Towards Traffic Load Balancing in Drone-Assisted Communications for IoT
Towards Traffic Load Balancing in Drone-Assisted Communications for IoT
复制标题
DOI：
10.1109/jiot.2018.2889503
复制
发表时间：
2019-04
影响因子：
10.6
通讯作者：
Q. Fan;N. Ansari
中科院分区：
文献类型：
--
作者：
Q. Fan;N. Ansari
边缘计算使物联网(IoT)设备收集的数据能够存储在本地FOG节点中并由其处理，并允许IoT用户同时通过这些节点访问IoT应用程序。在这种情况下，通信延迟严重影响物联网用户请求的响应时间。由于物联网用户[即用户设备(UE)]的动态分布，可以灵活部署在热点地区的无人机基站(DBS)可以通过缓解宏基站的繁重流量负载来改善物联网用户的无线时延。基于无人机的通信带来了两大挑战：1)DBS应该部署在流量需求较大的合适区域，以服务更多的UE；2)网络中的流量负载应该在宏BSS和DBS之间分配，以避免造成交通拥堵。因此，我们提出了一种无人机辅助雾化网络中的流量负载均衡方案，以最小化物联网用户的无线时延。在该方案中，我们将问题分解为两个子问题，并设计了两个分别优化DBS放置和用户关联的算法。已经建立了大量的仿真来验证所提出的方案的性能。
Edge computing enables data collected by Internet of Things (IoT) devices to be stored in and processed by local fog nodes as well as allows IoT users to access IoT applications via these nodes at the same time. In this case, the communications latency critically affects the response time of IoT user requests. Owing to the dynamic distribution of IoT users [i.e., user equipments (UEs)], drone base station (DBS), which can be flexibly deployed for hotspot areas, can potentially improve the wireless latency of IoT users by mitigating the heavy traffic loads of macro BSs. Drone-based communications poses two major challenges: 1) the DBS should be deployed in suitable areas with heavy traffic demands to serve more UEs and 2) the traffic loads in the network should be allocated among macro BSs and DBSs to avoid instigating traffic congestions. Therefore, we propose a traffic load balancing scheme in such drone-assisted fog network to minimize the wireless latency of IoT users. In the scheme, we divide the problem into two subproblems and design two algorithms to optimize the DBS placement and user association, respectively. Extensive simulations have been set up to validate the performance of the proposed scheme.