Pub Date : 2016-06-27DOI: 10.1109/IGBSG.2016.7539428
Han-Wen Liang, Chih-Hsiang Ho, Li-Sheng Chen, W. Chung, Shih-Yi Yuan, S. Kuo
This paper proposes a deterministic propagation model for Coverage Hole Detection (CHD). In the well known 3GPP and the 4G mobile telecommunications technology, the minimization of drive test is an important issue, where CHD is often conducted by the costly drive test. This paper utilizes the radio link failure report mechanism specified in 4G to achieve CHD, which can significantly reduce the costly drive tests. During CHD, radio propagation model is required to reconstruct the radio map of target cell. In general, deterministic propagation model requires precise structural information of the cell, and statistical propagation model assumes the existence of spatial correlation, which may be unavailable due to 1) the absence of spatial correlation information and 2) the high cost in learning the required parameters. This paper targets on the scenario where prior terrain information and spatial correlation are unavailable, which is a more practical assumption in CHD problem.
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We present scheduling policies that can be used by Micro Grids (MGs) with the possibility of energy production, consumption and storage, in the context of a novel Smart Grid architecture. Assuming a Day-Ahead market, we investigate the management of resources so as to achieve higher profit for the MGs under various operating scenarios. The possibility of cooperation among MGs in the presence of forecast errors is also studied, demonstrating that it can lead to more intelligent and profitable operation of the MG resources. The profits of cooperation among MGs whose production patterns have positive, zero, or negative correlation are assessed.
{"title":"Micro grid scheduling policies, forecasting errors, and cooperation based on production correlation","authors":"Georgios Tsaousoglou, Prodromos Makris, Emmanouel Varvarigos","doi":"10.1109/IGBSG.2016.7539445","DOIUrl":"https://doi.org/10.1109/IGBSG.2016.7539445","url":null,"abstract":"We present scheduling policies that can be used by Micro Grids (MGs) with the possibility of energy production, consumption and storage, in the context of a novel Smart Grid architecture. Assuming a Day-Ahead market, we investigate the management of resources so as to achieve higher profit for the MGs under various operating scenarios. The possibility of cooperation among MGs in the presence of forecast errors is also studied, demonstrating that it can lead to more intelligent and profitable operation of the MG resources. The profits of cooperation among MGs whose production patterns have positive, zero, or negative correlation are assessed.","PeriodicalId":348843,"journal":{"name":"2016 2nd International Conference on Intelligent Green Building and Smart Grid (IGBSG)","volume":"557 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132303366","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}
Software-Defined Networking (SDN) consists of two planes: the control and the forwarding plane. The control plane is moved out of the switch and into the separate, centralized controller, and is responsible for configuring the switch and programming the paths to be used by data flows. The controller hosting the applications collects information from the OpenFlow switch using the OpenFlow protocol and manipulates the forwarding of packets. This paper is to implement a QoS/QoE mapping and adjusting application that is used by the ISP to monitor the user-perceived QoE after accessing the service. The application is implemented on the RYU controller platform to monitor the performance of the OpenvSwitch-based OpenFlow switch. The implementation results show that the designed application can directly reflect the perceived quality of users and provide the ISP with valuable information for offering higher quality services.
SDN (Software-Defined Networking)分为两个平面:控制平面和转发平面。控制平面从交换机移到独立的集中式控制器中，负责配置交换机并对数据流使用的路径进行编程。承载应用程序的控制器使用OpenFlow协议从OpenFlow交换机收集信息，并操纵数据包的转发。本文的目的是实现一个QoS/QoE映射和调整应用程序，用于ISP在访问服务后监控用户感知的QoE。该应用程序在RYU控制器平台上实现，用于监控基于openvswitch的OpenFlow交换机的性能。实施结果表明，所设计的应用程序能够直接反映用户的感知质量，为ISP提供有价值的信息，以提供更高质量的服务。
{"title":"The implementation of a QoS/QoE mapping and adjusting application in software-defined networks","authors":"Wu-Hsiao Hsu, Xinghui Wang, Sheng-Cheng Yeh, Ping-Sheng Huang","doi":"10.1109/IGBSG.2016.7539431","DOIUrl":"https://doi.org/10.1109/IGBSG.2016.7539431","url":null,"abstract":"Software-Defined Networking (SDN) consists of two planes: the control and the forwarding plane. The control plane is moved out of the switch and into the separate, centralized controller, and is responsible for configuring the switch and programming the paths to be used by data flows. The controller hosting the applications collects information from the OpenFlow switch using the OpenFlow protocol and manipulates the forwarding of packets. This paper is to implement a QoS/QoE mapping and adjusting application that is used by the ISP to monitor the user-perceived QoE after accessing the service. The application is implemented on the RYU controller platform to monitor the performance of the OpenvSwitch-based OpenFlow switch. The implementation results show that the designed application can directly reflect the perceived quality of users and provide the ISP with valuable information for offering higher quality services.","PeriodicalId":348843,"journal":{"name":"2016 2nd International Conference on Intelligent Green Building and Smart Grid (IGBSG)","volume":"303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132691181","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 : 2016-06-27DOI: 10.1109/IGBSG.2016.7539410
Yu-Min Lin, H. Kuo, A. Wu
Wireless sensor networks (WSNs) show immense promise in many applications, such as environmental monitoring and remotely metering. Compressive sensing (CS) is a novel signal processing that has been envisioned as a useful regime to address the energy and scaling constraints in WSNs. CS is able to move the burden of sensory nodes to central cloud/server. However, prevailing CS reconstruction algorithms are vulnerable to noise. In this paper, we exploit the natural noise-tolerance property of least mean square (LMS) adaptive filter and propose a greedy-LMS algorithm for CS reconstruction. When SNR is 48dB, greedy-LMS algorithm achieves 16% and 47% higher successful rate than BPDN and OMP, respectively. In addition, the computational complexity of greedy-LMS is competitive with OMP.
{"title":"Robust LMS-based compressive sensing reconstruction algorithm for noisy wireless sensor networks","authors":"Yu-Min Lin, H. Kuo, A. Wu","doi":"10.1109/IGBSG.2016.7539410","DOIUrl":"https://doi.org/10.1109/IGBSG.2016.7539410","url":null,"abstract":"Wireless sensor networks (WSNs) show immense promise in many applications, such as environmental monitoring and remotely metering. Compressive sensing (CS) is a novel signal processing that has been envisioned as a useful regime to address the energy and scaling constraints in WSNs. CS is able to move the burden of sensory nodes to central cloud/server. However, prevailing CS reconstruction algorithms are vulnerable to noise. In this paper, we exploit the natural noise-tolerance property of least mean square (LMS) adaptive filter and propose a greedy-LMS algorithm for CS reconstruction. When SNR is 48dB, greedy-LMS algorithm achieves 16% and 47% higher successful rate than BPDN and OMP, respectively. In addition, the computational complexity of greedy-LMS is competitive with OMP.","PeriodicalId":348843,"journal":{"name":"2016 2nd International Conference on Intelligent Green Building and Smart Grid (IGBSG)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115440976","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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