Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things
Cognitive technologies can bring important benefits to our everyday life, enabling connected devices to do tasks that in the past only humans could do, leading to the Cognitive Internet of Things. Wireless Sensor and Actuator Networks (WSAN) are often employed for communication between Internet obje...
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European Alliance for Innovation (EAI)
2014-05-01
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Series: | EAI Endorsed Transactions on Cognitive Communications |
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Online Access: | http://eudl.eu/doi/10.4108/cogcom.1.2.e4 |
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doaj-252c7ad56f874d13954d647c1dd67f112020-11-25T02:11:09ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Cognitive Communications2313-45342014-05-011211310.4108/cogcom.1.2.e4Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive ThingsR. Francisco0A.M. Arsenio1YDreams Robotics and IST, Edificio A Moagem - Cidade do Engenho e da Artes, Largo da Estação, 6230-311 Fundão, PortugalYDreams Robotics and Universidade da Beira Interior, Edificio A Moagem - Cidade do Engenho e da Artes, Largo da Estação, 6230-311 Fundão, Portugal; arturarsenio@di.ubi.ptCognitive technologies can bring important benefits to our everyday life, enabling connected devices to do tasks that in the past only humans could do, leading to the Cognitive Internet of Things. Wireless Sensor and Actuator Networks (WSAN) are often employed for communication between Internet objects. However, WSAN face some problems, namely sensors’ energy and CPU load consumption, which are common to other networked devices, such as mobile devices or robotic platforms. Additionally, cognitive functionalities often require large processing power, for running machine learning algorithms, computer vision processing, or behavioral and emotional architectures. Cloud massive storage capacity, large processing speeds and elasticity are appropriate to address these problems. This paper proposes a middleware that transfers flows of execution between devices and the cloud for computationally demanding applications (such as those integrating a robotic brain), to efficiently manage devices’ resources.http://eudl.eu/doi/10.4108/cogcom.1.2.e4Internet of ThingsFinite State MachinesResource OptimizationWireless Sensor and Actuator NetworksCloud ComputingMiddleware |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
R. Francisco A.M. Arsenio |
spellingShingle |
R. Francisco A.M. Arsenio Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things EAI Endorsed Transactions on Cognitive Communications Internet of Things Finite State Machines Resource Optimization Wireless Sensor and Actuator Networks Cloud Computing Middleware |
author_facet |
R. Francisco A.M. Arsenio |
author_sort |
R. Francisco |
title |
Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things |
title_short |
Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things |
title_full |
Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things |
title_fullStr |
Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things |
title_full_unstemmed |
Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things |
title_sort |
switching brains: cloud-based intelligent resources management for the internet of cognitive things |
publisher |
European Alliance for Innovation (EAI) |
series |
EAI Endorsed Transactions on Cognitive Communications |
issn |
2313-4534 |
publishDate |
2014-05-01 |
description |
Cognitive technologies can bring important benefits to our everyday life, enabling connected devices to do tasks that in the past only humans could do, leading to the Cognitive Internet of Things. Wireless Sensor and Actuator Networks (WSAN) are often employed for communication between Internet objects. However, WSAN face some problems, namely sensors’ energy and CPU load consumption, which are common to other networked devices, such as mobile devices or robotic platforms. Additionally, cognitive functionalities often require large processing power, for running machine learning algorithms, computer vision processing, or behavioral and emotional architectures. Cloud massive storage capacity, large processing speeds and elasticity are appropriate to address these problems. This paper proposes a middleware that transfers flows of execution between devices and the cloud for computationally demanding applications (such as those integrating a robotic brain), to efficiently manage devices’ resources. |
topic |
Internet of Things Finite State Machines Resource Optimization Wireless Sensor and Actuator Networks Cloud Computing Middleware |
url |
http://eudl.eu/doi/10.4108/cogcom.1.2.e4 |
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