of the target asset with acceptable precision.IEEE Indonesia Sect,Univ Negeri Malang,Inovasi Berna

Two population-based optimization algorithms for minimum weight connected dominating set problem

WOS: 000407732600046Minimum weight connected dominating set (MWCDS) is a very important NP-Hard problem used in many applications such as backbone formation, data aggregation, routing and scheduling in wireless ad hoc and sensor networks. Population-based approaches are very useful to solve NP-Hard optimization problems. In this study, a hybrid genetic algorithm (HGA) and a population-based iterated greedy (PBIG) algorithm for MWCDS problem are proposed. To the best of our knowledge, the proposed algorithms are the first population-based algorithms to solve MWCDS problem on undirected graphs. HGA is a steady-state procedure which incorporates a greedy heuristic with a genetic search. PBIG algorithm refines the population by partially destroying and greedily reconstructing individual solutions. We compare the performance of the proposed algorithms with other greedy heuristics and brute force methods through extensive simulations. We show that our proposed algorithms perform very well in terms of MWCDS solution quality and CPU time. (C) 2017 Elsevier B.V. All rights reserved.Scientific and Technical Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [BIDEB 2211-C]The authors would like to thank the anonymous reviewers for their careful reading of the manuscript, insightful comments and suggestions that helped to improve the quality of this paper. We thank to Dr. Aybars Ugur for suggestions and guidance that are very helpful for us. We also thank Scientific and Technical Research Council of Turkey (TUBITAK) for the BIDEB 2211-C program for the PhD scholarship

Three techniques for automatic extraction of corpus callosum in structural midsagittal brain MR images: Valley Matching, Evolutionary Corpus Callosum Detection and Hybrid method

WOS: 000336474900011Corpus callosum (CC) is an important structure for medical image registration. We propose three novel fully automated for the extraction of CC. Our first algorithm, Valley matching (VM), is based on fixed searched range in histogram processing and uses prior anatomical information for locating CC. The second one, Evolutionary CC Detection (ECD), based on genetic algorithm presents a new fitness function that uses anatomical ratios, instead of fixed prior knowledge without the need for preprocessing. The final one, called Evolutionary Valley Matching (EVM), takes advantages of the strong points of the first and second algorithms. The search space defined for ECD is reduced by VM which uses crowding method to find the peaks in the multi-modal histogram. Another important contribution of this study is that there is no existing method using genetic algorithm for extracting CC. Our proposed algorithms perform with the success rates up to 95.5%. (C) 2013 Elsevier Ltd. All rights reserved