Oladiran G. Olaleye, Alaa Ali, Ahmed Aly, M. Iqbal, D. Perkins, M. Bayoumi
{"title":"为机会网络生成和设计频谱感知模块的框架","authors":"Oladiran G. Olaleye, Alaa Ali, Ahmed Aly, M. Iqbal, D. Perkins, M. Bayoumi","doi":"10.1109/UEMCON.2017.8249073","DOIUrl":null,"url":null,"abstract":"For improved spectrum utilization in opportunistic network (OppN), spectrum awareness (SA) metrics can be generated from the synthesis and analysis of both static and dynamic network parameters. However, there are several techniques and algorithms for evaluating network parameters. Hence, a standardized framework is needed for generating SA towards improved spectrum consumption. To the best of our knowledge, no such framework currently exist in literature. In this work, therefore, we propose a novel approach for constructing, justifying and improving SA modules for OppN. Our approach maps different SA metrics to network parameters, which we define as SA integrals. We derive the constant of proportionality (SA constant) between the metrics and the integrals as a function of reliability, computational complexity and latency. The derived SA constants can be used to justify and compare SA techniques and algorithms. Based on the results obtained from the modeling and simulation of an adhoc cognitive radio network, using QualNet, we illustrate the applicability of SA constant as an index (0.0 < SA constant < 1.0) for quantifying the level of SA derivable from any specified SA module.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Framework for generating and designing spectrum awareness modules for opportunistic networking\",\"authors\":\"Oladiran G. Olaleye, Alaa Ali, Ahmed Aly, M. Iqbal, D. Perkins, M. Bayoumi\",\"doi\":\"10.1109/UEMCON.2017.8249073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For improved spectrum utilization in opportunistic network (OppN), spectrum awareness (SA) metrics can be generated from the synthesis and analysis of both static and dynamic network parameters. However, there are several techniques and algorithms for evaluating network parameters. Hence, a standardized framework is needed for generating SA towards improved spectrum consumption. To the best of our knowledge, no such framework currently exist in literature. In this work, therefore, we propose a novel approach for constructing, justifying and improving SA modules for OppN. Our approach maps different SA metrics to network parameters, which we define as SA integrals. We derive the constant of proportionality (SA constant) between the metrics and the integrals as a function of reliability, computational complexity and latency. The derived SA constants can be used to justify and compare SA techniques and algorithms. Based on the results obtained from the modeling and simulation of an adhoc cognitive radio network, using QualNet, we illustrate the applicability of SA constant as an index (0.0 < SA constant < 1.0) for quantifying the level of SA derivable from any specified SA module.\",\"PeriodicalId\":403890,\"journal\":{\"name\":\"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UEMCON.2017.8249073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UEMCON.2017.8249073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Framework for generating and designing spectrum awareness modules for opportunistic networking
For improved spectrum utilization in opportunistic network (OppN), spectrum awareness (SA) metrics can be generated from the synthesis and analysis of both static and dynamic network parameters. However, there are several techniques and algorithms for evaluating network parameters. Hence, a standardized framework is needed for generating SA towards improved spectrum consumption. To the best of our knowledge, no such framework currently exist in literature. In this work, therefore, we propose a novel approach for constructing, justifying and improving SA modules for OppN. Our approach maps different SA metrics to network parameters, which we define as SA integrals. We derive the constant of proportionality (SA constant) between the metrics and the integrals as a function of reliability, computational complexity and latency. The derived SA constants can be used to justify and compare SA techniques and algorithms. Based on the results obtained from the modeling and simulation of an adhoc cognitive radio network, using QualNet, we illustrate the applicability of SA constant as an index (0.0 < SA constant < 1.0) for quantifying the level of SA derivable from any specified SA module.