کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
388641 660935 2010 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel prediction-based strategy for object tracking in sensor networks by mining seamless temporal movement patterns
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A novel prediction-based strategy for object tracking in sensor networks by mining seamless temporal movement patterns
چکیده انگلیسی

Energy saving in sensor networks has received a great deal of research attention in recent years due to its wide applications. One important research issue is energy efficient object tracking in sensor networks (OTSNs). Past studies on energy saving in OTSNs can be divided into two main directions: (1) improvement in hardware design; and (2) improvement in software approaches. Many research papers save energy in hardware design, but few discuss software approaches. The intuitive way to conserve the energy of sensor nodes is to reduce the operation time of high-powered components. Utilizing the movement patterns of objects to save energy is one software approach. However, it did not take temporal information into consideration nor did it define a suitable segmenting time unit of time interval in advance. Due to the time interval between movements is a real number, an improper segmenting time unit may not discover the useful patterns, directly resulting in the inefficient object tracking. In this paper, we propose a seamless data mining algorithm named STMP-Mine to efficiently discover the temporal movement patterns of objects in sensor networks without predefining the segmenting time unit. Moreover, we propose novel location prediction strategies that employ the discovered temporal movement patterns to reduce prediction errors to save energy. With empirical evaluation on simulated data, STMP-Mine and the proposed prediction strategies are shown to deliver excellent performance in terms of scalability and energy efficiency.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 37, Issue 4, April 2010, Pages 2799–2807
نویسندگان
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