Telecommunications Network Planning and Maintenance

Telecommunications network operators are on a constant challenge to provide new services which require ubiquitous broadband access. In an attempt to do so, they are faced with many problems such as the network coverage or providing the guaranteed Quality of Service (QoS). Network planning is a multi-objective optimization problem which involves clustering the area of interest by minimizing a cost function which includes relevant parameters, such as installation cost, distance between user and base station, supported traffic, quality of received signal, etc. On the other hand, service assurance deals with the disorders that occur in hardware or software of the managed network. This paper presents a large number of multicriteria techniques that have been developed to deal with different kinds of problems regarding network planning and service assurance. The state of the art presented will help the reader to develop a broader understanding of the problems in the domain

A new QoS Routing Architecture in NGI

After a thorough understanding of the relevant research knowledge and the key theory of NGN, I describe the research objectives and the recent development of the QoS routing in this thesis. QoS routing is regarded as the key part in the problem of the next generation of integrated-service network. A new routing algorithm is put forward in this thesis, which is better than OSPF in some aspects. As for the experiment, NS2 is chosen as the simulation environment, and some other experimental results are also included to manifest its strongpoint. The development and requirement of NGN is described in Chapter One; The definition and types of routing and the basic theories of QoS routing are described in Chapter Two; The development and research method of QoS are focused in Chapter Three. The new routing algorithm and simulation is proposed in Chapter Four

A green intelligent routing algorithm supporting flexible QoS for many-to-many multicast

The tremendous energy consumption attributed to the Information and Communication Technology (ICT) field has become a persistent concern during the last few years, attracting significant academic and industrial efforts. Networks have begun to be improved towards being “green”. Considering Quality of Service (QoS) and power consumption for green Internet, a Green Intelligent flexible QoS many-to-many Multicast routing algorithm (GIQM) is presented in this paper. In the proposed algorithm, a Rendezvous Point Confirming Stage (RPCS) is first carried out to obtain a rendezvous point and the candidate Many-to-many Multicast Sharing Tree (M2ST); then an Optimal Solution Identifying Stage (OSIS) is performed to generate a modified M2ST rooted at the rendezvous point, and an optimal M2ST is obtained by comparing the original M2ST and the modified M2ST. The network topology of Cernet2, GéANT and Internet2 were considered for the simulation of GIQM. The results from a series of experiments demonstrate the good performance and outstanding power-saving potential of the proposed GIQM with QoS satisfied

Prediction-based Decentralized Routing Algorithm

We introduce a new efficient routing algorithm called Prediction-based Decentralized Routing algorithm (PDR), which is based on the Ant Colony Optimization (ACO) meta-heuristics. In our approach, an ant uses a combination of the link state information and the predicted link load instead of the ant's trip time to determine the amount of pheromone to deposit. A Feed Forward Neural Network (FFNN) is used to build adaptive traffic predictors which capture the actual traffic behaviour. We study two performance parameters: the rejection ratio and the percentage of accepted bandwidth under two different network load conditions. We show that our algorithm reduces the rejection ratio of requests and achieves a higher throughput when compared to Shortest Path First and Widest Shortest Path algorithms

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

The Application of Ant Colony Optimization

The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance

Optimising routing and trustworthiness of ad hoc networks using swarm intelligence

This thesis was submitted for the degree of Doctor of Philsophy and awarded by Brunel UniversityThis thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes

A Review on Swarm Intelligence Based Routing Approaches

The principles of bio-inspired or swarm intelligence algorithms can be effectively used to achieve optimal solutions in routing for complex and dynamic wireless sensor networks or body area networks. As the name indicates, it is a field that is inspired by natural living beings like ants, bees, fishes, etc. Studies have proved that the routing protocols based on such bio-inspired methods perform better in terms of energy efficiency, reliability, adaptivity, scalability, and robustness. The general classification of routing protocols is classical-based and swarm-based routing protocols, where both the protocols were specifically categorized as data-centric, location-aware, hierarchical and network flow, and QoS aware protocols. In this paper, an evocative taxonomy and comparison of various swarm-based routing algorithms are presented. A brief discussion about the sensor network design and the major factors that influence the routing is also discussed. The comparative analysis of the selected swarm-based protocols is also done with respect to routing characteristics like query based, route selection, energy efficiency, and path selection. From the review, it is observed that the selection of a routing protocol is application dependent. This paper will be helpful to the researchers as a reference on bio-inspired algorithms for new protocol designs and also for the proper selection of routing protocols according to the type of applications

A Review on Swarm Intelligence Based Routing Approaches

The principles of bio-inspired or swarm intelligence algorithms can be effectively used to achieve optimal solutions in routing for complex and dynamic wireless sensor networks or body area networks. As the name indicates, it is a field that is inspired by natural living beings like ants, bees, fishes, etc. Studies have proved that the routing protocols based on such bio-inspired methods perform better in terms of energy efficiency, reliability, adaptivity, scalability, and robustness. The general classification of routing protocols is classical-based and swarm-based routing protocols, where both the protocols were specifically categorized as data-centric, location-aware, hierarchical and network flow, and QoS aware protocols. In this paper, an evocative taxonomy and comparison of various swarm-based routing algorithms are presented. A brief discussion about the sensor network design and the major factors that influence the routing is also discussed. The comparative analysis of the selected swarm-based protocols is also done with respect to routing characteristics like query based, route selection, energy efficiency, and path selection. From the review, it is observed that the selection of a routing protocol is application dependent. This paper will be helpful to the researchers as a reference on bio-inspired algorithms for new protocol designs and also for the proper selection of routing protocols according to the type of applications