基于一致性哈希算法和Ckafka技术的IMS电话实时录音系统
作者:

IMS Telephone Real-Time Recording System Based on Consistent Hash Algorithm and Ckafka
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [18]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    基于电路交换的传统电话录音系统因其结构复杂,存储的不便捷和非实时性的特点,已经无法满足新时代行政办公对高效,即时的通话录音需求,因此,提出一种基于电力IMS的电话实时录音系统.首先分析了电力IMS交换网中电话终端实时录音的业务需求;其次介绍了系统的实现流程,阐明了系统的关键技术:利用录音服务器对其镜像端口的SIP报文进行解析获得媒体流并解码、采用一致性哈希算法的内存数据库作为解码数据的缓存机制、利用Ckafka技术在两者之间构建实时数据通道;最后就响应时间、吞吐量、容错能力和推送的最大时延这四项指标对录音服务器进行性能分析,结果表明该系统的实时性强,吞吐量大,具备一定的容错能力,并能实现多服务器之间的负载均衡.

    Abstract:

    The traditional circuit-switched telephone recording system has been unable to meet the needs of efficient and instant call recording in the new era administrative office due to its complicated structure, inconvenient storage, and non-real-time characteristics. Therefore, this paper presents a real-time recording system for power IMS telephone terminal to solve these problems. First of all, the article analyzes the business needs of real-time recording of telephone terminals in the power IMS exchange network. Secondly, the article introduces the implementation process of the system and clarifies the key technologies of the system: the system uses the recording server to parse the SIP message of its mirrored port for obtaining the media stream and decoding, and consistent Hash algorithm memory database is used as decoding data caching mechanism, and the message queue between the both is Ckafka. Finally, the performance of the recording server is analyzed based on the four indicators of response time, throughput, fault tolerance, and maximum delay. The analysis shows that the system has strong real-time performance, large throughput, certain fault tolerance, and load balancing.

    参考文献
    [1] 马文学, 王龙龙, 戎烁, 等. IMS网络业务触发体系架构的研究. 计算机与网络, 2019, 45(15):69-71.[doi:10.3969/j.issn.1008-1739.2019.15.054
    [2] 许苏明, 王忠民. SIP协议及其应用. 世界电信, 2002, (10):45-48
    [3] 梁东杰. 计算机通信网安全协议的分析. 通讯世界, 2019, 26(5):133-134.[doi:10.3969/j.issn.1006-4222.2019.05.086
    [4] 王计艳, 李赟, 董勋, 等. 核心网未来网络架构演进. 电信科学, 2015, 31(S1):140-147
    [5] 陈子怡. 基于C语言的计算机编程技术研究. 电脑编程技巧与维护, 2018, 401(11):63-64, 83.[doi:10.3969/j.issn.1006-4052.2018.11.024
    [6] Ji ZL, Ganchev I, O'Droma M, et al. A distributed Redis framework for use in the UCWW. Proceedings of 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery. Shanghai, China. 2014. 241-244.
    [7] Bhole RH, Chapte VM, Karve AC. A study of apache Kafka in big data stream processing. Proceedings of 2018 International Conference on Information, Communication, Engineering and Technology. Pune, India. 2018. 110-113.
    [8] 李浩杰, 杜军威, 朱桂新. 基于分布式搜索引擎的消息中间件设计. 青岛科技大学学报(自然科学版), 2016, 37(1):102-107
    [9] Sanchez VAB, Kim W, Eom Y, et al. EclipseMR:Distributed and parallel task processing with consistent hashing. Proceedings of 2007 IEEE International Conference on Cluster Computing. Honolulu, HI, USA. 2017. 322-332.
    [10] Thar K, Ullah S, Hong CS. Consistent hashing based cooperative caching and forwarding in content centric network. Proceedings of the 16th Asia-Pacific Network Operations and Management Symposium. Hsinchu, China. 2014. 176-179.
    [11] Hong T, Wu YT, Cao BY, et al. A dynamic data allocation method with improved load-balancing for cloud storage system. IET International Conference on Smart and Sustainable City 2013 (ICSSC 2013). Shanghai, China. 2013. 220-225.
    [12] 缪其勇. 分布式radius系统高可用负载均衡算法的设计与实现. 电子测试, 2018, (15):68-69.[doi:10.3969/j.issn.1000-8519.2018.15.028
    [13] Hsiao HC, Chang CW. A symmetric load balancing algorithm with performance guarantees for distributed hash tables. IEEE Transactions on Computers, 2013, 62(4):662-675.[doi:10.1109/TC.2012.13
    [14] Rieche S, Petrak L, Wehrle K. A thermal-dissipation-based approach for balancing data load in distributed hash tables. Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks. Tampa, FL, USA. 2004. 742-751.
    [15] Wang XM, Loguinov D. Load-balancing performance of consistent hashing:Asymptotic analysis of random node join. IEEE/ACM Transactions on Networking (TON), 2007, 15(4):892-905.[doi:10.1109/TNET.2007.893881
    [16] Liu Q, Cai WD, Shen J, et al. VPCH:A consistent hashing algorithm for better load balancing in a Hadoop environment. Proceedings of the 3rd International Conference on Advanced Cloud and Big Data. Yangzhou, China. 2015. 69-72.
    [17] 陈小惠, 彭世新, 卜宪德. IMS行政交换网集中录音系统的设计与实现. 电力信息与通信技术, 2016, 14(11):78-82
    [18] Zhang GX, Zhai CJ, Wang XY. Research of distributed data optimization storage and statistical method in the environment of big data. Proceedings of 2017 International Conference on Smart Grid and Electrical Automation (ICSGEA). Changsha, China. 2017. 612-617.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

江凇,王宝海,赵金城,宋江,段佳秀.基于一致性哈希算法和Ckafka技术的IMS电话实时录音系统.计算机系统应用,2020,29(5):88-93

复制
分享
文章指标
  • 点击次数:1549
  • 下载次数: 2445
  • HTML阅读次数: 1439
  • 引用次数: 0
历史
  • 收稿日期:2019-08-22
  • 最后修改日期:2019-09-10
  • 在线发布日期: 2020-05-07
  • 出版日期: 2020-05-15
文章二维码
您是第11207641位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号