Shortest hop multipath algorithm for wireless sensor networks

AbstractShortest hop or distance path is one of the most common methods used for relaying messages in a wide variety of networks. It provides an efficient message relaying to destination in terms of energy and time. There are many algorithms for constructing shortest hop or distance path. However, according to our knowledge, no algorithm for constructing a shortest hop multipath for wireless sensor networks (WSNs) has yet been proposed in the literature. In this paper, we propose a novel distributed shortest hop multipath algorithm for WSNs in order to generate energy efficient paths for data dissemination or routing. The proposed algorithm generates shortest hop braided multipath to be used for fault-tolerance or load-balancing. It guarantees the BFS tree and generates near optimal paths in O(V.D+V) message complexity and O(D2) time complexity regarding the communication costs towards the sink after termination of algorithm

Görevdeş ağlarda gecikme metriği tabanlı hiyerarşik katman geliştirme üzerine bir çalışma

Günümüzde Internet üzerinden yapılan ve herhangi bir merkezi yapıya veya hiyerarsik kontrole ihtiyaç duymayan islemler ve iletisim ortamları, klasik dagıtık sistemlere göre büyük ölçüde daha karmasık hale gelmislerdir. Bu nedenle gelismekte olan görevdes aglara olan ilgi artmıstır ve görevdes aglar üzerinden yüksek kalitede video akıslandırma yapmak olanaklı hale gelmistir. Bu çalısmada, üstüne bindirmeli ag yapıları (overlay networks) incelenmis ve görevdes aglar için yeni bir mimari gelistirilmistir. Önerilen metot, sistemin kolay yönetilebilir olması için eslerin hiyerarsik bir yapı içerisinde kümelenmesine ve verimli bir içerik iletimi için bu hiyerarsik yapı üzerine kurulacak olan çoklu gönderim agacı temeline dayanmaktadır. Tasarlanan üstüne bindirmeli ag yapısında, eslerin kümelenmesi için kullanılan mekanizma, eslerin birbirleri ile ölçtükleri paket dolasım süresidir. Bu sayede ag topolojisi üzerinde birbirine yakın olan eslerin aynı küme içerisinde bulunması hedeflenmistir. Önerilen üstüne bindirmeli ag yapısı, Internet test ortamı olan PlanetLab üzerinde gerçeklenip kümeleme performansına bakılmıstır. Alınan test sonuçları, önerilen hiyerarsik üstüne bindirmeli ag yapısının, emsal düz yapılara göre daha iyi bir kümeleme yaptıgını göstermistir

Immune Plasma Algorithm: A Novel Meta-Heuristic for Optimization Problems

The recent global health crisis also known as the COVID-19 or coronavirus pandemic has attracted the researchers' attentions to a treatment approach called immune plasma or convalescent plasma once more again. The main idea lying behind the immune plasma treatment is transferring the antibody rich part of the blood taken from the patients who are recovered previously to the critical individuals and its efficiency has been proven by successfully using against great influenza of 1918, H1N1 flu, MERS, SARS and Ebola. In this study, we modeled the mentioned treatment approach and introduced a new meta-heuristic called Immune Plasma (IP) algorithm. The performance of the IP algorithm was investigated in detail and then compared with some of the classical and state-of-art meta-heuristics by solving a set of numerical benchmark problems. Moreover, the capabilities of the IP algorithm were also analyzed over complex engineering optimization problems related with the noise minimization of the electro-encephalography signal measurements. The results of the experimental studies showed that the IP algorithm is capable of obtaining better solutions for the vast majority of the test problems compared to other commonly used meta-heuristic algorithms

Experimental Analysis of Energy Efficient and QoS Aware Objective Functions for RPL Algorithm in IoT Networks

The Internet of Things (IoT) refers to smart devices with limited resources that connect to the Internet and transmit data. Routing is an important process in this structure, which can be described as the general frame of wireless sensor networks (WSNs). The Routing Protocol for Low-Power and Lossy Networks (RPL) is recommended by the Internet Engineering Task Force (IETF) to provide communication in resource-constrained networks and is designed for routing in IoT. Basically, it is the Internet Protocol Version 6 (IPv6) protocol developed based on the energy consumed by devices. The algorithm has an important place in the performance of the IoT network. In this paper, the performance of the RPL under different objective functions (OFs) is examined. OFs are symbolized and defined by detailed equations. This study provides an experimental analysis of the RPL algorithm. An overview of the RPL algorithm is also included. Finally, the RPL algorithm is simulated by a custom simulator which is performing on the application layer, created using the Python programming language. The algorithm’s behaviour in terms of different OFs such as throughput maximization, energy efficiency maximization and energy consumption minimization was observed and the results were evaluated under different parameters such as packet size, number of nodes and different signal-to-noise ratio (SNR) values. Our experimental results may be useful for both researchers and practitioners working in related fields

Bilişsel radyo ağlarında frekans atama, kanal zamanlama ve yönlendirme

Bu tez çalışmasında bilişsel radyo ağları üzerinde birden fazla kaynak ve hedef arasındaki yolları oluşturma, frekans atama, kanal zamanlama ve yönlendirme problemleri için yeni yaklaşımlar öne sürülmüş ve yeni algoritmalar geliştirilmiştir. Bu problemleri çözmek için tamsayılı doğrusal programlama ve sezgisel yöntemler kullanılmıştır. Tezin ilk bölümünde birden fazla kaynak ve hedef arasında maksimal kliklerden kaçınılarak çoklu isteklere cevap verebilecek alternatif yolların tespiti için bir algoritma önerilmiştir. İkinci bölümde, tamsayılı doğrusal programlama ile modellenen bilişsel radyo ağları üzerindeki frekans atama ve kanal zamanlama problemi için, bilişsel radyo cihazlarının farklı frekanslara geçişinden kaynaklı harcanan enerji tüketimini dikkate alan sezgisel bir algoritma tasarlanmıştır. Üçüncü bölümde, frekans geçiş gecikmesini dikkate alarak yolun kapasitesini maksimize eden bir yönlendirme algoritması önerilmiştir. Yönlendirme sırasında harcanan enerjinin tespit edilmesi için bir model tasarlanmış, enerji verimliliğini maksimize eden yeni bir amaç fonksiyonu ortaya konmuştur. Verimliliğin maksimize edilmesi için enerji verimliliğini dikkate alan polinom zamanlı yeni bir algoritma tasarlanmıştır.In this thesis, new approaches and algorithms for multi-source multi-destination path selection, frequency assignment, channel scheduling and routing problems are proposed. Integer linear programming and heuristic methods are used for solving these problems. In the first section of the thesis, a new algorithm is proposed to construct paths for multi-source multi-destination cognitive radio networks while avoiding maximal cliques. In the second section of the thesis, a heuristic algorithm is designed for frequency assignment and channel scheduling problem formulated as integer linear programming model in cognitive radio networks by taking into account the different energy consumption that occurs while cognitive radio devices switch to different frequency bands. In the third section of the thesis, a frequency switching aware throughput maximization routing algorithm is proposed. The energy consumption during the routing protocol is modeled, and a new objective function for the energy efficiency maximization problem is formulated. A novel algorithm is proposed for the energy efficiency maximization problem

An improved immune plasma algorithm with a regional pandemic restriction

The coronavirus (COVID-19) and its global effect have increased the interests of researchers from different disciplines to the medical methods such as immune or convalescent plasma treatment. Immune Plasma algorithm (IPA) that is the first meta-heuristic referencing the steps of the immune plasma treatment as the name implies has been proposed recently and its potential has been investigated. In this study, a pandemic management strategy based on limiting the free movements between regions was modeled and integrated into the workflow of the IPA and a new variant called regional IPA (rIPA) was introduced. For analyzing the contribution of the proposed method, twelve numerical benchmark problems were solved. Also, the performance of the rIPA was investigated by solving a new big data optimization problem that requires minimization of the measurement noise of electroencephalography signals. The results obtained by the rIPA were compared with the fourteen well-known and state-of-art meta-heuristics. Comparative studies showed that managing the relationship between the individuals of the population as in the proposed regional model significantly contributes to the capabilities and rIPA outperforms other meta-heuristics for most of the test cases

Solving UAV Localization Problem with Artificial Bee Colony (ABC) Algorithm

Driven by the wireless communication, sensor, vision system and battery technologies, unmanned aerial vehicles for short UAVs have started to be used for solving social, commercial or military applications including traffic surveillance, package transportation, wildlife research and critical area monitoring. In addition to the mentioned usage scenarios of the UAVs, an UAV or a set of UAVs can be successfully used as wireless base station or stations for the users inside a building when mobile cellular networks are down. In this study, wireless base station role is assigned to a UAV and its optimal location is tried to be determined with the Artificial Bee Colony (ABC) algorithm. Experimental studies carried out with different building scenarios showed that ABC algorithm is capable of finding more appropriate location for the UAV compared to the Particle Swarm Optimization (PSO) algorithm