Social network has become the important platform for the current social individual to exchange information and access various media. Traditional searching and locating method is faced with the characteristics of the high order correlation and implicit correlation for large-scale users, and user-association multidimensional and heterogeneity. In order to effectively deal with large-scale social network data, and improve the efficiency of user’s locating, this article introduces the peer-to-peer distributed searching mechanism with the help of the cloud computing platform. This searching mechanism assigns user a logical identifier, and matches the underlying physical address and the upper users’ logical address, so as to build the cloud logical topology structure of social network. This paper designs a K neighbor discovery algorithm. It is used to cluster the nodes according to the features of the user, so as to realize the quickly locating of social network. The performance of the algorithm is analyzed according to the user’s searching logic path length of social network, and information amount of routing state. The simulation of the algorithm is evaluated by maintenance costs of average network aggregation coverage and query time. The performance analysis and simulation results demonstrate that social network cloud has good performance and searching efficiency.
목차
Abstract 1.Introduction 2.Related Work 3.Topological Structure of Social Network Cloud Coverage and System Architecture Based on DHT 3.1 DHT 3.2 Basic Conception 3.3 Description of System Level Architectural 3.4 Description of Overlay Logical Topological Structure 4.Social Network Aggregation and Discovery Algorithm Based on DHT 4.1 Network Aggregation and Cluster Segmentation 4.2 Description of Discovery Algorithm 5.Performance Analysis and Simulation 5.1 Simulation 6.Conclusions and Future Work Acknowledgments References
키워드
Big data storagePeer-to-peer networkClusterDHT
저자
Xiaoshu Zhu [ School of Computer Science and Engineering; Guangxi Universities Key Lab of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, Guangxi , P.R. China ]
Corresponding author
Junhong Feng [ School of Computer Science and Engineering; Guangxi Universities Key Lab of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, Guangxi , P.R. China ]
Jie Zhang [ School of Computer Science and Engineering; Guangxi Universities Key Lab of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, Guangxi , P.R. China ]
보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Grid and Distributed Computing
간기
격월간
pISSN
2005-4262
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.9 No.7