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.

Bio-inspired computation: where we stand and what's next

In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

Bio-inspired computation: where we stand and what's next

In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

Air Force Institute of Technology Research Report 2007

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Applied (Meta)-Heuristic in Intelligent Systems

Engineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristic algorithms have emerged as the prevailing methods. A generic metaheuristic framework guides the course of search trajectories beyond local optimality, thus overcoming the limitations of traditional computation methods. The application of modern metaheuristics ranges from unmanned aerial and ground surface vehicles, unmanned factories, resource-constrained production, and humanoids to green logistics, renewable energy, circular economy, agricultural technology, environmental protection, finance technology, and the entertainment industry. This Special Issue presents high-quality papers proposing modern metaheuristics in intelligent systems

Preventing premature convergence and proving the optimality in evolutionary algorithms

http://ea2013.inria.fr//proceedings.pdfInternational audienceEvolutionary Algorithms (EA) usually carry out an efficient exploration of the search-space, but get often trapped in local minima and do not prove the optimality of the solution. Interval-based techniques, on the other hand, yield a numerical proof of optimality of the solution. However, they may fail to converge within a reasonable time due to their inability to quickly compute a good approximation of the global minimum and their exponential complexity. The contribution of this paper is a hybrid algorithm called Charibde in which a particular EA, Differential Evolution, cooperates with a Branch and Bound algorithm endowed with interval propagation techniques. It prevents premature convergence toward local optima and outperforms both deterministic and stochastic existing approaches. We demonstrate its efficiency on a benchmark of highly multimodal problems, for which we provide previously unknown global minima and certification of optimality

Heuristic algorithms for wireless mesh network planning

x, 131 leaves : ill. ; 29 cmTechnologies like IEEE 802.16j wireless mesh networks are drawing increasing attention of the research community. Mesh networks are economically viable and may extend services such as Internet to remote locations. This thesis takes interest into a planning problem in IEEE 802.16j networks, where we need to establish minimum cost relay and base stations to cover the bandwidth demand of wireless clients. A special feature of this planning problem is that any node in this network can send data to at most one node towards the next hop, thus traffic flow is unsplittable from source to destination. We study different integer programming formulations of the problem. We propose four types of heuristic algorithms that uses greedy, local search, variable neighborhood search and Lagrangian relaxation based approaches for the problem. We evaluate the algorithms on database of network instances of 500-5000 nodes, some of which are randomly generated network instances, while other network instances are generated over geometric distribution. Our experiments show that the proposed algorithms produce satisfactory result compared to benchmarks produced by generalized optimization problem solver software

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes