A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things
The explosive growth of Internet of Things (i.e., IoT) terminal equipment makes its topology more complex, which leads to the increasing cost of network research. Recently, the implicit community structure is widely used to improve the efficiency of research. However, most of the non-overlapping com...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9130144/ |
| _version_ | 1818617240188092416 |
|---|---|
| author | Yizhe Li Hui Xia Rui Zhang Benxu Hu Xiangguo Cheng |
| author_facet | Yizhe Li Hui Xia Rui Zhang Benxu Hu Xiangguo Cheng |
| author_sort | Yizhe Li |
| collection | DOAJ |
| description | The explosive growth of Internet of Things (i.e., IoT) terminal equipment makes its topology more complex, which leads to the increasing cost of network research. Recently, the implicit community structure is widely used to improve the efficiency of research. However, most of the non-overlapping community detection algorithms have some weakness, such as the large number of community detected and the obvious scale gap between communities. To address these abovementioned problems, we design a novel non-overlapping community detection algorithm, named as Pairing, Splitting and Aggregating algorithm (i.e., PSA). Firstly, in order to improve the accuracy of community division, a new node similarity index is designed to transform the network into a large number of similar node pairs. Secondly, based on the connected branches composed of similar node pairs, the network is further divided into several similar node sets. Thirdly, to balance the scale gap of different communities, the Grasshopper Optimization Algorithm, (i.e., GOA) is introduced to combine the local attribute (i.e., conductance) and global attribute (i.e., modularity) together to aggregate similar node sets into potential (or final) communities. Finally, the experimental results show that PSA not only controls the difference among communities well, but also outperforms the other four popular algorithms in terms of two metrics. Moreover, we propose a community-based resource discovery method (or scheme), named as Community-assisted Short-distance-query Resource Discovery algorithm (i.e., CSRD) to further verify the efficiency of PSA. The results show that the resource discovery efficiency of CSRD using PSA is better compared with other algorithms. |
| first_indexed | 2024-12-16T17:02:33Z |
| format | Article |
| id | doaj.art-ebc6ebed59c349309d063b1318ca55fa |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:02:33Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ebc6ebed59c349309d063b1318ca55fa2022-12-21T22:23:41ZengIEEEIEEE Access2169-35362020-01-01812393812395110.1109/ACCESS.2020.30060299130144A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of ThingsYizhe Li0Hui Xia1https://orcid.org/0000-0001-7326-5796Rui Zhang2https://orcid.org/0000-0002-4117-2656Benxu Hu3Xiangguo Cheng4https://orcid.org/0000-0002-1228-4894College of Computer Science and Technology, Qingdao University, Qingdao, ChinaCollege of Information Science and Engineering, Ocean University of China, Qingdao, ChinaCollege of Computer Science and Technology, Qingdao University, Qingdao, ChinaCollege of Computer Science and Technology, Qingdao University, Qingdao, ChinaCollege of Computer Science and Technology, Qingdao University, Qingdao, ChinaThe explosive growth of Internet of Things (i.e., IoT) terminal equipment makes its topology more complex, which leads to the increasing cost of network research. Recently, the implicit community structure is widely used to improve the efficiency of research. However, most of the non-overlapping community detection algorithms have some weakness, such as the large number of community detected and the obvious scale gap between communities. To address these abovementioned problems, we design a novel non-overlapping community detection algorithm, named as Pairing, Splitting and Aggregating algorithm (i.e., PSA). Firstly, in order to improve the accuracy of community division, a new node similarity index is designed to transform the network into a large number of similar node pairs. Secondly, based on the connected branches composed of similar node pairs, the network is further divided into several similar node sets. Thirdly, to balance the scale gap of different communities, the Grasshopper Optimization Algorithm, (i.e., GOA) is introduced to combine the local attribute (i.e., conductance) and global attribute (i.e., modularity) together to aggregate similar node sets into potential (or final) communities. Finally, the experimental results show that PSA not only controls the difference among communities well, but also outperforms the other four popular algorithms in terms of two metrics. Moreover, we propose a community-based resource discovery method (or scheme), named as Community-assisted Short-distance-query Resource Discovery algorithm (i.e., CSRD) to further verify the efficiency of PSA. The results show that the resource discovery efficiency of CSRD using PSA is better compared with other algorithms.https://ieeexplore.ieee.org/document/9130144/Community detectiongrasshopper optimization algorithmInternet of Thingsnon-overlapping communityresources discovery |
| spellingShingle | Yizhe Li Hui Xia Rui Zhang Benxu Hu Xiangguo Cheng A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things IEEE Access Community detection grasshopper optimization algorithm Internet of Things non-overlapping community resources discovery |
| title | A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things |
| title_full | A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things |
| title_fullStr | A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things |
| title_full_unstemmed | A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things |
| title_short | A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things |
| title_sort | novel community detection algorithm based on paring splitting and aggregating in internet of things |
| topic | Community detection grasshopper optimization algorithm Internet of Things non-overlapping community resources discovery |
| url | https://ieeexplore.ieee.org/document/9130144/ |
| work_keys_str_mv | AT yizheli anovelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT huixia anovelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT ruizhang anovelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT benxuhu anovelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT xiangguocheng anovelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT yizheli novelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT huixia novelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT ruizhang novelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT benxuhu novelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings AT xiangguocheng novelcommunitydetectionalgorithmbasedonparingsplittingandaggregatingininternetofthings |