CORNETO: A Software System for Simulating and Optimizing Optical Networks

In this paper we present a software system that is being developed at the University of Leeds for simulating and optimizing energy efficient optical core networks. The system is called CORNETO, an acronym for CORe NETwork Optimization. The software implements many of the energy saving concepts, methods and computational heuristics that have been produced by the ongoing INTERNET, INTelligent Energy awaRe NETworks, project. The main objective of the software is to help network operators and planners green their networks while maintaining quality of service. In this paper we briefly describe the software and demonstrate its capabilities with two case studies

Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks

The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques. Among the candidates, pure reluctance and anisotropic permanent magnet motors are gaining popularity, despite their complex structure. The availability of accurate mathematical models that describe these motors is essential to the design of any model-based advanced control. This paper focuses on the relations between currents and flux linkages, which are obtained through innovative radial basis function neural networks. These special drive-oriented neural networks take as inputs the motor voltages and currents, returning as output the motor flux linkages, inclusive of any nonlinearity and cross-coupling effect. The theoretical foundations of the radial basis function networks, the design hints, and a commented series of experimental results on a real laboratory prototype are included in this paper. The simple structure of the neural network fits for implementation on standard drives. The online training and tracking will be the next steps in field programmable gate array based control systems

An energy-aware resource design model for constrained networks

The Internet of Things is expected to incorporate objects and sensor networks of all kinds, and in particular, constrained sensor networks where energy consumption is a critical issue. In order to increase the lifetime of such networks, intelligent and standard-based solutions should be used. Here, we address this challenge through the use of CoRE interfaces for the resource design. These interfaces allow the server side to compose/organize resources and the client side to discover and determine how to consume such resources, besides allowing decisions to be easily integrated into the operation of the network. An energy-aware resource design model is proposed, based on CoRE interfaces, for the design of resources matching client needs. Based on this model, we develop an algorithm that proved to be energy efficient

Intelligent Green Communication Network for Internet of Things

The text covers the advanced and innovative concept of green communication networks using the Internet of Things in different fields including cloud technology, agriculture, the automobile sector, and robotics. It will also help readers in learning the efficient use of sensors and devices in the Internet of Things networks. The text covers 5G communication and its application for intelligent and green network-enabled Internet of Things. This book • Discusses intelligent and green networking-enabled Internet of Things • Covers architectures and models for intelligent and green communication networks-enabled Internet of Things • Discusses designing Internet of Things devices that help in reducing the emissions of CO2 in the environment and energy consumption • Highlights green computing approach and green communication network designs and implementations for Internet of Things ecosystem • Includes studies on energy-aware systems, technologies, and green communication This book comprehensively discusses recent advances and applications in the area of green Internet of Things communication in a single volume. It will serve as an ideal reference text for senior undergraduate and graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology

An Intelligent Routing Protocol Based on DYMO for MANET

in this paper, intelligent routing protocols for mobile ad-hoc networks (MANET) will be proposed .Depending on the concepts of fuzzy and neural networks. The goal is to get good quality service by finding the most convenient data transfer paths, therefore a Fuzzy-based, Neural-Fuzzy based and Energy aware are three approaches have been proposed to enhance Dynamic Manet On-demand (DYMO),All approaches were implemented in ns-2 simulator and compared with original protocol in terms of performance metrics, which showed that there was an improvement in route efficiency

Towards Intelligent Energy-Aware Self-Organised Cellular Networks (iSONs)

This thesis investigates the application of intelligent energy-aware resource management techniques for current and future wireless broadband deployments. Energy-aware topology management is firstly studied aiming at dynamically managing the network topology by fine tuning the status of network entities (dormant / active) to scale the energy consumption with traffic demands. This is studied through an analytical model based on queueing theory and through simulation to help understand its operational capabilities under a range of traffic conditions. Advanced radio resource management is also investigated. This reduces the number of nodes engaged in the service whenever possible reducing the energy consumption at low and medium traffic loads while enhancing system capacity and QoS when the traffic load is high. As an enabling technology for self-awareness and adaptability, Reinforcement Learning (RL) is applied to manage network resources in an intelligent, self-aware, and adaptable manner. This is complemented with a range of novel cognitive learning and reasoning algorithms which are capable of translating past experience into valuable sets of information in order to optimise decisions taken as part of the radio resource and topology management functionalities. Dependencies between the proposed techniques are also addressed formulating an intelligent self-adaptable approach, which is capable of dynamically deactivating redundant nodes and redirecting traffic appropriately while enhancing system capacity and QoS

MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy