@inproceedings{li_online_2018,
	address = {Beijing, China},
	title = {Online {Data} {Traffic} {Steering} in {Software}-{Defined} {Autonomous} {Vehicle} {Networks}},
	isbn = {978-1-5386-7005-7},
	url = {https://ieeexplore.ieee.org/document/8641236/},
	doi = {10.1109/ICCChina.2018.8641236},
	abstract = {In the past decade, autonomous driving technologies have experienced a significant growth. In order to meet the increasing data transmission demands from autonomous vehicles (AVs), a novel network paradigm connecting AVs with the Internet is needed. In this paper, we first present the Software-Defined Autonomous Vehicle Networks (SD-AVN) framework to bridge the gap by introducing Software Defined Networking (SDN) and fog computing technologies. With SDN, we focus on a centralized routing problem in SD-AVN, and our intent is to minimize the overall transmission cost by reducing the usage of 5G base stations (BSs). Motivated by this, we formulate the global routing problem as a mixed integer programming (MIP) problem and develop an online log-competitive approximation algorithm to solve it. After that, we also explain that the computation-intensive routing tasks can be distributed to different fog controllers to reduce the scheduling time and end-to-end delay. Experimental results validate the effectiveness of the proposed algorithm in comparison with other two routing heuristics.},
	language = {en},
	urldate = {2022-10-04},
	booktitle = {2018 {IEEE}/{CIC} {International} {Conference} on {Communications} in {China} ({ICCC})},
	publisher = {IEEE},
	author = {Li, Xiaoxi and Zhang, Chi},
	month = aug,
	year = {2018},
	pages = {330--334},
}

{"_id":"dd6FcwvZgzGJhZBHf","bibbaseid":"li-zhang-onlinedatatrafficsteeringinsoftwaredefinedautonomousvehiclenetworks-2018","author_short":["Li, X.","Zhang, C."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","address":"Beijing, China","title":"Online Data Traffic Steering in Software-Defined Autonomous Vehicle Networks","isbn":"978-1-5386-7005-7","url":"https://ieeexplore.ieee.org/document/8641236/","doi":"10.1109/ICCChina.2018.8641236","abstract":"In the past decade, autonomous driving technologies have experienced a significant growth. In order to meet the increasing data transmission demands from autonomous vehicles (AVs), a novel network paradigm connecting AVs with the Internet is needed. In this paper, we first present the Software-Defined Autonomous Vehicle Networks (SD-AVN) framework to bridge the gap by introducing Software Defined Networking (SDN) and fog computing technologies. With SDN, we focus on a centralized routing problem in SD-AVN, and our intent is to minimize the overall transmission cost by reducing the usage of 5G base stations (BSs). Motivated by this, we formulate the global routing problem as a mixed integer programming (MIP) problem and develop an online log-competitive approximation algorithm to solve it. After that, we also explain that the computation-intensive routing tasks can be distributed to different fog controllers to reduce the scheduling time and end-to-end delay. Experimental results validate the effectiveness of the proposed algorithm in comparison with other two routing heuristics.","language":"en","urldate":"2022-10-04","booktitle":"2018 IEEE/CIC International Conference on Communications in China (ICCC)","publisher":"IEEE","author":[{"propositions":[],"lastnames":["Li"],"firstnames":["Xiaoxi"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Chi"],"suffixes":[]}],"month":"August","year":"2018","pages":"330–334","bibtex":"@inproceedings{li_online_2018,\n\taddress = {Beijing, China},\n\ttitle = {Online {Data} {Traffic} {Steering} in {Software}-{Defined} {Autonomous} {Vehicle} {Networks}},\n\tisbn = {978-1-5386-7005-7},\n\turl = {https://ieeexplore.ieee.org/document/8641236/},\n\tdoi = {10.1109/ICCChina.2018.8641236},\n\tabstract = {In the past decade, autonomous driving technologies have experienced a significant growth. In order to meet the increasing data transmission demands from autonomous vehicles (AVs), a novel network paradigm connecting AVs with the Internet is needed. In this paper, we first present the Software-Defined Autonomous Vehicle Networks (SD-AVN) framework to bridge the gap by introducing Software Defined Networking (SDN) and fog computing technologies. With SDN, we focus on a centralized routing problem in SD-AVN, and our intent is to minimize the overall transmission cost by reducing the usage of 5G base stations (BSs). Motivated by this, we formulate the global routing problem as a mixed integer programming (MIP) problem and develop an online log-competitive approximation algorithm to solve it. After that, we also explain that the computation-intensive routing tasks can be distributed to different fog controllers to reduce the scheduling time and end-to-end delay. Experimental results validate the effectiveness of the proposed algorithm in comparison with other two routing heuristics.},\n\tlanguage = {en},\n\turldate = {2022-10-04},\n\tbooktitle = {2018 {IEEE}/{CIC} {International} {Conference} on {Communications} in {China} ({ICCC})},\n\tpublisher = {IEEE},\n\tauthor = {Li, Xiaoxi and Zhang, Chi},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {330--334},\n}\n\n","author_short":["Li, X.","Zhang, C."],"key":"li_online_2018","id":"li_online_2018","bibbaseid":"li-zhang-onlinedatatrafficsteeringinsoftwaredefinedautonomousvehiclenetworks-2018","role":"author","urls":{"Paper":"https://ieeexplore.ieee.org/document/8641236/"},"metadata":{"authorlinks":{}},"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero/_MingYAN_","dataSources":["7bvyz9GrWb3E3F8y3"],"keywords":[],"search_terms":["online","data","traffic","steering","software","defined","autonomous","vehicle","networks","li","zhang"],"title":"Online Data Traffic Steering in Software-Defined Autonomous Vehicle Networks","year":2018}