https://scholars.lib.ntu.edu.tw/handle/123456789/580933
標題: | Interference and Outage in Clustered Wireless Sensor Networks with Cluster-Centric Data Collectors | 作者: | Hsieh H.-Y Huang H.-C. HUNG-YUN HSIEH |
關鍵字: | Aggregates; Laplace transforms; Petroleum reservoir evaluation; Poisson distribution; Aggregate interference; Analytical expressions; Analytical results; Clustered wireless sensor networks; Independence assumption; Mathematical tractability; Poisson cluster process; Poisson point process; Sensor nodes | 公開日期: | 2019 | 起(迄)頁: | 625-630 | 來源出版物: | 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018 | 摘要: | In many wireless sensor networks, the distribution of sensor nodes involved in data transmission may be clustered as induced by the underlying geographical factor or protocol design. Instead of using the homogeneous Poisson Point Process (PPP), related work has investigated the Poisson Cluster Process (PCP) for modeling the location distribution of sensor nodes and obtaining analytical results such as the aggregate interference and outage probability for such networks. Many research endeavors, however, assume that data collectors are randomly deployed independently of the sensor nodes. While such an assumption lends itself for mathematical tractability, it is not typically how data collectors are deployed to relay data from sensor nodes to the backbone network. To address this pitfall, in this paper we consider the scenario where data collectors are deployed at the centers, or parent points, of the clusters in PCP. Since the locations of data collectors and sensor nodes are correlated, the independence assumption adopted in most related work cannot be applied. We first derive the analytical expression of the Laplace transform of the aggregate interference at each data collector and then obtain the closed-form lower bound of the transmission success probability for each sensor node to transmit data to the nearby data collector. Numerical evaluation shows that the derived lower bound matches the simulation results very well. In addition, we have also shown that placing data collectors at cluster centers, while mathematically involved for analysis, can achieve significant performance gain compared to conventional scenarios where data collectors and sensor nodes are distributed independently without any coordination. ? 2018 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063077106&doi=10.1109%2fICCChina.2018.8641162&partnerID=40&md5=4bc21ec0b7aab25f13269e3c34c86c60 https://scholars.lib.ntu.edu.tw/handle/123456789/580933 |
DOI: | 10.1109/ICCChina.2018.8641162 |
顯示於: | 電機工程學系 |
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