2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014)最新文献_第3页

V2X demonstration V2X示范

2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014) Pub Date : 2014-09-01 DOI: 10.1109/WIVEC.2014.6953267

Rekha Signoria, Joseph Peruski, Lars Wolleschensky

引用次数: 0

Comparing LIMERIC and DCC approaches for VANET channel congestion control 比较LIMERIC和DCC方法在VANET信道拥塞控制中的应用

2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014) Pub Date : 2014-09-01 DOI: 10.1109/WIVEC.2014.6953217

G. Bansal, Bin Cheng, Ali Rostami, Katrin Sjöberg, J. Kenney, M. Gruteser

{"title":"Comparing LIMERIC and DCC approaches for VANET channel congestion control","authors":"G. Bansal, Bin Cheng, Ali Rostami, Katrin Sjöberg, J. Kenney, M. Gruteser","doi":"10.1109/WIVEC.2014.6953217","DOIUrl":"https://doi.org/10.1109/WIVEC.2014.6953217","url":null,"abstract":"Channel congestion is one of the major challenges for IEEE 802.11p-based vehicular ad hoc networks. Unless controlled, congestion increases with vehicle density, leading to high packet loss and degraded safety application performance. In this paper, we study two classes of congestion control - reactive and adaptive. The reactive approach is represented by the Decentralized Congestion Control (DCC) framework defined in ETSI. The adaptive approach is represented by the LIMERIC linear control algorithm. Both approaches control safety message transmission as a function of channel load (i.e. Channel Busy Ratio, CBR). A reactive approach uses CBR directly, defining an appropriate transmission behavior for each CBR value, e.g. via a table lookup. By contrast, an adaptive approach identifies the transmission behavior that drives CBR to a target channel load, thus achieving the best message throughput possible for any given vehicle density. The paper considers two variations of DCC, one in which it serves as a traffic shaping “gatekeeper” above the MAC sublayer, and another in which it additionally limits safety message generation at the facilities layer. The paper has two main results. First, it is shown that LIMERIC generally outperforms both DCC variations in a winding road scenario with various vehicle densities. Inter-packet reception gap and position tracking error are the primary metrics. This advantage is due to primarily LIMERIC's ability to achieve a target load consistent with maximum throughput and vehicle awareness. Second, it is shown that both DCC variations are subject to steady state oscillations, and the case in which DCC also limits message generation is subject to truly unstable variations. The paper uses NS-2 simulation results to support these conclusions.","PeriodicalId":410528,"journal":{"name":"2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128931874","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}

引用次数: 52

Spectrum sensing with energy detection in cognitive Vehicular Ad hoc Networks 基于能量检测的认知车载自组织网络频谱感知

2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014) Pub Date : 2014-09-01 DOI: 10.1109/WIVEC.2014.6953263

Xiaomin Qian, L. Hao

引用次数: 15

Wireless sensor network-assisted, autonomous mapping with information-theoretic utility 无线传感器网络辅助，具有信息论效用的自主映射

2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014) Pub Date : 2014-09-01 DOI: 10.1109/WIVEC.2014.6953270

Steffen Beyme, C. Leung

{"title":"Wireless sensor network-assisted, autonomous mapping with information-theoretic utility","authors":"Steffen Beyme, C. Leung","doi":"10.1109/WIVEC.2014.6953270","DOIUrl":"https://doi.org/10.1109/WIVEC.2014.6953270","url":null,"abstract":"A mobile, autonomous platform is assisted by a wireless sensor network in its task of inferring a map of the spatial distribution of a physical quantity that is measured by the sensor nodes. Sensor nodes initiate a broadcast in the network, when the measured quantity assumes a value in the range of interest. Specifically, we consider randomly deployed networks of location-agnostic wireless sensor nodes, which broadcast messages by flooding. The node-to-node delays are assumed to be random. In networks of this type, the hop count of a broadcast message, given the distance from the source node, can be approximated by a simple parametric distribution. The mobile platform can interrogate a nearby sensor node to obtain, with a given success probability, the hop counts of the broadcast messages originating from different source nodes. By fusing successive hop count observations, the mobile platform infers the locations of the source nodes and thereby, the spatial distribution of the quantity of interest. The path taken by the mobile platform should minimize the resulting mapping error as quickly as possible. We propose an information-driven path planning approach, in which the mobile platform acts by maximizing a weighted sum of myopic, mutual information gains. We show by simulation, that suitable control of the weights is effective at reducing the error between the true and the inferred map, by preventing the information gain to be dominated by only a few source nodes.","PeriodicalId":410528,"journal":{"name":"2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131705327","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}

引用次数: 1