Device-to-Device Users Clustering Based on Physical and Social Characteristics
This paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and p...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/165608 |
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| _version_ | 1832559176387133440 |
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| author | Li Wang Giuseppe Araniti Chunyan Cao Wei Wang Yang Liu |
| author_facet | Li Wang Giuseppe Araniti Chunyan Cao Wei Wang Yang Liu |
| author_sort | Li Wang |
| collection | DOAJ |
| description | This paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and physical relationships among D2D terminals. Towards this goal, we propose two clustering approaches. The first one is based on the Chinese restaurant process (CRP), whereas the second one enhances the traditional CRP by defining a “distance-dependent Chinese restaurant process” (namely, DCRP). Numerical simulation results demonstrate superiority of our proposed clustering schemes in terms of system throughput, energy consumption, and energy efficiency over the existing schemes that rely only on physical distance. |
| format | Article |
| id | doaj-art-e3cbbbdae6fb4b5d87553e798c547c11 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-e3cbbbdae6fb4b5d87553e798c547c112025-02-03T01:30:43ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/165608165608Device-to-Device Users Clustering Based on Physical and Social CharacteristicsLi Wang0Giuseppe Araniti1Chunyan Cao2Wei Wang3Yang Liu4 Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China Mediterranea University, 89100 Reggio Calabria, Italy Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThis paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and physical relationships among D2D terminals. Towards this goal, we propose two clustering approaches. The first one is based on the Chinese restaurant process (CRP), whereas the second one enhances the traditional CRP by defining a “distance-dependent Chinese restaurant process” (namely, DCRP). Numerical simulation results demonstrate superiority of our proposed clustering schemes in terms of system throughput, energy consumption, and energy efficiency over the existing schemes that rely only on physical distance.https://doi.org/10.1155/2015/165608 |
| spellingShingle | Li Wang Giuseppe Araniti Chunyan Cao Wei Wang Yang Liu Device-to-Device Users Clustering Based on Physical and Social Characteristics International Journal of Distributed Sensor Networks |
| title | Device-to-Device Users Clustering Based on Physical and Social Characteristics |
| title_full | Device-to-Device Users Clustering Based on Physical and Social Characteristics |
| title_fullStr | Device-to-Device Users Clustering Based on Physical and Social Characteristics |
| title_full_unstemmed | Device-to-Device Users Clustering Based on Physical and Social Characteristics |
| title_short | Device-to-Device Users Clustering Based on Physical and Social Characteristics |
| title_sort | device to device users clustering based on physical and social characteristics |
| url | https://doi.org/10.1155/2015/165608 |
| work_keys_str_mv | AT liwang devicetodeviceusersclusteringbasedonphysicalandsocialcharacteristics AT giuseppearaniti devicetodeviceusersclusteringbasedonphysicalandsocialcharacteristics AT chunyancao devicetodeviceusersclusteringbasedonphysicalandsocialcharacteristics AT weiwang devicetodeviceusersclusteringbasedonphysicalandsocialcharacteristics AT yangliu devicetodeviceusersclusteringbasedonphysicalandsocialcharacteristics |