Pub Date : 2017-04-01DOI: 10.1109/WOCC.2017.7929008
Nassima Merabtine, D. Djenouri, D. Zegour, El-sedik Lamini, Rima Bellal, Imene Ghaoui, Nabila Dahlal
A new centralized clustering protocol for periodic traffic wireless sensor networks is proposed in this paper. The proposed protocol uses one-step off-line cluster computation algorithm, where all the clustering schemes and their respective durations are calculated by the base station (BS) once at the network initialization. This provides the BS a global vision and enables it to reach better clustering schemes with adapted rounds' durations. It also eliminates costs proportional to periodic online re-clustering, using an energy prediction model. A new weight function is proposed to evaluate the chance of sensor-nodes to become CHs in a round. Experimental results demonstrate that the proposed protocol considerably prolong the network lifetime and the packet delivery ratio as compared to the LEACH-C protocol. The enhancement exceeds the double for the network lifetime and is more than ten times for packet delivery ratio.
{"title":"One-step clustering protocol for periodic traffic wireless sensor networks","authors":"Nassima Merabtine, D. Djenouri, D. Zegour, El-sedik Lamini, Rima Bellal, Imene Ghaoui, Nabila Dahlal","doi":"10.1109/WOCC.2017.7929008","DOIUrl":"https://doi.org/10.1109/WOCC.2017.7929008","url":null,"abstract":"A new centralized clustering protocol for periodic traffic wireless sensor networks is proposed in this paper. The proposed protocol uses one-step off-line cluster computation algorithm, where all the clustering schemes and their respective durations are calculated by the base station (BS) once at the network initialization. This provides the BS a global vision and enables it to reach better clustering schemes with adapted rounds' durations. It also eliminates costs proportional to periodic online re-clustering, using an energy prediction model. A new weight function is proposed to evaluate the chance of sensor-nodes to become CHs in a round. Experimental results demonstrate that the proposed protocol considerably prolong the network lifetime and the packet delivery ratio as compared to the LEACH-C protocol. The enhancement exceeds the double for the network lifetime and is more than ten times for packet delivery ratio.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":"30 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86877668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/WOCC.2017.7928985
B. Dingel, N. Madamopoulos
The need for photonic components with linear electric field has increased for both analog and digital communication systems as these systems evolve toward faster speed, higher spectral efficiency (SE), and wider bandwidth environments. Here, we present a common linearization platform for electric field coming from any Mach-Zehnder (MZ)-based devices. We show how this common platform has applications and advantages as linear Frequency Discriminator (FD) device for phase-modulated direct-detection Microwave Photonic Link (MPLs), and as linear Electric Field Modulator (LOFM) for multilevel coherent transmitter in digital optical communication systems.
{"title":"Linearization of photonic components for digital and analog optical fiber communication systems","authors":"B. Dingel, N. Madamopoulos","doi":"10.1109/WOCC.2017.7928985","DOIUrl":"https://doi.org/10.1109/WOCC.2017.7928985","url":null,"abstract":"The need for photonic components with linear electric field has increased for both analog and digital communication systems as these systems evolve toward faster speed, higher spectral efficiency (SE), and wider bandwidth environments. Here, we present a common linearization platform for electric field coming from any Mach-Zehnder (MZ)-based devices. We show how this common platform has applications and advantages as linear Frequency Discriminator (FD) device for phase-modulated direct-detection Microwave Photonic Link (MPLs), and as linear Electric Field Modulator (LOFM) for multilevel coherent transmitter in digital optical communication systems.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":"16 6 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75549038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.1109/WOCC.2017.7928975
Zhaomin Chen, C. Yeo, Bu-Sung Lee, C. Lau
Anomaly detection is critical given the raft of cyber attacks these days. It is thus essential to identify the network anomalies more accurately. In this paper, we propose a novel network anomaly detection system which combines random projections (sketches) and feature-based MSPCA to detect anomalous source IP addresses. By combining PCA and wavelet analysis, MSPCA can separate anomalous data efficiently. Incorporating with Sketch data structure enables our system to identify anomalous source IP addresses. In our proposed system, we extract several network flow-based features which are helpful in exposing the different kinds of attacks. We conduct two comparisons using real network traces from MAWI dataset. The results show that MSPCA-based method has better performance than PCA-based one. In addition, feature-based anomaly detection system is superior in detecting more subtle attacks than one based on packet counting.
{"title":"A novel anomaly detection system using feature-based MSPCA with sketch","authors":"Zhaomin Chen, C. Yeo, Bu-Sung Lee, C. Lau","doi":"10.1109/WOCC.2017.7928975","DOIUrl":"https://doi.org/10.1109/WOCC.2017.7928975","url":null,"abstract":"Anomaly detection is critical given the raft of cyber attacks these days. It is thus essential to identify the network anomalies more accurately. In this paper, we propose a novel network anomaly detection system which combines random projections (sketches) and feature-based MSPCA to detect anomalous source IP addresses. By combining PCA and wavelet analysis, MSPCA can separate anomalous data efficiently. Incorporating with Sketch data structure enables our system to identify anomalous source IP addresses. In our proposed system, we extract several network flow-based features which are helpful in exposing the different kinds of attacks. We conduct two comparisons using real network traces from MAWI dataset. The results show that MSPCA-based method has better performance than PCA-based one. In addition, feature-based anomaly detection system is superior in detecting more subtle attacks than one based on packet counting.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":"33 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78337888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-01DOI: 10.1109/WOCC.2017.7928996
Li-Chun Wang, Shao-Hung Cheng, Ang-Hsun Tsai
In this paper we present a data-driven power control (DDPC) approach to improve total cell throughput and energy efficiency of ultra-dense femtocells. Although femtocells can increase the capacity and coverage in an indoor environment, ultra-dense femtocells may consume a lot of energy and generate severe interference. We investigate a data-driven clustering approach to reduce co-tier interference among femtocells in a dense deployment scenario. The proposed DDPC approach periodically collects the operation data of dense femtocells, including reference signal received power (RSRP) from each user, the transmission power and the number of users per femtocell, and so on. The collected data are processed via the affinity propagation (AP) clustering algorithm to determine the cluster centers to perform power control. The AP clustering algorithm can automatically determine appropriate the number of clusters and the corresponding cluster centers for various femtocell densities. Simulation results show that the proposed DDPC approach can increase 41% higher total cell throughput and 64% higher energy efficiency respectively, compared to the approach without power control in the ultra-dense femtocells.
{"title":"Data-driven power control of ultra-dense femtocells: A clustering based approach","authors":"Li-Chun Wang, Shao-Hung Cheng, Ang-Hsun Tsai","doi":"10.1109/WOCC.2017.7928996","DOIUrl":"https://doi.org/10.1109/WOCC.2017.7928996","url":null,"abstract":"In this paper we present a data-driven power control (DDPC) approach to improve total cell throughput and energy efficiency of ultra-dense femtocells. Although femtocells can increase the capacity and coverage in an indoor environment, ultra-dense femtocells may consume a lot of energy and generate severe interference. We investigate a data-driven clustering approach to reduce co-tier interference among femtocells in a dense deployment scenario. The proposed DDPC approach periodically collects the operation data of dense femtocells, including reference signal received power (RSRP) from each user, the transmission power and the number of users per femtocell, and so on. The collected data are processed via the affinity propagation (AP) clustering algorithm to determine the cluster centers to perform power control. The AP clustering algorithm can automatically determine appropriate the number of clusters and the corresponding cluster centers for various femtocell densities. Simulation results show that the proposed DDPC approach can increase 41% higher total cell throughput and 64% higher energy efficiency respectively, compared to the approach without power control in the ultra-dense femtocells.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":" 28","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91415336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-01DOI: 10.1109/WOCC.2017.7928997
Hsin-An Hou, Li-Chun Wang
In this paper we present an algebraic analytical approach to estimate area spectrum efficiency (ASE) of interference-limited cellular mobile systems with small reuse distance ratio. In an ultra-dense network (UDN), the co-channel inter-site distance is very small (e.g. 2 times of cell radius). However, to the best of our knowledge, an accurate performance framework for cellular mobile network with small number of co-channel inter-site distance ratio is rarely seen in the literature. To improve the accuracy of expression, we take interference signals from the all interfering BSs on two-dimension and area spectral efficiency (ASE) into account, and derive the close-form expression for the downlink signal-to-interference plus noise ratio (SINR) by Newton's generalized binomial equation and triangle identities of a base station (BS) geometry model. Based on the SINR expression, we further derive tight approximation formulas of downlink spectral efficiency (SE)s and ASE. Moreover, the SINR close-form expression and the tight approximation for SE and ASE with small reuse distance ratio are also presented and validated.
{"title":"Area spectral efficiency for cellular networks with small reuse distance: An algebraic approach","authors":"Hsin-An Hou, Li-Chun Wang","doi":"10.1109/WOCC.2017.7928997","DOIUrl":"https://doi.org/10.1109/WOCC.2017.7928997","url":null,"abstract":"In this paper we present an algebraic analytical approach to estimate area spectrum efficiency (ASE) of interference-limited cellular mobile systems with small reuse distance ratio. In an ultra-dense network (UDN), the co-channel inter-site distance is very small (e.g. 2 times of cell radius). However, to the best of our knowledge, an accurate performance framework for cellular mobile network with small number of co-channel inter-site distance ratio is rarely seen in the literature. To improve the accuracy of expression, we take interference signals from the all interfering BSs on two-dimension and area spectral efficiency (ASE) into account, and derive the close-form expression for the downlink signal-to-interference plus noise ratio (SINR) by Newton's generalized binomial equation and triangle identities of a base station (BS) geometry model. Based on the SINR expression, we further derive tight approximation formulas of downlink spectral efficiency (SE)s and ASE. Moreover, the SINR close-form expression and the tight approximation for SE and ASE with small reuse distance ratio are also presented and validated.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":"241 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76950106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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