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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

Energy Efficient Offloading for Competing Users on a Shared Communication Channel

Meskar, Erfan January 2016 (has links)
In this thesis we consider a set of mobile users that employ cloud-based computation offloading. In computation offloading, user energy consumption can be decreased by uploading and executing jobs on a remote server, rather than processing the jobs locally. In order to execute jobs in the cloud however, the user uploads must occur over a base station channel which is shared by all of the uploading users. Since the job completion times are subject to hard deadline constraints, this restricts the feasible set of jobs that can be remotely processed, and may constrain the users ability to reduce energy usage. The system is modelled as a competitive game in which each user is interested in minimizing its own energy consumption. The game is subject to the real-time constraints imposed by the job execution deadlines, user specific channel bit rates, and the competition over the shared communication channel. The thesis shows that for a variety of parameters, a game where each user independently sets its offloading decisions always has a pure Nash equilibrium, and a Gauss-Seidel method for determining this equilibrium is introduced. Results are presented which illustrate that the system always converges to a Nash equilibrium using the Gauss-Seidel method. Data is also presented which show the number of Nash equilibria that are found, the number of iterations required, and the quality of the solutions. We find that the solutions perform well compared to a lower bound on total energy performance. / Thesis / Master of Applied Science (MASc)
22

RESOURCE MANAGEMENT FOR MOBILE COMPUTATION OFFLOADING

Chen, Hong 11 1900 (has links)
Mobile computation offloading (MCO) is a way of improving mobile device (MD) performance by offloading certain task executions to a more resourceful edge server (ES), rather than running them locally on the MD. This thesis first considers the problem of assigning the wireless communication bandwidth and the ES capacity needed for this remote task execution, so that task completion time constraints are satisfied. The objective is to minimize the average power consumption of the MDs, subject to a cost budget constraint on communication and computation resources. The thesis includes contributions for both soft and hard task completion deadline constraints. The soft deadline case aims to create assignments so that the probability of task completion time deadline violation does not exceed a given violation threshold. In the hard deadline case, it creates resource assignments where task completion time deadlines are always satisfied. The problems are first formulated as mixed integer nonlinear programs. Approximate solutions are then obtained by decomposing the problems into a collection of convex subproblems that can be efficiently solved. Results are presented that demonstrate the quality of the proposed solutions, which can achieve near optimum performance over a wide range of system parameters. The thesis then introduces algorithms for static task class partitioning in MCO. The objective is to partition a given set of task classes into two sets that are either executed locally or those classes that are permitted to contend for remote ES execution. The goal is to find the task class partition that gives the minimum mean MD power consumption subject to task completion deadlines. The thesis generates these partitions for both soft and hard task completion deadlines. Two variations of the problem are considered. The first assumes that the wireless and computational capacities are given and the second generates both capacity assignments subject to an additional resource cost budget constraint. Two class ordering methods are introduced, one based on a task latency criterion, and another that first sorts and groups classes based on a mean power consumption criterion and then orders the task classes within each group based on a task completion time criterion. A variety of simulation results are presented that demonstrate the excellent performance of the proposed solutions. The thesis then considers the use of digital twins (DTs) to offload physical system (PS) activity. Each DT periodically communicates with its PS, and uses these updates to implement features that reflect the real behaviour of the device. A given feature can be implemented using different models that create the feature with differing levels of system accuracy. The objective is to maximize the minimum feature accuracy for the requested features by making appropriate model selections subject to wireless channel and ES resource availability. The model selection problem is first formulated as an NP-complete integer program. It is then decomposed into multiple subproblems, each consisting of a modified Knapsack problem. A polynomial-time approximation algorithm is proposed using dynamic programming to solve it efficiently, by violating its constraints by at most a given factor. A generalization of the model selection problem is then given and the thesis proposes an approximation algorithm using dependent rounding to solve it efficiently with guaranteed constraint violations. A variety of simulation results are presented that demonstrate the excellent performance of the proposed solutions. / Thesis / Doctor of Philosophy (PhD) / Mobile devices (MDs) such as smartphones are currently used to run a wide variety of application tasks. An alternative to local task execution is to arrange for some MD tasks to be run on a remote non-mobile edge server (ES). This is referred to as mobile computation offloading (MCO). The work in this thesis studies two important facets of the MCO problem. 1. The first considers the joint effects of communication and computational resource assignment on task completion times. This work optimizes task offloading decisions, subject to task completion time requirements and the cost that one is willing to incur when designing the network. Procedures are proposed whose objective is to minimize average mobile device power consumption, subject to these cost constraints. 2. The second considers the use of digital twins (DTs) as a way of implementing mobile computation offloading. A DT implements features that describe its physical system (PS) using models that are hosted at the ES. A model selection problem is studied, where multiple DTs share the execution services at a common ES. The objective is to optimize the feature accuracy obtained by DTs subject to the communication and computation resource availability. The thesis proposes different approximation and decomposition methods that solve these problems efficiently.
23

Binary Multi-User Computation Offloading via Time Division Multiple Access

Manouchehrpour, Mohammad Amin January 2023 (has links)
The limited energy and computing power of small smart devices restricts their ability to support a wide range of applications, especially those needing quick responses. Mobile edge computing offers a potential solution by providing computing resources at the network access points that can be shared by the devices. This enables the devices to offload some of their computational tasks to the access points. To make this work well for multiple devices, we need to judiciously allocate the available communication and computing resources among the devices. The main focus of this thesis is on (near) optimal resource allocation in a K-user offloading system that employs the time division multiple access (TDMA) scheme. In this thesis, we develop effective algorithms for the resource allocation problem that aim to minimize the overall (cost of the) energy that the devices consume in completing their computational tasks within the specified deadlines while respecting the devices' constraints. This problem is tackled for tasks that cannot be divided and hence the system must make a binary decision as to whether or not a task should be offloaded. This implies the need to develop an effective decision-making algorithm to identify a suitable group of devices for offloading. This thesis commences by developing efficient communication resource algorithms that incorporate the impact of integer finite block length in low-latency computational offloading systems with reserved computing resources. In particular, it addresses the challenge of minimizing total energy consumption in a binary offloading scenario involving K users. The approach considers different approximations of the fundamental rate limit in the finite block length regime, departing from the conventional asymptotic rate limits developed by Shannon. Two such alternatives, namely the normal approximation and the SNR-gap approximation, are explored. A decomposition approach is employed, dividing the problem into an inner component that seeks an optimal solution for the communication resource allocation within a defined set of offloading devices, and an outer component aimed at identifying a suitable set of offloading devices. Given the finiteness of the block length and its integer nature, various relaxation techniques are employed to determine an appropriate communication resource allocation. These include incremental and independent roundings, alongside an extended search that utilizes randomization-based methods in both rounding schemes. The findings reveal that incremental randomized rounding, when applied to the normal approximation of the rate limits, enhances system performance in terms of reducing the energy consumption of the offloading users. Furthermore, customized pruned greedy search techniques for selecting the offloading devices efficiently generate good decisions. Indeed, the proposed approach outperforms a number of existing approaches. In the second contribution, we develop efficient algorithms that address the challenge of jointly allocating both computation and communication resources in a binary offloading system. We employ a similar decomposition methodology as in the previous work to perform the decision-making, but this is now done along with joint computation and communication resource allocation. For the inner resource allocation problem, we divide the problem into two components: determining the allocation of computation resources and the optimal allocation of communication resources for the given allocation of computation resources. The allocation of the computation resources implicitly determines a suitable order for data transmission, which facilitates the subsequent optimal allocation of the communication resources. In this thesis, we introduce two heuristic approaches for allocating the computation resources. These approaches sequentially maximize the allowable transmission time for the devices in sequence, starting from the largest leading to a reduction in total offloading energy. We demonstrate that the proposed heuristics substantially lower the computational burden associated with solving the joint computation--communication resource allocation problem while maintaining a low total energy. In particular, its use results in substantially lower energy consumption than other simple heuristics. Additionally, the heuristics narrow the energy gap in comparison to a fictitious scenario in which each task has access to the whole computation resource without the need for sharing. / Thesis / Master of Applied Science (MASc)
24

Remote Software Guard Extension (RSGX)

Sundarasamy, Abilesh 21 December 2023 (has links)
With the constant evolution of hardware architecture extensions aimed at enhancing software security, a notable availability gap arises due to the proprietary nature and design-specific characteristics of these features, resulting in a CPU-specific implementation. This gap particularly affects low-end embedded devices that often rely on CPU cores with limited resources. Addressing this challenge, this thesis focuses on providing access to hardware-based Trusted Execution Environments (TEEs) for devices lacking TEE support. RSGX is a framework crafted to transparently offload security-sensitive workloads to an enclave hosted in a remote centralized edge server. Operating as clients, low-end TEE-lacking devices can harness the hardware security features provided by TEEs of either the same or different architecture. RSGX is tailored to accommodate applications developed with diverse TEE-utilizing SDKs, such as the Open Enclave SDK, Intel SGX SDK, and many others. This facilitates easy integration of existing enclave-based applications, and the framework allows users to utilize its features without requiring any source code modifications, ensuring transparent offloading behind the scenes. For the evaluation, we set up an edge computing environment to execute C/C++ applications, including two overhead micro-benchmarks and four popular open-source applications. This evaluation of RSGX encompasses an analysis of its security benefits and a measurement of its performance overhead. We demonstrate that RSGX has the potential to mitigate a range of Common Vulnerability Exposures (CVEs), ensuring the secure execution of confidential computations on hybrid and distributed machines with an acceptable performance overhead. / Master of Science / A vast amount of data is generated globally every day, most of which contains critical information and is often linked to individuals. Therefore, safeguarding data is essential at every stage, whether it's during transmission, storage, or processing. Different security principles are applied to protect data at various stages. This thesis particularly focuses on data in use. To protect data in use, several technologies are available, and one of them is confidential computing, which is a hardware-based security technology. However, confidential computing is limited to certain high-end computing machines, and many resource-constrained devices do not support it. In this thesis, we propose RSGX, a framework to offload secured computation to a confidential computing-capable remote device with a Security as a Service (SECaaS) approach. Through RSGX, users can leverage confidential computing capabilities for any of their applications based on any SDK. RSGX provides this capability transparently and securely. Our evaluation shows that users, by adapting RSGX, can mitigate several security vulnerabilities, thereby enhancing security with a reasonable overhead.
25

User equipment based-computation offloading for real-time applications in the context of Cloud and edge networks / Délestage de calcul pour des applications temps-réel dans le contexte du Cloud et du edge

Messaoudi, Farouk 16 April 2018 (has links)
Le délestage de calcul ou de code est une technique qui permet à un appareil mobile avec une contrainte de ressources d'exécuter à distance, entièrement ou partiellement, une application intensive en calcul dans un environnement Cloud avec des ressources suffisantes. Le délestage de code est effectué principalement pour économiser de l'énergie, améliorer les performances, ou en raison de l'incapacité des appareils mobiles à traiter des calculs intensifs. Plusieurs approches et systèmes ont été proposés pour délester du code dans le Cloud tels que CloneCloud, MAUI et Cyber Foraging. La plupart de ces systèmes offrent une solution complète qui traite différents objectifs. Bien que ces systèmes présentent en général de bonnes performances, un problème commun entre eux est qu'ils ne sont pas adaptés aux applications temps réel telles que les jeux vidéo, la réalité augmentée et la réalité virtuelle, qui nécessitent un traitement particulier. Le délestage de code a connu un récent engouement avec l'avènement du MEC et son évolution vers le edge à multiple accès qui élargit son applicabilité à des réseaux hétérogènes comprenant le WiFi et les technologies d'accès fixe. Combiné avec l'accès mobile 5G, une pléthore de nouveaux services mobiles apparaîtront, notamment des service type URLLC et eV2X. De tels types de services nécessitent une faible latence pour accéder aux données et des capacités de ressources suffisantes pour les exécuter. Pour mieux trouver sa position dans une architecture 5G et entre les services 5G proposés, le délestage de code doit surmonter plusieurs défis; la latence réseau élevée, hétérogénéité des ressources, interopérabilité des applications et leur portabilité, la consommation d'énergie, la sécurité, et la mobilité, pour citer quelques uns. Dans cette thèse, nous étudions le paradigme du délestage de code pour des applications a temps réel, par exemple; les jeux vidéo sur équipements mobiles et le traitement d'images. L'accent sera mis sur la latence réseau, la consommation de ressources, et les performances accomplies. Les contributions de la thèse sont organisées sous les axes suivants : Étudier le comportement des moteurs de jeu sur différentes plateformes en termes de consommation de ressources (CPU / GPU) par image et par module de jeu ; Étudier la possibilité de distribuer les modules du moteur de jeu en fonction de la consommation de ressources, de la latence réseau, et de la dépendance du code ; Proposer une stratégie de déploiement pour les fournisseurs de jeux dans le Cloud, afin de mieux exploiter les ressources, en fonction de la demande variable en ressource par des moteurs de jeu et de la QoE du joueur ; Proposer une solution de délestage statique de code pour les moteurs de jeu en divisant la scène 3D en différents objets du jeu. Certains de ces objets sont distribués en fonction de la consommation de ressources, de la latence réseau et de la dépendance du code ; Proposer une solution de délestage dynamique de code pour les moteurs de jeu basée sur une heuristique qui calcule pour chaque objet du jeu, le gain du délestage. En fonction de ce gain, un objet peut être distribué ou non ; Proposer une nouvelle approche pour le délestage de code vers le MEC en déployant une application sur la bordure du réseau (edge) responsable de la décision de délestage au niveau du terminal et proposer deux algorithmes pour prendre la meilleure décision concernant les tâches à distribuer entre le terminal et le serveur hébergé dans le MEC. / Computation offloading is a technique that allows resource-constrained mobile devices to fully or partially offload a computation-intensive application to a resourceful Cloud environment. Computation offloading is performed mostly to save energy, improve performance, or due to the inability of mobile devices to process a computation heavy task. There have been a numerous approaches and systems on offloading tasks in the classical Mobile Cloud Computing (MCC) environments such as, CloneCloud, MAUI, and Cyber Foraging. Most of these systems are offering a complete solution that deal with different objectives. Although these systems present in general good performance, one common issue between them is that they are not adapted to real-time applications such as mobile gaming, augmented reality, and virtual reality, which need a particular treatment. Computation offloading is widely promoted especially with the advent of Mobile Edge Computing (MEC) and its evolution toward Multi-access Edge Computing which broaden its applicability to heterogeneous networks including WiFi and fixed access technologies. Combined with 5G mobile access, a plethora of novel mobile services will appear that include Ultra-Reliable Low-latency Communications (URLLC) and enhanced Vehicle-toeverything (eV2X). Such type of services requires low latency to access data and high resource capabilities to compute their behaviour. To better find its position inside a 5G architecture and between the offered 5G services, computation offloading needs to overcome several challenges; the high network latency, resources heterogeneity, applications interoperability and portability, offloading frameworks overhead, power consumption, security, and mobility, to name a few. In this thesis, we study the computation offloading paradigm for real-time applications including mobile gaming and image processing. The focus will be on the network latency, resource consumption, and accomplished performance. The contributions of the thesis are organized on the following axes : Study game engines behaviour on different platforms regarding resource consumption (CPU/GPU) per frame and per game module; study the possibility to offload game engine modules based on resource consumption, network latency, and code dependency ; propose a deployment strategy for Cloud gaming providers to better exploit their resources based on the variability of the resource demand of game engines and the QoE ; propose a static computation offloading-based solution for game engines by splitting 3D world scene into different game objects. Some of these objects are offloaded based on resource consumption, network latency, and code dependency ; propose a dynamic offloading solution for game engines based on an heuristic that compute for each game object, the offloading gain. Based on that gain, an object may be offloaded or not ; propose a novel approach to offload computation to MEC by deploying a mobile edge application that is responsible for driving the UE decision for offloading, as well as propose two algorithms to make best decision regarding offloading tasks on UE to a server hosted on the MEC.
26

Mobile Cloud Computing: A Comparison Study of Cuckoo and AIOLOS Offloading Frameworks

Kaddour, Inan 01 January 2018 (has links)
Currently, smart mobile devices are used for more than just calling and texting. They can run complex applications such as GPS, antivirus, and photo editor applications. Smart devices today offer mobility, flexibility, and portability, but they have limited resources and a relatively weak battery. As companies began creating mobile resource intensive and power intensive applications, they have realized that cloud computing was one of the solutions that they could utilize to overcome smart device constraints. Cloud computing helps decrease memory usage and improve battery life. Mobile cloud computing is a current and expanding research area focusing on methods that allow smart mobile devices to take full advantage of cloud computing. Code offloading is one of the techniques employed in cloud computing with mobile devices. This research compares two dynamic offloading frameworks to determine which one is better in terms of execution time and battery life improvement.
27

Methodology for definition of new operating sectors fo DP assisted offloading operations in spread-moored platforms. / Metodologia para definição de novos setores operacionais para operações de offloading com navios DP em plataformas ancoradas em Spread Mooring.

Orsolini, Ana Luísa de Barros 22 February 2017 (has links)
This thesis defines and applies a methodology for analyzing the possibility of extending the operating sector of DP shuttle tankers for offloading operations in Spread Moored FPSO Platforms. Extending the operating sector is beneficial to increase operations\' availability and to reduce DP power demand under certain environmental conditions. This study is important, since several emergency disconnections have occurred during offloading in Santos Basin because the shuttle tanker was pushed out of the green sector by environmental resultants that pointed to the West. However, this proposal has to be carefully analyzed in order to guarantee the operations\' safety and not to increase the risks of collision between FPSO and shuttle tanker, of oil pollution and of personnel safety. The methodology consists in five basic steps: Preliminary Risk Analysis to assess the potential hazards associated with the new sector; evaluation of the uptime gain through static analysis; evaluation of DP power demand inside the original and extended sector; real time simulations to evaluate the operation in a realistic environment; and, finally, field tests to validate the proposal. This thesis presents the contextualization of the problem, a bibliographical research, theoretical concepts, the detailed methodology and results of each step. The results show that the average uptime gain is significant both in Campos and Santos Basins - up to 9% and 13% respectively - and that the additional risks created by the sector extension are well mitigated if some recommendations are put into place. The conclusion of this thesis is that extending the operating sector is not only beneficial but also safe. / Esta dissertação define e aplica uma metodologia para analisar a possibilidade de extensão do setor operacional de navios aliviadores DP para operações de offloading em plataformas FPSO ancoradas em Spread-Mooring. Esta proposta apresenta como vantagens o aumento da disponibilidade das operações e redução na demanda de energia do navio DP em certas condições ambientais. O estudo é importante tendo em vista que várias desconexões de emergência já ocorreram durante operações de alívio na Bacia de Santos, porque o navio-tanque foi empurrado para fora do setor verde por resultantes ambientais que apontavam para oeste. No entanto, a proposta deve ser cuidadosamente analisada para garantir que o novo setor não aumenta os riscos de colisão, de poluição ambiental e de segurança às pessoas. A metodologia consiste em cinco etapas básicas: Análise Preliminar de Riscos (APR); avaliação do ganho de disponibilidade da operação; avaliação da demanda de energia do sistema DP nos setores original e estendido; simulações de manobra em tempo real; e, finalmente, testes em campo para validação da proposta. Esta dissertação apresenta a contextualização do problema, pesquisa bibliográfica, conceitos teóricos, a metodologia detalhada e os resultados de cada etapa. Os resultados mostram que o ganho médio de disponibilidade é significativo nas bacias de Campos e de Santos - até 9% e 13%, respectivamente - e que os riscos adicionais criados pela extensão do setor são devidamente mitigados se as recomendações levantadas na APR forem implementadas. A conclusão desta dissertação é que estender o setor operacional é, não somente benéfico, mas também seguro.
28

Methodology for definition of new operating sectors fo DP assisted offloading operations in spread-moored platforms. / Metodologia para definição de novos setores operacionais para operações de offloading com navios DP em plataformas ancoradas em Spread Mooring.

Ana Luísa de Barros Orsolini 22 February 2017 (has links)
This thesis defines and applies a methodology for analyzing the possibility of extending the operating sector of DP shuttle tankers for offloading operations in Spread Moored FPSO Platforms. Extending the operating sector is beneficial to increase operations\' availability and to reduce DP power demand under certain environmental conditions. This study is important, since several emergency disconnections have occurred during offloading in Santos Basin because the shuttle tanker was pushed out of the green sector by environmental resultants that pointed to the West. However, this proposal has to be carefully analyzed in order to guarantee the operations\' safety and not to increase the risks of collision between FPSO and shuttle tanker, of oil pollution and of personnel safety. The methodology consists in five basic steps: Preliminary Risk Analysis to assess the potential hazards associated with the new sector; evaluation of the uptime gain through static analysis; evaluation of DP power demand inside the original and extended sector; real time simulations to evaluate the operation in a realistic environment; and, finally, field tests to validate the proposal. This thesis presents the contextualization of the problem, a bibliographical research, theoretical concepts, the detailed methodology and results of each step. The results show that the average uptime gain is significant both in Campos and Santos Basins - up to 9% and 13% respectively - and that the additional risks created by the sector extension are well mitigated if some recommendations are put into place. The conclusion of this thesis is that extending the operating sector is not only beneficial but also safe. / Esta dissertação define e aplica uma metodologia para analisar a possibilidade de extensão do setor operacional de navios aliviadores DP para operações de offloading em plataformas FPSO ancoradas em Spread-Mooring. Esta proposta apresenta como vantagens o aumento da disponibilidade das operações e redução na demanda de energia do navio DP em certas condições ambientais. O estudo é importante tendo em vista que várias desconexões de emergência já ocorreram durante operações de alívio na Bacia de Santos, porque o navio-tanque foi empurrado para fora do setor verde por resultantes ambientais que apontavam para oeste. No entanto, a proposta deve ser cuidadosamente analisada para garantir que o novo setor não aumenta os riscos de colisão, de poluição ambiental e de segurança às pessoas. A metodologia consiste em cinco etapas básicas: Análise Preliminar de Riscos (APR); avaliação do ganho de disponibilidade da operação; avaliação da demanda de energia do sistema DP nos setores original e estendido; simulações de manobra em tempo real; e, finalmente, testes em campo para validação da proposta. Esta dissertação apresenta a contextualização do problema, pesquisa bibliográfica, conceitos teóricos, a metodologia detalhada e os resultados de cada etapa. Os resultados mostram que o ganho médio de disponibilidade é significativo nas bacias de Campos e de Santos - até 9% e 13%, respectivamente - e que os riscos adicionais criados pela extensão do setor são devidamente mitigados se as recomendações levantadas na APR forem implementadas. A conclusão desta dissertação é que estender o setor operacional é, não somente benéfico, mas também seguro.
29

Infraestrutura para operações de Offloading computacional em ambiente integrado Cloudlet-SDN com suporte a mobilidade

FRANÇA, Adriano Henrique de Melo 29 August 2016 (has links)
Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2017-04-25T12:03:54Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_AdrianoHenrique.pdf: 1956295 bytes, checksum: 38ce5d73db0d44416c8653e58120f11c (MD5) / Made available in DSpace on 2017-04-25T12:03:55Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_AdrianoHenrique.pdf: 1956295 bytes, checksum: 38ce5d73db0d44416c8653e58120f11c (MD5) Previous issue date: 2016-08-29 / Apesar da grande evolução tecnológica nos hardwares dos dispositivos móveis e nas redes sem fio, ainda existem grandes limitações nesses dispositivos em termos de processamento, capacidade de armazenamento e autonomia de energia, quando comparados aos desktops e servidores. O paradigma de Computação em Nuvem Móvel (MCC – Mobile Cloud Computing) permite estender os recursos computacionais dos dispositivos móveis através da utilização das técnicas de offloading computacional possibilitando um melhor desempenho as aplicações e uma redução no consumo das baterias dos dispositivos. Entretanto, a técnica de offloading nem sempre traz benefícios para o dispositivo móvel em situações de constante mobilidade do usuário, já que cada mudança de rede requer que o processo de offloading seja refeito. Esta dissertação propõe uma solução para otimizar o consumo de energia e o tempo de resposta durante as operações de offloading computacional quando o dispositivo muda de ponto de acesso. A proposta considera um esquema de gerenciamento de mobilidade baseado em Software Defined Networking (SDN) e técnica de caching remoto, que permite ao usuário receber o resultado do offloading no próximo acesso à rede, mesmo que esse fique desconectado por um longo período. A solução foi implementada em um testbed WiFi, com acesso ao ambiente MCC utilizando cloudlet baseada na plataforma OpenStack e integrada ao controlador SDN OpenDaylight. O consumo de energia obtido pela proposta que utiliza SDN/OpenFlow para o gerenciamento de mobilidade chegou a ser 11,33 vezes menor e a velocidade de processamento foi 3,23 vezes maior que do ambiente tradicional. O sistema de caching remoto, apesar de se mostrar útil em relação à rápida entrega dos resultados já processados, elevou consideravelmente o consumo de energia da bateria. A técnica de caching remoto é indicada para os casos nos quais a aplicação envia à cloudlet um grande volume de dados para ser processado e o nível da bateria do dispositivo encontra-se em estado não crítico ou quando o usuário enfrenta um longo período sem comunicação com a cloudlet. / Although the great technological evolution in the mobile devices hardware and wireless networks, remains significant limitations of these devices regarding processing, storage, and energy, when compared to desktops and servers. The paradigm of Mobile Cloud Computing (MCC) allows to extend the computational resources of the mobile devices through the use of computational offloading techniques, achieving a better performance on the part of the applications and a reduction in the battery consumption of the devices. The offloading technique does not always bring benefits to a mobile device in situations of high mobility since each network change requires the execution of the offloading process. This dissertation proposes a solution to optimize energy consumption and response times during the computational offloading operations when the device change of access points (AP). To this end, the proposal considers for such, a mobility management scheme based on SDN (Software Defined Networking) and a remote caching technique, that allows the user to receive the result from offloading in the next AP, even if he stays disconnected for an extended period. The solution was implemented in one Wi-Fi testbed, with access to the MCC environment using cloudlet based on the OpenStack platform and integrated with the OpenDaylight SDN controller. The achieved reduction of energy consumption for the mobility management proposal arrived to be 11.33 times lower, and the processing speed was 3.23 times bigger that of the traditional environment. The remote caching system, although useful in fast delivering the already processed results, considerably raised the battery energy consumption. Thus, the applicability of remote caching limits it to the cases where the application sends to the cloudlet an enormous volume of data to be processed and the battery level of the device is not critical or when the user faces an extended period without communication with the cloudlet.
30

Cognitive offloading: O vlivu nových médií na kognitivní schopnosti člověka / Cognitive offloading: About the impact of new media on human cognitivity

Mikšovská, Markéta January 2020 (has links)
(in English) The subject of this master thesis is a cognitive offloading, sometimes also called cognitive outsourcing, meaning the impact of new media on human cognitive abilities. This work describes the evolution of the theoretical concept of cognitive offloading, types of cognitive offloading and it's functioning in today's society. Following Daniel Wegner's work, it describes basic concepts such as group mind and transactive memory and it focuses on a specific area of cognitive offloading - the impact of mobile photography on human memory. The thesis summarizes results of existing studies in this field and presents the results of a replicated pilot study conducted with the students of Czech high school. The aim of this study was to find out if - and to what extent - does smartphones impact one's memory and cognitive abilities in daily life. The conclusion analyzes the limits of this work and outlines further research possibilities in this field.

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