Remote Control and Monitoring of Smart Home Facilities via Smartphone with Wi-Fly

Due to the widespread ownership of smartphone devices, the application of mobile technologies to enhance the monitoring and control of smart home facilities has attracted much academic attention. This study indicates that tools already in the possession of the end user can be a significant part of the specific context-aware system in the smart home. The behaviour of the system in the context of existing systems will reflect the intention of the client. This model system offers a diverse architectural concept for Wireless Sensor Actuator Mobile Computing in a Smart Home (WiSAMCinSH) and consists of sensors and actuators in various communication channels, with different capacities, paradigms, costs and degree of communication reliability. This paper focuses on the utilization of end users’ smartphone applications to control home devices, and to enable monitoring of the context-aware environment in the smart home to fulfil the needs of the ageing population. It investigates the application of an iPhone to supervise smart home monitoring and control electrical devices, and through this approach, after initial setup of the mobile application, a user can control devices in the smart home from different locations and over various distances

Improving Resource Consumption in Context- Aware Mobile Applications Through Alternative Architectural Styles

Over the last years, the Internet of Things has fostered a growing interest in context-aware mobile applications; this fact is mainly due to highly favoring information provision from multiple Internetconnected devices. To identify user context, these applications collect information from the user and his/her environment and typically lter app information, so that the user receives only the interesting and relevant information. However, such a task usually implies further resource consumption on user mobile devices, not only regarding battery usage but also in terms of network traf c. Accordingly, although context-aware applications can improve user experiences in their daily lives, they must ensure the maintenance of lowlevel resource consumption; otherwise, the applications are promptly replaced by less consuming ones, and therefore, removed from the mobile market. In this paper, we evaluate and discuss several architectural styles for context-aware mobile applications, as well as, providing a set of guidelines to decide on the right architecture for a particular app depending on its characteristics. The use of such guidelines when choosing the right architectural style can strongly in uence the resource consumption of context-aware mobile applications. Following these guidelines, user satisfaction of a context-aware mobile application may be improved, thus guaranteeing the app success

Context-driven progressive enhancement of mobile web applications: a multicriteria decision-making approach

Personal computing has become all about mobile and embedded devices. As a result, the adoption rate of smartphones is rapidly increasing and this trend has set a need for mobile applications to be available at anytime, anywhere and on any device. Despite the obvious advantages of such immersive mobile applications, software developers are increasingly facing the challenges related to device fragmentation. Current application development solutions are insufficiently prepared for handling the enormous variety of software platforms and hardware characteristics covering the mobile eco-system. As a result, maintaining a viable balance between development costs and market coverage has turned out to be a challenging issue when developing mobile applications. This article proposes a context-aware software platform for the development and delivery of self-adaptive mobile applications over the Web. An adaptive application composition approach is introduced, capable of autonomously bypassing context-related fragmentation issues. This goal is achieved by incorporating and validating the concept of fine-grained progressive application enhancements based on a multicriteria decision-making strategy

Algorithms for efficient symbolic detection of faults in context-aware applications.

Context-aware and adaptive applications running on mobile devices pose new challenges for the verification community. Current verification techniques are tailored for different domains (mostly hardware) and the kind of faults that are typical of applications running on mobile devices are difficult (or impossible) to encode using the patterns of ldquotraditionalrdquo verification domains. In this paper we present how techniques similar to the ones used in symbolic model checking can be applied to the verification of context-aware and adaptive applications. More in detail, we show how a model of a context-aware application can be encoded by means of ordered binary decision diagrams and we introduce symbolic algorithms for the verification of a number of properties

Mobile Crowd Sensing in Edge Computing Environment

abstract: The mobile crowdsensing (MCS) applications leverage the user data to derive useful information by data-driven evaluation of innovative user contexts and gathering of information at a high data rate. Such access to context-rich data can potentially enable computationally intensive crowd-sourcing applications such as tracking a missing person or capturing a highlight video of an event. Using snippets and pictures captured from multiple mobile phone cameras with specific contexts can improve the data acquired in such applications. These MCS applications require efficient processing and analysis to generate results in real time. A human user, mobile device and their interactions cause a change in context on the mobile device affecting the quality contextual data that is gathered. Usage of MCS data in real-time mobile applications is challenging due to the complex inter-relationship between: a) availability of context, context is available with the mobile phones and not with the cloud, b) cost of data transfer to remote cloud servers, both in terms of communication time and energy, and c) availability of local computational resources on the mobile phone, computation may lead to rapid battery drain or increased response time. The resource-constrained mobile devices need to offload some of their computation. This thesis proposes ContextAiDe an end-end architecture for data-driven distributed applications aware of human mobile interactions using Edge computing. Edge processing supports real-time applications by reducing communication costs. The goal is to optimize the quality and the cost of acquiring the data using a) modeling and prediction of mobile user contexts, b) efficient strategies of scheduling application tasks on heterogeneous devices including multi-core devices such as GPU c) power-aware scheduling of virtual machine (VM) applications in cloud infrastructure e.g. elastic VMs. ContextAiDe middleware is integrated into the mobile application via Android API. The evaluation consists of overheads and costs analysis in the scenario of ``perpetrator tracking" application on the cloud, fog servers, and mobile devices. LifeMap data sets containing actual sensor data traces from mobile devices are used to simulate the application run for large scale evaluation.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Profiling Power Consumption on Mobile Devices

The proliferation of mobile devices, and the migration of the information access paradigm to mobile platforms, motivate studies of power consumption behaviors with the purpose of increasing the device battery life. The aim of this work is to profile the power consumption of a Samsung Galaxy I7500 and a Samsung Nexus S, in order to understand how such feature has evolved over the years. We performed two experiments: the first one measures consumption for a set of usage scenarios, which represent common daily user activities, while the second one analyzes a context-aware application with a known source code. The first experiment shows that the most recent device in terms of OS and hardware components shows significantly lower consumption than the least recent one. The second experiment shows that the impact of different configurations of the same application causes a different power consumption behavior on both smartphones. Our results show that hardware improvements and energy-aware software applications greatly impact the energy efficiency of mobile device

A Meta Model Based Extension of BPMN 2.0 for Mobile Context Sensitive Business Processes and Applications

Smart devices like smartphones or tablets have become ubiquitous, which affected many daily work activities like maintaining contacts via a mobile CRM anywhere, anytime. Thus, business processes can now be executed independently of an employee’s location. In addition, mobile devices have the possibility to measure physical quantities through sensors, like location or acceleration. Moreover, the connection to wireless networks made it possible to query context information like customer history. These context information can be used to adapt mobile business processes and the mobile application that support them. But in order to use this advantage, mobile sensor data has to be reflected in the business process model. As current languages for process aware information systems, such as BPMN, do not support the influence of mobile context information, we propose an extension of the BPMN that will enable the modeling of mobile context sensitive business processes

A test case generation approach for mobile APPS based on context and GUI events

The increase of mobile devices with rich innovative feature has become an enabler for developing mobile applications (mobile apps) that offer users an advance and extremely-localized context-aware content. Nowadays mobile apps are developed to address more critical areas of people’s daily computing needs, which bring concern on the applications’ quality. In order to build a high quality and more reliable applications, there is a need for effective testing techniques to test the apps. The most recent testing technique focuses on graphical user interface (GUI) events with little attention to context events. This makes it difficult to identify other defects in the changes that can be inclined by context in which an application runs. The major challenge in testing mobile apps that react to context events is how to identify the events from an application during testing. This study proposes an approach (named TEGDroid) for testing mobile apps considering the two sets of events: GUI and context events. This approach comprises five steps which are; extraction of resources from APK file, static analysis of the extracted app’s byte code to identify GUI events, analysis of mobile apps’ permission to identify different scenarios of context events, generation of test case based on the GUI and context events and validation of the test cases using code coverage and mutation testing. Experiment was performed on real world open source mobile apps to evaluate TEGDroid. Results from the experimental evaluation indicates that the approach is effective in identifying context events and had 61%-91% coverage across the seven (7) selected applications. Results from the mutation analysis shows that 100% of the mutants were killed. This indicates that TEGDroid have the capability to detect faults in mobile apps

"InstantSocial" – Implementing a Distributed Mobile Multi-user Application with Adaptation Middleware

In this position paper we explore how new capabilites of mobile devices could be used to setup distributed multi-user mobile applications with potentially high interest for end users. We describe an example of such an application by transposing Internet social network trends and principles to a mobile ad hoc environment. Then we present a tentative design and implentation sketch of this application in terms of the MUSIC context-aware adaptation middleware we are currently developing