Android/OSGi-based vehicular network management system

Chen, Ming-Chiao; Chen, Jiann-Liang; Chang, Teng-Wen

doi:10.1016/j.comcom.2010.03.032

Cited by 44 publications

(17 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Thus, it can prevent time-sensitive applications from delays, averting the system from race condition or deadlock crashes. In addition, the platform of Chen et al (2011), which is based on remote resource management, can make applications require less memory and resources. Hence, it can eliminate the well-known "non-responsive" exceptions in Android.…”

Section: Process Managementmentioning

confidence: 99%

Charting the API minefield using software telemetry data

2014

View full text Add to dashboard Cite

Programs draw significant parts of their functionality through the use of Application Programming Interfaces (APIs). Apart from the way developers incorporate APIs in their software, the stability of these programs depends on the design and implementation of the APIs. In this work, we report how we used software telemetry data to analyze the causes of API failures in Android applications. Specifically, we got 4.9 GB worth of crash data that thousands of applications sent to a centralized crash report management service. We processed that data to extract approximately a million stack traces, stitching together parts of chained exceptions, and established heuristic rules to draw the border between applications and the API calls. We examined a set of more than a half million stack traces associated with risky API calls to map the space of the most common application failure reasons. Our findings show that the top ones can be attributed to memory exhaustion, race conditions or deadlocks, and missing or corrupt resources. Given the classes of the crash causes we identified, we recommend API design and implementation choices, such as specific exceptions, default resources, and non-blocking algorithms, that can eliminate common failures. In addition, we argue that development tools like memory analyzers, thread debuggers, and static analyzers can prevent crashes through early code testing and analysis. Finally, some execution platform and framework designs for process and memory management can also eliminate some application crashes.

show abstract

Section: Process Managementmentioning

confidence: 99%

Charting the API minefield using software telemetry data

2014

View full text Add to dashboard Cite

show abstract

“…For this purpose, an in-house water quality simulation model known as E2ALGAE, that was webenabled, has been previously developed by the authors for predicting water quality in lakes, rivers and estuaries. The proliferation of smartphones has expanded the use of mobile apps in various fields [5][6][7]. To render the applications on mobile devices, this paper presents the implementation of E2ALGAE that is redesigned for execution on-site by mobile devices.…”

Section: Introductionmentioning

confidence: 99%

Mobile apps for water quality simulation

Teh

Koh

2013

Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

View full text Add to dashboard Cite

Learning via numerical experiments sustains the passion of learning science, through novel experience made possible by technological advancements, particularly among the young generations. To complement classroom theoretical study of water quality modeling for a course on Mathematical Modeling (MSG327), an in-house water quality simulation model known as E2ALGAE is redesigned for execution on-site by mobile devices. Armed with smartphones and other mobile devices, students are able to execute water quality numerical simulations on-site in conjunction with field data acquisition to strengthen their intuitive learning. In this manner, they are empowered with the tools by which they can relate theoretical knowledge to practical experience and experiments, linking the tame classroom with the wild field environments. This paper presents the development and implementation of the mobile version of E2ALGAE. A parallel version developed on C# and html language for web execution or in computer is also available on request. The use of E2ALGAE in MSG327 to allow numerical experiments and relevant on-site environmental monitoring in conjunction with related lab work and classroom theoretical study creates a new learning environment that is appealing, comprehensive and effective. Students' evaluation on the course delivery and relevance indicates high level of satisfaction and acceptance of the teaching method, which incorporates the use of mobile apps as an attractive media for students and young researchers to explore the experience of water quality simulations on-site and in the lab. It is envisaged that this mobile apps can be utilized onsite by researchers and governments enforcement agencies as an effective means to verify technical conclusions reported in Environmental Impact assessment (EIA) reports submitted for government approval.

show abstract

“…(3) Integrated with Google service: the operating system can be integrated with cloud services, such as Gmail and Google maps. Based on the above advantages, users can develop application programs in health care [8,9], or in vehicle communication [10]. However, there are many technical challenges in the basic interactions of motion recognition for smart phones.…”

Section: Introductionmentioning

confidence: 99%

A study of motion recognition system using a smart phone

Chu

Cheng

Tsai

2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

As technology fast progressed, information equipment operating interfaces have changed. Traditional instruction operation has evolved into intuitive operation, providing users a convenient operation experience without the need of learning in advance. At present, several kinds of intuitive user interface systems have been developed in smart phones, such as picture vertical/horizontal automatic sensing switch and smart phone face/back sensing switch. In this paper, we developed a motion recognition system, where a G-sensor inside a smart phone records user's motions, and then the motions are identified by the proposed recognition algorithm to realize the intuitive operation function.

show abstract

Android/OSGi-based vehicular network management system

Cited by 44 publications

References 6 publications

Charting the API minefield using software telemetry data

Charting the API minefield using software telemetry data

Mobile apps for water quality simulation

A study of motion recognition system using a smart phone

Contact Info

Product

Resources

About