Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
SOUZA, Hallyson Gustavo Tavares de
 |
| Orientador(a): |
ALBUQUERQUE JÚNIOR, Gabriel Alves de |
| Banca de defesa: |
CALLOU, Gustavo Rau de Almeida,
MACIEL, Paulo Romero Martins,
ANDRADE, Ermeson Carneiro de |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Informática Aplicada
|
| Departamento: |
Departamento de Estatística e Informática
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
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| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7876
|
Resumo: |
The Internet of Things (IoT) is a reality that has been inserted in the daily lives of people promoting interaction between the physical and digital world. Parallel to this, the evolution of mobile devices combined with the scientific and technological development in health has brought advances to meet diverse needs of users. In this context, the term mobile health (mHealth) is used to refer to the use of these devices in order to provide better services in the health area, expanding medical care and reducing costs. The use of mobile cloud computing (MCC) allows you to overcome the limitations of mobile devices’ capabilities such as processing, storage and power consumption. Remote monitoring of patients through wireless sensors implanted near their body constitutes a body area network (WBAN). These networks are used to record and make available data that can aid in the diagnosis and prevention of diseases. This integration of technologies creates new alternatives for treatment and follow-up of patients, either inside or outside the hospital environment. This work presents a study of the availability in IoT systems applied to mHealth. The architecture analyzed consists of patients monitored by wireless sensors, internal communication network (intra-BAN), mobile device with its battery and communication interfaces, external communication network (extra-BAN) with WiFi and 3G connection, and finally, the cloud environment in which the data is stored. From these components, hierarchical models were developed using reliability block diagrams (RBD) and continuous time Markov chain (CTMC). The availability of each component is independently calculated using its Mean Time to Fault (MTTF) and Mean Time to Repair (MTTR) values in order to evaluate the availability of the system, or parts of it. Several experiments were carried out to evaluate relevant factors for high availability in mHealth systems. The results show that the communication protocol adopted in intra-BAN, Zigbee or Bluetooth, do not present significant differences on the availability of the system. It was also noted that for domestic environments, it is more effective to use two small routers in the extra-BAN, than to use a more expensive and large router. Finally, the availability of reserve batteries and powerbanks, contribute positively to the achievement of high availability. The proposed models can help developers and maintainers of mHealth systems to scale the system depending on the level of service they want to provide. |
