Software Defined Network-based control system for an efficient traffic management for emergency situations in smart cities

被引:61
作者
Rego, Albert [1 ]
Garcia, Laura [1 ]
Sendra, Sandra [1 ,2 ]
Lloret, Jaime [1 ]
机构
[1] Univ Politecn Valencia, Valencia, Spain
[2] Univ Granada, Telemat & Commun Dept TSTC, Dept Signal Theory, Granada, Spain
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2018年 / 88卷
关键词
Software Defined Networks (SDN); Internet of Things (loT); Smart city; Emergency situations; Quick evacuation; Traffic; Energy consumption; Cloud; Network performance; Jitter; Delay; THINGS; MODEL;
D O I
10.1016/j.future.2018.05.054
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Smart cities provide new applications based on Internet of Things (loT) technology. Moreover, Software Defined Networks (SDNs) offer the possibility of controlling the network based on applications requirements. One of the main problems that arise when an emergency happens is minimizing the delay time in emergency resource forwarding so as to reduce both human and material damages. In this paper, a new control system based on the integration of SDN and loT in smart city environments is proposed. This control system actuates when an emergency happens and modifies dynamically the routes of normal and emergency urban traffic in order to reduce the time that the emergency resources need to get to the emergency area. The architecture is based on a set of loT networks composed by traffic lights, traffic cameras and an algorithm. The algorithm controls the request of resources and the modification of routes in order to ease the movement of emergency service units. Afterwards, the proposal is tested by emulating a Smart City as a SDN-utilizing Mininet. The experiments show that the delay of the emergency traffic improves in a 33% when the algorithm is running. Moreover, the energy consumed by the loT nodes is modeled and the obtained results display that it increases linearly with the number of nodes, therefore, the proposal is scalable. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:243 / 253
页数:11
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