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Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

机译:支持SDN的移动无线网络中的协同众包的拥塞控制和流量调度

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摘要

Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT), targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN). This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA) is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.
机译:当前,已经在移动网络和物联网(IoT)中实现了许多基于众包的移动应用程序,其目标是实时服务和推荐。协作众包中频繁的信息交换和数据传输被大量注入当前的通信网络中,这对移动无线网络(MWN)构成了巨大挑战。本文针对软件定义的MWN中的流量调度和负载均衡问题,设计了一种混合路由转发方案以及一种拥塞控制算法,以实现可行的解决方案。流量调度算法首先根据任务的数量以升序对任务进行排序,然后使用贪心方案对其进行求解。在提出的拥塞控制方案中,首先将交通分配转换为多背包问题,然后利用人工鱼群算法(AFSA)解决此问题。实际网络拓扑的数值结果表明,与传统方案相比,所提出的拥塞控制和流量调度方案可以实现负载均衡,降低网络拥塞的可能性,提高网络吞吐量。

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