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一种用于智慧城市中基于物联网的大数据的新型资源分配与频谱碎片整理机制。

A Novel Resource Allocation and Spectrum Defragmentation Mechanism for IoT-Based Big Data in Smart Cities.

作者信息

Peng Yuhuai, Wang Jiaying, Tan Aiping, Wu Jingjing

机构信息

School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China.

Key Laboratory of Vibration and Control of Aero-Propulsion System of Ministry of Education, Northeastern University, Shenyang 110819, China.

出版信息

Sensors (Basel). 2019 Aug 6;19(15):3443. doi: 10.3390/s19153443.

Abstract

People's demand for high-traffic applications and the need for Internet of Things (IoT) are enormous in smart cities. The amount of data generated by virtual reality, high-definition video, and other IoT applications is growing at an exponential rate that far exceeds our expectations, and the types of data are becoming more diverse. It has become critical to reliably accommodate IoT-based big data with reasonable resource allocation in optical backbone networks for smart cities. For the problem of reliable transmission and efficient resource allocation in optical backbone networks, a novel resource allocation and spectrum defragmentation mechanism for massive IoT traffic is presented in this paper. Firstly, a routing and spectrum allocation algorithm based on the distance-adaptive sharing protection mechanism (DASP) is proposed, to obtain sufficient protection and reduce the spectrum consumption. The DASP algorithm advocates applying different strategies to the resource allocation of the working and protection paths. Then, the protection path spectrum defragmentation algorithm based on OpenFlow is designed to improve spectrum utilization while providing shared protection for traffic demands. The lowest starting slot-index first (LSSF) algorithm is employed to remove and reconstruct the optical paths. Numerical results indicate that the proposal can effectively alleviate spectrum fragmentation and reduce the bandwidth-blocking probability by 44.68% compared with the traditional scheme.

摘要

在智慧城市中,人们对高流量应用的需求以及对物联网(IoT)的需求极为巨大。虚拟现实、高清视频和其他物联网应用所产生的数据量正以指数级速度增长,远远超出我们的预期,并且数据类型也日益多样化。在智慧城市的光骨干网络中,通过合理的资源分配来可靠地承载基于物联网的大数据已变得至关重要。针对光骨干网络中的可靠传输和高效资源分配问题,本文提出了一种适用于海量物联网流量的新型资源分配和频谱碎片整理机制。首先,提出了一种基于距离自适应共享保护机制(DASP)的路由和频谱分配算法,以获得足够的保护并降低频谱消耗。DASP算法主张对工作路径和保护路径的资源分配应用不同的策略。然后,设计了基于OpenFlow的保护路径频谱碎片整理算法,以提高频谱利用率,同时为流量需求提供共享保护。采用最低起始时隙索引优先(LSSF)算法来移除和重建光路。数值结果表明,与传统方案相比,该方案能够有效缓解频谱碎片问题,并将带宽阻塞概率降低44.68%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2134/6695597/b597711cf092/sensors-19-03443-g001.jpg

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