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Framework to Enable Scalable and Distributed Application Development: Lessons Learned While Developing the Opportunistic Seamless Localization System

Framework to Enable Scalable and Distributed Application Development: Lessons Learned While Developing the Opportunistic Seamless Localization System

J. Aernouts, B. Claerhout, G. Ergeerts, M. Weyn
Copyright: © 2013 |Volume: 4 |Issue: 4 |Pages: 18
ISSN: 1947-9220|EISSN: 1947-9239|EISBN13: 9781466635708|DOI: 10.4018/ijaras.2013100104
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MLA

Aernouts, J., et al. "Framework to Enable Scalable and Distributed Application Development: Lessons Learned While Developing the Opportunistic Seamless Localization System." IJARAS vol.4, no.4 2013: pp.64-81. http://doi.org/10.4018/ijaras.2013100104

APA

Aernouts, J., Claerhout, B., Ergeerts, G., & Weyn, M. (2013). Framework to Enable Scalable and Distributed Application Development: Lessons Learned While Developing the Opportunistic Seamless Localization System. International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS), 4(4), 64-81. http://doi.org/10.4018/ijaras.2013100104

Chicago

Aernouts, J., et al. "Framework to Enable Scalable and Distributed Application Development: Lessons Learned While Developing the Opportunistic Seamless Localization System," International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) 4, no.4: 64-81. http://doi.org/10.4018/ijaras.2013100104

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Abstract

In real-time middleware, latency is a critical aspect. When the input rate exceeds a certain threshold, queuing will result in an exponentially increasing delay. Distributed computing enables scaling so that this growing latency is kept at a constant minimum. When developing a generic framework, redundancy, platform independency, fault tolerance and transparency are important features that need to be taken care of. The authors’ test case, a localization system that is used to track multiple objects, is an example of such a heavy loaded and latency critical system. This specific test case requires that the framework quickly scales and reacts to changing loads, making this research challenging and innovative.

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