A Node Selection Paradigm for Crowdsourcing Service Based on Region Feature in Crowd Sensing
المؤلفون المشاركون
Gui, Xiaolin
An, Jian
Peng, Zhenlong
Gui, Ruowei
Liao, Dong
Cai, Ningchao
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-11-14
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Crowd sensing is a human-centered sensing model.
Through the cooperation of multiple nodes, an entire sensing task is completed.
To improve the efficiency of sensing missions, a cost-effective set of service nodes, which is easy to fit in performing different tasks, is needed.
In this paper, we propose a low-cost service node selection method based on region features, which builds on the relationship between task requirements and geographical locations.
The method uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to cluster service nodes and calculate the center point of each cluster.
The area then is divided into regions according to rules of Voronoi diagrams.
Local feature vectors are constructed according to the historical records in each divided region.
When a particular sensing task arrives, Analytic Hierarchy Process (AHP) is used to match the feature vector of each region to mission requirements to get a certain number of service nodes satisfying the characteristics.
To get a lower cost output, a revised Greedy Algorithm is designed to filter the exported service nodes to get the required low-cost service nodes.
Experimental results suggest that the proposed method shows promise in improving service node selection accuracy and the timeliness of finishing tasks.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Peng, Zhenlong& Gui, Xiaolin& An, Jian& Liao, Dong& Cai, Ningchao& Gui, Ruowei. 2018. A Node Selection Paradigm for Crowdsourcing Service Based on Region Feature in Crowd Sensing. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1208400
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Peng, Zhenlong…[et al.]. A Node Selection Paradigm for Crowdsourcing Service Based on Region Feature in Crowd Sensing. Mathematical Problems in Engineering No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1208400
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Peng, Zhenlong& Gui, Xiaolin& An, Jian& Liao, Dong& Cai, Ningchao& Gui, Ruowei. A Node Selection Paradigm for Crowdsourcing Service Based on Region Feature in Crowd Sensing. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1208400
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1208400
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر