TrustICE: Hardware-Assisted Isolated Computing Environments on Mobile Devices

2015 ◽  
Author(s):  
He Sun ◽  
Kun Sun ◽  
Yuewu Wang ◽  
Jiwu Jing ◽  
Haining Wang
Keyword(s):  
Mobile Devices ◽  
Computing Environments

Service Provision for Pervasive Computing Environments

2009 ◽  
pp. 279-289
Author(s):  
Emerson Loureiro ◽  
Frederico Bublitz ◽  
Loreno Oliveira ◽  
Nadia Barbosa ◽  
Angelo Perkusich ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Pervasive Computing ◽  
Service Provision ◽  
The Other ◽  
Service Oriented Computing ◽  
Computing Paradigm ◽  
Other Hand ◽  
The Future ◽  
Service Oriented ◽  
Computing Environments

The fast development on microelectronics has promoted the increase on the computational power of hardware components. On the other hand, we are facing a significant improvement on energy consumption as well as the reduction of the physical size of such components. These improvements and the emergence of wireless networking technologies are enabling the development of small and powered mobile devices. Due to this scenario, the so-called pervasive computing paradigm, introduced by Mark Weiser in 1991 (Weiser, 1991) is becoming a reality. Such a paradigm envisions a world where environments are inhabited by computing devices, all of them seamlessly integrated into peoples’ lives, and effectively helping to carry on their daily tasks. Among others, one major characteristic of Weiser’s vision is that each device in an environment becomes a potential client or provider of resources. Not surprisingly, pervasive computing environments are becoming dynamic repositories of computational resources, all of them available to mobile users from the palm of their hands. However, devices can unpredictably join and leave such environments. Thus, resources can be dynamically made available or unavailable. Such a scenario has a great impact on the way that resources are found and used. In the case of static environments, such as the Web, it is reasonable to look up and access resources, such as Web pages, knowing the address of their providers beforehand. On the other hand, for dynamic environments, such as the pervasive computing ones, this is not a reasonable approach. This is due to the fact that one cannot guarantee that the provider of a resource will be available at any moment, because it may have left the environment or simply turned off. A better approach would be to discover these resources based on their descriptions, or any other feature that does not require the client to know the specific address of their providers. To this end, some of the current pervasive computing solutions, like Wings (Loureiro, Bublitz, Oliveira, Barbosa, Perkusich, Almeida, & Ferreira, 2006), Green (Sivaharan, Blair, & Coulson, 2005), RUNES (Costa, Coulson, Mascolo, Picco, & Zachariadis, 2005), and Scooby (Robinson, Wakeman, & Owen, 2004), are making use of a novel approach from the branch of distributed applications, the service-oriented computing paradigm (Papazoglou, 2003; Huhns & Singh, 2005). This is due to the fact that such a paradigm provides a crucial element for pervasive computing systems, the ability for dynamically binding to remote resources (Bellur & Narenda, 2005), which enables mobile devices to find needed services on demand. However, pervasive environments may be structured in different ways. They can range from wired networks to completely wireless ones, where communication among the devices is performed in an ad hoc way. Such a characteristic indicates that the way services are provisioned in a pervasive computing environment should fit in its organization, in order to enhance the access to the services available. Considering the above discussion, in this article we provide a review on service provision and its applicability in pervasive computing. More precisely, we will list the existing service provision approaches and discuss the characteristics and problems associated with each one, as well as their usage in pervasive computing environments. We start by providing introductory concepts of service-oriented and pervasive computing, respectively in the service-oriented computing and pervasive computing sections. Next, we present the service provision techniques available and how they can be applied for pervasive computing environments. The main current solutions within this scope will be introduced in the service oriented technologies section. Some of the future trends associated with research for service provision in pervasive computing environments will be presented in the future research trends section. Finally, in the conclusions sect

scholarly journals iCompose: context-aware physical user interface for application composition

2011 ◽  
Vol 1 (4) ◽  
Author(s):  
Oleg Davidyuk ◽  
Ekaterina Gilman ◽  
Iván Milara ◽  
Jussi Mäkipelto ◽  
Mikko Pyykkönen ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Evaluation Study ◽  
User Acceptance ◽  
User Evaluation ◽  
Context Aware ◽  
Dynamic Nature ◽  
Everyday Objects ◽  
Everyday Activities ◽  
Computing Environments ◽  
Ubiquitous Computing Environments

AbstractUbiquitous computing environments advocate creating applications by plugging together various resources (mobile devices, displays, augmented everyday objects, and so on) and Web Services to support the user’s everyday activities and needs. This approach is referred to as application composition, and such applications are called composite. Due to the dynamic nature of ubiquitous environments, application composition has to be supported at runtime, so that the applications are able to adapt to the situation within the environment and other contexts. Application composition is usually performed by autonomous context-aware mechanisms that provide limited or no control for users. Still, users need to be aware of their environments and be able to control and configure applications when they are composed and executed. Towards this goal we present in this article a context-aware application composition system based on the iCompose interface for composing and controlling applications at runtime. Users compose applications by simply touching the resources in the environment with their mobile devices, while the iCompose interface provides feedback and assists users by suggesting them possible further actions. The interface relies on a rule-based reasoner and utilizes various context sources to support users dynamically, according to the situation in which they compose applications. We present a complete implementation of the system and report the results of a user evaluation study conducted with 21 participants. This study assesses the issues of control, usability, feasibility and user acceptance of the iCompose interface for context-aware application composition and the prototype as a whole.

scholarly journals Highly Secure Mobile Devices Assisted with Trusted Cloud Computing Environments

ETRI Journal ◽  
2015 ◽  
Vol 37 (2) ◽  
pp. 348-358 ◽  
Author(s):  
Doohwan Oh ◽  
Ilkyu Kim ◽  
Keunsoo Kim ◽  
Sang-Min Lee ◽  
Won Woo Ro
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Computing Environments

Service Provision for Pervasive Computing Environments

2007 ◽  
pp. 877-884
Author(s):  
E. Loureiro ◽  
Frederico Bublitz ◽  
Loreno Oliveira ◽  
Nadia Barbosa ◽  
Angelo Perkusich ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Mobile Devices ◽  
Pervasive Computing ◽  
The Other ◽  
Computational Power ◽  
Physical Size ◽  
Computing Paradigm ◽  
Fast Development ◽  
Computing Environments ◽  
Networking Technologies

The fast development on microelectronics has promoted the increase on the computational power of hardware components. On the other hand, we are facing a significant improvement on energy consumption as well as the reduction of the physical size of such components. These improvements and the emergence of wireless networking technologies are enabling the development of small and powered mobile devices. Due to this scenario, the so-called pervasive computing paradigm, introduced by Mark Weiser in 1991 (Weiser, 1991) is becoming a reality. Such a paradigm envisions a world where environments are inhabited by computing devices, all of them seamlessly integrated into peoples’ lives, and effectively helping to carry on their daily tasks.

Engineering Emergent Ecologies of Interacting Artefacts

2008 ◽  
pp. 364-384 ◽  
Author(s):  
Ioannis D. Zaharakis ◽  
Achilles D. Kameas
Keyword(s):  
Ubiquitous Computing ◽  
Swarm Intelligence ◽  
Mobile Devices ◽  
Social Memory ◽  
Fault Tolerant ◽  
Network Connectivity ◽  
Engineering Approach ◽  
Computing Environments ◽  
Ubiquitous Computing Environments ◽  
Ubiquitous Network

Nowadays, our living environments already provide ubiquitous network connectivity and are populated by an increasing number of artefacts (objects enhanced with sensing, computation, and networking abilities). In addition, people are increasingly using mobile devices as intermediaries between themselves and the artefacts. In order to create, manage, communicate with, and reason about ubiquitous computing environments that involve hundreds of interacting artefacts and cooperating mobile devices, we propose to embed, in these entities, social memory, enhanced context memory, and shared experiences. In this context, we describe an engineering approach and a framework to deal with emergent ecologies of locally interacting artefacts that provide services not existing initially in the individuals, and exhibiting them in a consistent and fault-tolerant way. Because they are emergent, their structure or availability are not predefined or known before hand; we draw from swarm intelligence methods to describe such ecologies.

scholarly journals Towards Integrating Mobile Devices into Dew Computing: A Model for Hour-Wise Prediction of Energy Availability

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 86 ◽  
Author(s):  
Mathias Longo ◽  
Matías Hirsch ◽  
Cristian Mateos ◽  
Alejandro Zunino
Keyword(s):  
Mobile Devices ◽  
Mean Squared Error ◽  
State Variables ◽  
Electricity Grid ◽  
Computing Services ◽  
Computing Environments ◽  
Error Metric ◽  
The One ◽  
Prediction Approach ◽  
Dew Computing

With self-provisioning of resources as premise, dew computing aims at providing computing services by minimizing the dependency over existing internetwork back-haul. Mobile devices have a huge potential to contribute to this emerging paradigm, not only due to their proximity to the end user, ever growing computing/storage features and pervasiveness, but also due to their capability to render services for several hours, even days, without being plugged to the electricity grid. Nonetheless, misusing the energy of their batteries can discourage owners to offer devices as resource providers in dew computing environments. Arguably, having accurate estimations of remaining battery would help to take better advantage of a device’s computing capabilities. In this paper, we propose a model to estimate mobile devices battery availability by inspecting traces of real mobile device owner’s activity and relevant device state variables. The model includes a feature extraction approach to obtain representative features/variables, and a prediction approach, based on regression models and machine learning classifiers. On average, the accuracy of our approach, measured with the mean squared error metric, overpasses the one obtained by a related work. Prediction experiments at five hours ahead are performed over activity logs of 23 mobile users across several months.

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