Based on Pause Time Comparative Analysis made among Bee-Ant Colony Optimized Routing (BACOR) Vs Existing Routing Protocols for Scalable Mobile Ad Hoc Networks (MANETs)

In this paper based on swarm intelligence a new approach for an on demand ad-hoc routing algorithm is proposed. The foraging behavior of Ant colony optimization and Bee colony optimization, which are the subset of swarm intelligence and considering the ability of simple ants to solve complex problems by cooperation. Several algorithms which are based on ant colony problems were introduced in the literatures to solve different problems, e.g., optimization problems. The proposed algorithm is compared and proven by results that the approach has the potential to become an appropriate routing tactics for mobile ad-hoc networks. The results were presented based on the simulations made with the implementation in ns-2. Keywords:BACOR, Bee Routing, Ant Routing, Bee-Ant Routin

QoS-Based Web Service Discovery in Mobile Ad Hoc Networks Using Swarm Strategies

Mobile ad hoc networks are noncentralised, multihop, wireless networks that lack a common infrastructure and hence require self-organisation. Their infrastructureless and dynamic nature entails the implementation of a new set of networking technologies in order to provide efficient end-to-end communication according to the principles of the standard TCP/IP suite. Routing, IP address autoconfiguration and Web service discovery are among the most challenging tasks in the ad hoc network domain. Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviours of insects, such as ants and bees. Self-organization, decentralization, adaptivity, robustness, and scalability make swarm intelligence a successful design paradigm for the above-mentioned problems. In this paper we proposeBeeAdHocServiceDiscovery, a new service discovery algorithm based on the bee metaphor, which also takes into account quality metrics estimates. The protocol has been specifically designed to work in mobile ad hoc network scenarios operating withBeeadhoc, a well-known routing algorithm inspired by nature. We present both the protocol strategy and the formal evaluation of the discovery overhead and route optimality metrics showing thatBeeAdHocServiceDiscoveryguarantees valuable performances even in large scale ad hoc wireless networks. Eventually, future research suggestions are sketched

Ant-based Routing Schemes for Mobile Ad hoc Networks

An ad-hoc network is a collection of mobile nodes, which communicate over radio. These networks have an important advantage; they do not require any existing infrastructure or central administration. Therefore, mobile ad-hoc networks are suitable for temporary communication links. This flexibility, however, comes at a price: communication is difficult to organize due to frequent topology changes. Routing in such networks can be viewed as a distributed optimization problem. A new class of algorithms, inspired by swarm intelligence, is currently being developed that can potentially solve numerous problems of modern communications networks. These algorithms rely on the interaction of a multitude of simultaneously interacting agents. A survey of few such algorithms for ad hoc networks is presented here

ACODV : Ant Colony Optimisation Distance Vector routing in ad hoc networks

A mobile ad hoc network is a collection of wireless mobile devices which dynamically form a temporary network, without using any existing network infrastructure or centralised administration. Each node in the network effectively becomes a router, and forwards packets towards the packet’s destination node. Ad hoc networks are characterized by frequently changing network topology, multi-hop wireless connections and the need for dynamic, efficient routing protocols. The overarching requirement for low power consumption, as battery powered sensors may be required to operate for years without battery replacement; An emphasis on reliable communication as opposed to real-time communication, it is more important for packets to arrive reliably than to arrive quickly; and Very scarce processing and memory resources, as these sensors are often implemented on small low-power microprocessors. This work provides overviews of routing protocols in ad hoc networks, swarm intelligence, and swarm intelligence applied to ad hoc routing. Various mechanisms that are commonly encountered in ad hoc routing are experimentally evaluated under situations as close to real-life as possible. Where possible, enhancements to the mechanisms are suggested and evaluated. Finally, a routing protocol suitable for such low-power sensor networks is defined and benchmarked in various scenarios against the Ad hoc On-Demand Distance Vector (AODV) algorithm.Dissertation (MSc)--University of Pretoria, 2005.Computer ScienceUnrestricte

A Review of Various Swarm Intelligence Based Routing Protocols for Iot

The paper provides insight into various swarm intelligence based routing protocols for Internet of Things (IoT), which are currently available for the Mobile Ad-hoc networks (MANETs) and wireless sensor networks (WSNs). There are several issues which are limiting the growth of Internet of Things. These include the reliability, link failures, routing, heterogeneity etc. The MANETs and WSNs routing issues impose almost same requirements for IoT routing mechanism. The recent work of the worldwide researchers is focused on this area. protocols are based on the principles of swarm intelligence. The swarm intelligence is applied to achieve the optimality and the efficiency in solving the complex, multi-hop and dynamic requirements of the wireless networks. The application of the ACO technique tries to provide answers to many routing issues. Using the swarm intelligence and ant colony optimization principles, it has been seen that, the protocols’ efficiency definitely increases and also provides more scope for the development of more robust, reliable and efficient routing protocols for the IoT. As the various standard protocols available for MANETs and WSNs are not reliable enough, the paper finds the need of some efficient routing algorithms for IoT

ESAHR: Energy Efficient Swarm Adaptive Hybrid Routing Topology for Mobile Ad hoc Networks

Ad hoc networks consist of independent self structured nodes. Nodes use a wireless medium for exchange their message or data, therefore two nodes can converse directly if and only if they are within each other2019;s broadcast range. Swarm intelligence submits to complex behaviors that occur from very effortless individual activities and exchanges, which is frequently experienced in nature, especially amongst social insects such as ants. Although each individual (an ant) has little intelligence and simply follows basic rules using local information gained from the surroundings, for instance ant2019;s pheromone track arranging and following activities, globally optimized activities, such as discovering a shortest route, appear when they work together as a group. In this regard in our earlier work we proposed a biologically inspired metaphor based routing in mobile ad hoc networks that referred as Swarm Adaptive Hybrid Routing (SAHR). . With the motivation gained from SAHR, here in this paper we propose a energy efficient swarm adaptive hybrid routing topology (ESAHR). The goal is to improve transmission performance along with energy conservation that used for packet transmission In this paper we use our earlier proposed algorithm that inspired from Swarm Intelligence to obtain these characteristics. In an extensive set of simulation tests, we evaluate our routing algorithm with state-of-the-art algorithm, and demonstrate that it gets better performance over a wide range of diverse scenarios and for a number of different assessment measures. In particular, we show that it scales better in energy conservation with the number of nodes in the network

Swarm intelligence and its applications to wireless ad hoc and sensor networks.

Swarm intelligence, as inspired by natural biological swarms, has numerous powerful properties for distributed problem solving in complex real world applications such as optimisation and control. Swarm intelligence properties can be found in natural systems such as ants, bees and birds, whereby the collective behaviour of unsophisticated agents interact locally with their environment to explore collective problem solving without centralised control. Recent advances in wireless communication and digital electronics have instigated important changes in distributed computing. Pervasive computing environments have emerged, such as large scale communication networks and wireless ad hoc and sensor networks that are extremely dynamic and unreliable. The network management and control must be based on distributed principles where centralised approaches may not be suitable for exploiting the enormous potential of these environments. In this thesis, we focus on applying swarm intelligence to the wireless ad hoc and sensor networks optimisation and control problems. Firstly, an analysis of the recently proposed particle swarm optimisation, which is based on the swarm intelligence techniques, is presented. Previous stability analysis of the particle swarm optimisation was restricted to the assumption that all of the parameters are non random since the theoretical analysis with the random parameters is difficult. We analyse the stability of the particle dynamics without these restrictive assumptions using Lyapunov stability and passive systems concepts. The particle swarm optimisation is then used to solve the sink node placement problem in sensor networks. Secondly, swarm intelligence based routing methods for mobile ad hoc networks are investigated. Two protocols have been proposed based on the foraging behaviour of biological ants and implemented in the NS2 network simulator. The first protocol allows each node in the network to choose the next node for packets to be forwarded on the basis of mobility influenced routing table. Since mobility is one of the most important factors for route changes in mobile ad hoc networks, the mobility of the neighbour node using HELLO packets is predicted and then translated into a pheromone decay as found in natural biological systems. The second protocol uses the same mechanism as the first, but instead of mobility the neighbour node remaining energy level and its drain rate are used. The thesis clearly shows that swarm intelligence methods have a very useful role to play in the management and control iv problems associated with wireless ad hoc and sensor networks. This thesis has given a number of example applications and has demonstrated its usefulness in improving performance over other existing methods

Kablosuz AD- HOC ağlar için oğul zekası tabanlı yeni bir yönlendirme protokolü

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.İletişim teknolojilerindeki gelişmeler kablosuz cihazların daha güçlü ve daha ucuz olmalarını sağlamıştır. Böylece hızlı teknolojik gelişmeler internete bağlanan cihaz sayısının artmasına sebep olmuştur. Hareketli Ad-Hoc ağlar, erişim noktası olmaksızın birbirleri ile iletişim kuran hareketli düğümlerden oluşur. Ad-Hoc ağlarda düğümlerin sürekli hareketinden dolayı sık sık topoloji değişikliği meydana gelir. Böylelikle Ad-Hoc ağlar kablolu ve erişim noktalı ağlara göre farklılıklar içerir. Ad-Hoc ağlar, genellikle internet alt yapısının kurulamadığı savaş, deprem ve sel gibi doğal afetlerde kullanılmaktadır. Son zamanlarda, hareketli Ad-Hoc ağlar pek çok araştırmacının ilgisini çekmiştir. Günümüzde hareketli Ad-Hoc ağlar akademik ve endüstri araştırmalarında sıklıkla kullanılmaktadır. Hareketli Ad-Hoc ağlarda araştırmacılar tarafından kabul edilen en önemli konulardan biri de yönlendirme protokolleridir. Yönlendirme protokolü geliştirme çalışması, kablosuz sistemlerde karmaşık, ölçeklenebilirlik, uyum, verimlilik ve pil ömrü gibi problemler ile ilgilenir. Kablosuz yönlendirme protokolleri bu sorunların üstesinden gelmek için geliştirilmiştir. Hareketli Ad-Hoc ağlarda ağ topolojisinin sürekli değişmesi bu ağlardaki yönlendirme protokollerinin diğerlerine göre farklı kılmıştır. Bu ağlarda kullanılacak yönlendirme protokolü ağdaki paket trafiğini arttırmayıp daha az paket kaybı ve gecikmeyle paketi kaynak düğümden hedef düğüme ulaştırmalıdır. Bunu yaparken de kullanılan protokol daha fazla paketi daha az enerji kullanarak hedef düğüme göndermelidir. Araştırmacılar tarafında birçok yönlendirme protokolü geliştirilmiştir. Bu protokollere örnek olarak ABR, SSR, DSDV, WRP, CGSR, OLSR, AODV, DSR, ZRP ve TORA verilebilir. Oğul zekâsı; termitler, arılar, karıncalar, kuşlar, balık sürüleri gibi aralarında etkileşim olan böceklerin veya diğer sosyal hayvanların topluluk halindeki davranışlarını örnek alarak, problemlere çözüm getirmeyi amaçlayan bir yapay zekâ tekniğidir. Oğul zekâsı biyolojik sistemler tarafından sunulmuştur ve mühendislik sistemlerinde ve ağ iletişiminde olduğu gibi birçok güçlü özellikler göstermiştir. Doğada biyolojik grup halinde yaşayan canlılar tarafından meydana getirilen oğul zekâsı, iletişim ağları gibi birçok mühendislik sistemlerinde istenen sayısız özellikler barındırır. Arılar, genellikle uzak mesafelere yiyecek bulmak amacıyla gitmek zorunda kalırlar. Yiyecek arama alanlarında besin kaynağı bulan arı kolonisinin diğer üyelerine haber vermek için kovana geri döner ve bir süre sonra diğer arıların etrafında uçarak besin kaynaklarının yerleri hakkında diğer arılara çeşitli danslarla bilgi verir. Bal arıları sağırdırlar ve bu nedenle birbirleri ile sesli iletişim kuramazlar. Birbiri ile iletişimlerini değişik şekilleri yerine getirerek kurarlar. Bu şekillere sallanma dansı denir. Bu dansta besin kaynağının kovana uzaklığı, yönü, besinin kalitesi ve miktarı hakkında bilgiler mevcuttur. Oğul zekâsı çözümleri dağıtık sistemlere ve ağ problemlerine uygulandıkları zaman ölçeklenebilirlik, hata toleransı, uyarlanabilirlik, modülerlik, paralellik ve otonomi gibi özelliklerinden dolayı geniş ve yüksek derecede dinamik sistemler için oldukça uygundur. Bu alanda geliştirilmiş protokollere örnek olarak ABC, AntNet, Adaptive-SDR, Beeadhoc algoritması ve Hopnet algoritması verilebilir. Bu tez çalışmasında, Ad-Hoc ağlardaki problemlere çözüm getirmek amacıyla; 1. Ad-Hoc ağlar için oğul zekâsı tabanlı yeni bir yönlendirme protokolü geliştirilmiştir. Geliştirilen bu protokol Bee-MANET olarak adlandırılmıştır. 2. Geliştirilen protokolü modellemek ve benzetimini yapmak amacıyla büyük ölçekli ağları destekleyen, model kütüphanesi zengin ve güçlü Ns-2 ağ simülatörü kullanılmıştır. 3. Geliştirilen protokolün üstünlüklerini göstermek amacıyla farklı ölçeklerden oluşan ağlar modellendi. Modellenen ağlar farklı trafik ve topolojilerde çalıştırılarak, geliştirilen Bee-MANET protokolü literatürdeki önemli protokoller olan AODV ve BeeAdhoc yönlendirme protokolü ile karşılaştırılarak başarımı incelendi. 4. Gerçekleştirilen uygulamalarda, geliştirilen yönlendirme protokolünün belirlenen problemlere çözüm getirdiği gözlemlendi.The development of communication technology has made wireless equipment's less, more powerful and less expensive. Such rapid technology improvement has contributed great growth to mobile devices connected to the Internet. Nodes communicate with each other without any center in ad hoc networks and have a constantly changing network topology. Due to the frequently changing network topology, mobile ad hoc networks utilize diverse routing protocols from other wireless systems. Wireless Mobile Ad Hoc Networks are used to provide communication in case of war and natural disasters such as earthquakes and flood. Recently, mobile ad hoc networks (MANETs) have drawn attention by many researchers At the present time, mobile ad hoc routing protocols are used in academic resources and industry. One of the main fields adopted by researchers studying on Mobile Ad-Hoc Networks is to develop routing protocols in wireless systems. Routing protocol development is related to complexity, scalability, adaptability, productivity, and battery life in wireless systems. Routing protocols for wireless systems are developed in order to cope with these problems. Due to the frequently changing network topology, mobile ad hoc networks utilize diverse routing protocols from other wireless systems. Frequently changing network topology causes constantly updating of routing tables and thus increases the number of control packets. The main part of every routing protocol is the routing protocol, which specifies all the logical processes of routing. In this process network traffic should not increase and should lose lesser number of packets, delay and battery life. Many routing protocols are developed by researchers such as ABR, SSR, DSDV, CGSR, WRP, OLSR, Beeadhoc, AODV, ZRP, TORA, AntNet, HOPNET and DSR. Swarm intelligence; termites, bees, ants, birds, fish, or as a swarm of insects which interact with each other in community with other social animals by imitating their behavior, which aims to bring solutions to the problems is an artificial intelligence techniques . Swarm intelligence has been inspired by biological systems and engineering intelligence systems and network communications, as demonstrated many powerful features. In nature, creatures that live in groups formed by biological swarm intelligence, many engineering systems such as communication networks, hosts numerous features desired. Bees usually have to go long distances to find food they order. Bees, when you find a source of food to give notice to the other members of the colony returns to the hive. After a while, bees flying around the other bees about the location of food sources with various dances inform the other bees. Honey bees are deaf and therefore cannot establish voice communication with each other. Establish communication with each other with their different dances. This way is called the swing dance. In this dance the barrel of the distance to the food source, direction, information about the quality and quantity of food available. Swarm intelligence solutions to problems when they are applied to distributed systems and network scalability, fault tolerance, adaptability, modularity, parallelism and autonomy of the properties are spacious and are well suited for highly dynamic systems. Examples of protocols developed in the art for example, ABC, Antnet, Adaptive-SDR, Beeadhoc Hopnet algorithm are given. In this thesis, routing protocols, network throughput and packet delivery ratio in order to solve problems such as; 1. A new routing protocol for Mobile Ad Hoc Networks has been developed by inspired swarm intelligence of the honey bees in order to bring solutions to network throughput and packet delivery ration. Developed protocol called Bee-MANET. 2. Bee-MANET has been compared to BeeAdhoc and AODV protocols which are most known protocols in the network community. Using the Ns-2 network, we develop simulation models of networks with varying topologies and scales. The results were presented as graphs and evaluated. 3. Different networks modeled to demonstrate the superiority of the developed protocol and were run in different traffic and topology. Bee-MANET, AODV, and Beeadhoc algorithms are empirically compared to research large-scale behavior. The results were presented as graphs and were evaluated. 4. Bee-MANET brings the solutions to the problems such as network throughput and packet delivery ratio