Cognitive radio (CR) is a cutting-edge wireless communication technology that adopts several existing communication concepts in order to efficiently utilize the spectrum and meet the users demands of high throughput and real-time systems. Conventionally, high throughput demands are met through adopting broadband and multi-antenna technologies such as, orthogonal frequency division multiplexing (OFDM) and Multi-Input Multi-Output (MIMO). Whereas, real-time application demands are met by analyzing metrics which characterize the delay limited channels, such as, outage probability over block-fading channels. Being an environmental friendly technology, energy efficiency metrics should be considered in the design of a CR application. This thesis tackles the energy efficiency of CR system from different aspects, utilizing different measuring metrics and constrains. Under the single-input single-output (SISO) OFDM we minimized the energy per goodbit (EPG) metric subject to several power and Quality of Service (QoS) constraints. In this approach, the minimum EPG metric is optimized via proposing two optimal and sub-optimal resource allocation schemes. We consider several parameters as optimization variables, such as, power policy, sensing threshold, and channel quality threshold. We also captured the impact of involving the media access control (MAC) layers parameters, such as, frame length, in the minimization of a modified EPG metric. Also, a MAC protocol, i.e., hybrid automatic repeat request (HARQ), and the associated power consumption of the retransmission mechanism is considered in the formulation of the problem. In this context, the optimal power and frame length are derived to minimize the modified EPG while considering several spectrum-sharing scenarios, which depend on sensing information. In MIMO based CR system, we maximized capacity to power ratio (CPR) (as an energy efficiency (EE) metric) subject to several power and QoS constraints. In this context, the impact of sensing information with imperfect channel state information (CSI) of the secondary channel has been considered. To realize a CR system with real-time applications we minimized the outage probability over M block-fading channel with several long-term and short-term energy constrains. We derive the minimum outage region and the associated optimal power. Tractable expressions to lower and upper bound the outage probability are derived. We then analyze the impact of utilizing the sensing process of primary user activity.

Through visual rhetoric analysis inspired by ”green communication” this essay aims to shed light on the differences in sustainability communication between two music festivals in Sweden. To be environmentally fatigued, to be tired of the environmental transition which is crucial for the survival of inhabitants of the earth, and the environment itself, is not ethically responsible. This essay strives to bring forward the specific aspects which inspire a festival with a sustainable profile, how it communicates, versus a festival with a non sustainable profile. One is found to use a rhetoric which promotes sustainability in an effective way, although the rhetoric is flawed by different factors of their communication. Another ignores the sustainability aspects completely in the rhetoric of their festival, and instead puts focus on energy, happiness and love, which contrasts against the apparent negative values they express.

Multi-radio multi-channel wireless mesh networks (WMNs) have been the focus of numerous research efforts during the past few years. These efforts aimed at extending the utilization of technologies based on the IEEE 802.11 standard in large-scale communities and even for city wide networking. However, mesh nodes in these networks are typically limited in their resources (e.g., bandwidth, power and radio interfaces). Such a limitation has led to an unsatisfactory network performance as well as users dissatisfaction. This dissertation addresses three important performance issues related to WMNs, namely, network performance enhancement, network survivability and green communications. To address the first issue, a novel quality of service (QoS) aware joint channel assignment (CA) and routing algorithm is developed. The proposed algorithm employs both dynamic and static CA techniques and corresponding link schedules that maximize the network throughput and minimize the delay and packet loss ratio. Next, the thesis addresses the problem of network survivability and theoretically analyzes the effects of node failure probabilities on the ability of the remaining network nodes to maintain their connectivity. A tight upper bound on the node failure probabilities needed to maintain full network connectivity on the one hand is first developed. On the other hand, a lower bound, at which the system loses connectivity, is also derived. We show that these bounds are dependent only on the nodes' geometric distribution and density. Based on the premise that failure of nodes in a small area may lead to failure of dependent nodes in other areas due to the quick divergence of traffic in these areas, an efficient node failure backup scheme is presented. The scheme relies on the capacity of the surviving network components in order to find new paths that do not overload the neighbours of the failed node which reduces the probability of generating congestion. Finally, the thesis addresses the problem of realizing energy-efficient WMNs that can operate using renewable energy sources. In these systems, batteries are often used to store and regulate the use of the supplied green energy to transmit the received data at each network router in order to overcome the problem of supply fluctuating of various energy sources. To realize these networks, the behaviour of the residual energy of the battery at a heavily loaded green wireless mesh node with a general traffic arrival and energy charging functions is first analyzed. Based on obtained theoretical results, both an online and an offline QoS aware packet scheduling schemes are proposed to minimize the probability of depleting the battery. Each of the aforementioned contributions is supported with various experimental evaluations to demonstrate the achieved performance enhancements.

This study explores what a company, that is working with sustainability or environmental issues, knows of their customers knowledge about this topic. How can this company get their customers more involved in sustainability issues and should they get them involved at all? This study was in collaboration with Big Image System (BIG) and data was collected and reviewed regarding the company’s recent social media activities on how they communicate their sustainability work to their customers. A survey was conducted and results show that most customers are aware of sustainability work in general and that the interest in environmental issues is high. They also show that distributing more relevant information to the customers is something the customers value and are interested in getting.

La consommation en énergie des réseaux de télécommunications a suscité un intérêt grandissant au cours des dernières années et les opérateurs mobiles cherchent des solutions innovantes pour optimiser l’efficacité énergétique. Dans cette thèse, nous nous focaliserons sur les schémas d’optimisation de la consommation d’énergie des réseaux d’accès mobiles. Nous commençons par étudier la stratégie de partage de charge qui minimise la consommation d’énergie dans la cellule tout en limitant l’impact sur la Qualité de Service. Le gain obtenu par ces algorithmes de gestion des ressources radio reste cependant limité; ceci est dû au fait que la consommation d’énergie ne dépend pas que de la charge, mais comporte une importante partie constante. Pour obtenir un gain plus important, nous proposons la mise en veille de certaines ressources du réseaux aux heures creuses où le trafic est faible, ce qui mène à des gains substantiels. Nous proposons ensuite un contrôleur de gestion de la mise en veille qui choisit l’action optimale en fonction de l’état du réseau. En effet, l’activation d’une nouvelle ressource n’est pas instantanée et un effet ping-pong peut apparaitre suite aux commandes simultanées d’activation/désactivation des ressources. Nous adaptons nos contrôleurs afin de prendre en compte ces imperfections, et nous montrons comment déduire la politique optimale. Nous étudions ensuite le cas de déploiement de petites cellules dans des réseaux hétérogènes et montrons que leur efficacité énergétique est améliorée par rapport au réseau purement macro-cellulaire, pourvu que la consommation d’énergie de petites cellules reste faible. Nous proposons ensuite un contrôleur optimal qui active/désactive les petites cellules en se basant sur des informations de trafic et de localisation des usagers. Nous considérons différents cas de figure avec une information complète, partielle ou retardée et montrons que ces schémas de mise en veille permettent d’atteindre d’importants gains de consommation d’énergie / In the recent years, more importance has been given to the energy consumption issue in telecommunication networks and mobile operators are rethinking their network design for optimizing its energy efficiency. In this thesis, we propose schemes for optimizing the energy consumption of mobile access networks. We begin by proposing energy-aware Radio Resource Management (RRM) schemes and show that a load balancing between available resources gives some energy savings. However, these gains remain small as a large part of the energy consumption is load-independent. We thus propose sleep mode schemes of resources in the network (cells or carriers) and show that they give a large gain when traffic is low. We then propose optimal sleep mode controllers that give, for each traffic scenario, the best actions to take in each state of the network. We make two observations: the first is that activating a new resource is not instantaneous, leading to QoS degradation if a conservative policy is not considered, and the second is that a ping-pong effect may appear at the frontier between two capacity regions. We adapt our controllers to take into account these imperfections, and show how to derive the optimal policy using Markov decision theory. We then extend our works to the case of small cell deployment in heterogeneous networks, composed of macro and small cells base stations. We study the capacity and power consumption of these networks and show that the energy efficiency is increased for some deployment strategies when the power consumption of small cells is low. We then propose sleep mode for small cells and develop optimal sleep/wakeup schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. We show that these sleep mode schemes achieve large energy consumption gains

Face à l'explosion du trafic mobile entraînée par le succès des smartphones, les opérateurs de réseaux mobiles (MNOs) densifient leurs réseaux à travers le déploiement massif des stations de base à faible portée (SBS), capable d’offrir des services très haut débit et de remplir les exigences de capacité et de couverture. Cette nouvelle infrastructure, appelée réseau cellulaire hétérogène (HetNet), utilise un mix de stations de base hiérarchisées, comprenant des macro-cellule à forte puissance et des SBS à faible puissance.La prolifération des HetNets soulève une nouvelle préoccupation concernant leur consommation d'énergie et empreinte carbone. Dans ce contexte, l'utilisation de technologies de production d'énergie dans les réseaux mobiles a suscité un intérêt particulier. Les sources d'énergie respectueuses de l'environnement couplées à un système de stockage d'énergie ont le potentiel de réduire les émissions carbone ainsi que le coût opérationnel énergétique des MNOs.L'intégration des énergies renouvelables (panneau solaire) et du stockage d'énergie (batterie) dans un SBS gagne en efficacité grâce aux leviers technologiques et économiques apportés par le smart grid (SG). Cependant, l'architecture résultante, que nous appelons Green Small-Cell Base station (GSBS), est complexe. Premièrement, la multitude de sources d'énergie, le phénomène de viellissement du système et le prix dynamique de l'électricité dans le SG sont des facteurs qui nécessitent planification et gestion pour un fonctionnement plus efficace du GSBS. Deuxièmement, il existe une étroite dépendance entre le dimensionnement et le contrôle en temps réel du système, qui nécessite une approche commune capable de résoudre conjointement ces deux problèmes. Enfin, la gestion holistique d’un HetNet nécessite un schéma de contrôle à grande échelle pour optimiser simultanément les ressources énergétiques locales et la collaboration radio entre les SBSs.Par conséquent, nous avons élaboré un cadre d'optimisation pour le pré-déploiement et le post-déploiement du GSBS, afin de permettre aux MNOs de réduire conjointement leurs dépenses d'électricité et le vieillissement de leurs équipements. L'optimisation pré-déploiement consiste en un dimensionnement du GSBS qui tient compte du vieillissement de la batterie et de la stratégie de gestion des ressources énergétiques. Le problème associé est formulé et le dimensionnement optimal est approché en s'appuyant des profils moyens (production, consommation et prix de l'électricité) à travers une méthode itérative basée sur le solveur non-linéaire “fmincon”. Le schéma de post-déploiement repose sur des capacités d'apprentissage permettant d'ajuster dynamiquement la gestion énergétique du GSBS à son environnement (conditions météorologiques, charge de trafic et coût de l'électricité). La solution s'appuie sur le fuzzy Q-learning qui consiste à combiner le système d'inférence floue avec l'algorithme Q-learning. Ensuite, nous formalisons un système d'équilibrage de charge capable d'étendre la gestion énergétique locale à une collaboration à l'échelle réseau. Nous proposons à ce titre un algorithme en deux étapes, combinant des contrôleurs hiérarchiques au niveau du GSBS et au niveau du réseau. Les deux étapes s'alternent pour continuellement planifier et adapter la gestion de l'énergie à la collaboration radio dans le HetNet.Les résultats de la simulation montrent que, en considérant le vieillissement de la batterie et l'impact mutuel de la conception du système sur la stratégie énergétique (et vice-versa), le dimensionnement optimal du GSBS est capable de maximiser le retour sur investissement. En outre, grâce à ses capacités d'apprentissage, le GSBS peut être déployé de manière plug-and-play, avec la possibilité de s'auto-organiser, d'améliorer le coût énergétique du système et de préserver la durée de vie de la batterie. / Pushed by an unprecedented increase in data traffic, Mobile Network Operators (MNOs) are densifying their networks through the deployment of Small-cell Base Stations (SBS), low-range radio-access transceivers that offer enhanced capacity and improved coverage. This new infrastructure – Heterogeneous cellular Network (HetNet) -- uses a hierarchy of high-power Macro-cell Base Stations overlaid with several low-power (SBSs).The augmenting deployment and operation of the HetNets raise a new crucial concern regarding their energy consumption and carbon footprint. In this context, the use of energy-harvesting technologies in mobile networks have gained particular interest. The environment-friendly power sources coupled with energy storage capabilities have the potential to reduce the carbon emissions as well as the electricity operating expenditures of MNOs.The integration of renewable energy (solar panel) and energy storage capability (battery) in SBSs gain in efficiency thanks to the technological and economic enablers brought by the Smart Grid (SG). However, the obtained architecture, which we call Green Small-Cell Base Station (GSBS), is complex. First, the multitude of power sources, the system aging, and the dynamic electricity price in the (SG) are factors that require design and management to enable the (GSBS) to efficiently operate. Second, there is a close dependence between the system sizing and control, which requires an approach to address these problems simultaneously. Finally, the achievement of a holistic management in a (HetNet) requires a network-level energy-aware scheme that jointly optimizes the local energy resources and radio collaboration between the SBSs.Accordingly, we have elaborated pre-deployment and post-deployment optimization frameworks for GSBSs that allow the MNOs to jointly reduce their electricity expenses and the equipment degradation. The pre-deployment optimization consists in an effective sizing of the GSBS that accounts for the battery aging and the associated management of the energy resources. The problem is formulated and the optimal sizing is approximated using average profiles, through an iterative method based on the non-linear solver “fmincon”. The post-deployment scheme relies on learning capabilities to dynamically adjust the GSBS energy management to its environment (weather conditions, traffic load, and electricity cost). The solution is based on the fuzzy Q-learning that consists in tuning a fuzzy inference system (which represents the energy arbitrage in the system) with the Q-learning algorithm. Then, we formalize an energy-aware load-balancing scheme to extend the local energy management to a network-level collaboration. We propose a two-stage algorithm to solve the formulated problem by combining hierarchical controllers at the GSBS-level and at the network-level. The two stages are alternated to continuously plan and adapt the energy management to the radio collaboration in the HetNet.Simulation results show that, by considering the battery aging and the impact of the system design and the energy strategy on each other, the optimal sizing of the GSBS is able to maximize the return on investment with respect to the technical and economic conditions of the deployment. Also, thanks to its learning capabilities, the GSBSs can be deployed in a plug-and-play fashion, with the ability to self-organize, improve the operating energy cost of the system, and preserves the battery lifespan.

Responsible production is a subject of increasing importance for companies toadopt and communicate to their environment and many companies choose to implementenvironmental – and ethic considerations into their brand strategy. There is, however, adividing line between companies according to what extent they choose to implementresponsible production into their brand strategy and to which extent they choose tocommunicate it to their stakeholders and surroundings. It is the hypothesis about a dividingline that is the foundation for this essay and something we believed could be interesting forfurther analysis.The purpose of our essay is to find out how the brand strategy of a company is affected by theresponsible production and in what extent they communicate it to their environment. Byanswering those questions we hope to find out why some companies communicateresponsible production more actively than others.We have conducted in-depth interviews with the Swedish clothing companies; MariaWesterlind, Zion and Dem Collective and we have through our analysis reached interestingconclusions. It is evident that the more distinct the company positions itself regarding theenvironment, the more important the responsible production seems to be to the brand strategy.This affects in what way and to what extent the company chooses to communicate with thecustomers. In other words, the bigger environmental exposure and the bigger environmentalmarket possibilities the more important and more active the communication gets.Those companies that have responsible production as a primary brand value also tend tocommunicate this in greater extent than other companies although there is not always aconnection. The greater control the company has over the supply chain, the more distinct thecommunication becomes. The majority of the companies use external certifications as a formof sponsorship to get certain benefits. We also have noticed that the more distinct thecompany communicate their responsible production, the more important the extent of theinformation to the customer gets. / <p>Program: Textilekonomutbildningen</p><p>Uppsatsnivå: C</p>

La investigación persigue un doble objetivo. El primero, aproximar el complejo y poliédrico paradigma de la ecología a la disciplina publicitaria; y el segundo, identificar y analizar la Publicidad Verde más representativa de los últimos veinte años en España. El trabajo se estructura en dos partes: en la primera, además de desvelarse vínculos entre la publicidad y la ecología -casi siempre mediante el consumo-, se desentrama la maraña epistemológica y etimológica en relación al medioambientalismo, al ecologismo y a la naturaleza. La segunda, el trabajo empírico, consiste en un análisis empírico de contenido sobre la Publicidad Verde insertada entre 1980 y 1999 en España. Se efectúa un análisis transdimensional de la Publicidad Verde (1.280 inserciones de muestra), en el que se aborda el objeto de estudio atendiendo a cinco dimensiones de análisis: 1,- Análisis temporal 2,- Análisis sectorial 3,- Análisis en función del tipo de publicidad (corporativa o de producto) 4,- Análisis terminológico 5,- Análisis en función de la estructura del anuncio. Acerca de la segunda dimensión, se pone especial énfasis en los sectores "con mayor deuda ecológica". Y sobre la cuarta dimensión, la terminológica, se propone y se realiza un análisis segmentado del concepto de "lo verde", vertebrándolo en seis universos específicos: el de la Naturaleza (UNAT), el de la Ecología (UECO), el del Medio Ambiente (UMED), el de la Energía (UENEG), el de la jerga científico-técnica y de la sostenibilidad (UCIENT) y el de las 3 R's -Reducir, reutilizar y reciclar- (U3R's).

In the light of a market that showcases increased hesitation and skepticism over green marketing and environmental communication, is the necessity of a well executed corporate communication greater than ever. What can be seen on the market is corporations that are unintentionally using motive greenwashing as a tool for attracting and persuading consumers to favour the corporations image. Prior research within green marketing has put a large focus on greenwashing in product context and the effects of it on consumer behaviour. In this study greenwashing is examined in a communication context and its effect on different aspects of consumer behaviour and attitude.

There has been a huge surge in the Internet of Things (IoT) applications in recent years. The sensor nodes in the IoT network generate data continuously that directly affects the longevity of the network. Even though the potential of IoT applications are immense, there are numerous challenges like security, privacy, load balancing, storage, heterogeneity of devices, and energy optimization that have to be addressed. Of those, the energy utilization of the network is of importance and has to be optimized. Several factors like residual energy, temperature, the load of Cluster Head (CH), number of alive nodes, and cost function affect the energy consumption of sensor nodes. In this paper, a hybrid Whale Optimization Algorithm-Moth Flame Optimization (MFO) is designed to select optimal CH, which in turn optimizes the aforementioned factors. The performance of the proposed work is then evaluated with existing algorithms with respect to the energy-specific factors. The results obtained prove that the proposed method outperforms existing approaches.