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基于跨层包大小优化的DTN节点存储资源管理机制

  • 姜福凯 ,
  • 卢汉成
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  • 中国科学技术大学信息网络实验室, 合肥 230027

收稿日期: 2014-01-21

  修回日期: 2014-04-14

基金资助

国家自然科学基金(61170231,61390513)和中国科学技术大学创新团队项目(WK2100100021)资助

A storage management scheme based on cross-layer packet size optimization in DTN

  • JIANG Fukai ,
  • LU Hancheng
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  • Information Network Lab, University of Science and Technology of China, Hefei 230027, China

Received date: 2014-01-21

  Revised date: 2014-04-14

摘要

在延迟容忍网络中,应用数据的成功交付依赖于节点存储器的保管.提高节点存储资源利用率有助于减轻网络拥塞,增加网络容量.DTN各层协议数据单元大小影响节点存储资源使用效率,提出一种基于跨层包大小优化的节点存储资源管理机制OSUS.OSUS可根据当前信道状况自适应调节Bundle大小和传输层帧大小,最大化节点存储资源利用率.实验仿真表明,相比于传统不采用自适应机制的方案,OSUS可以提升平均15%的节点存储资源利用率.

本文引用格式

姜福凯 , 卢汉成 . 基于跨层包大小优化的DTN节点存储资源管理机制[J]. 中国科学院大学学报, 2014 , 31(6) : 836 -842 . DOI: 10.7523/j.issn.2095-6134.2014.06.016

Abstract

Delivery of the application data in delay tolerant network relies on the custody transfer provided by the node storage. Fast release of the occupied node storage is significant for reducing congestion and enhancing network capacity. Studies have shown that the storage efficiency is affected by the size of packet at various network layers. We propose a storage management scheme based on cross-layer packet size optimization, OSUS. OSUS can dynamically adjust Bundle size and the transport layer frame size to maximize the node storage utilization. Simulation results show that, compared with traditional schemes where joint optimization algorithms are not adopted, OSUS can bring 15% improvement on average in the node storage utilization.

参考文献

[1] Cerf V, Burleigh S, Hooke A, et al. Delay tolerant network architecture[S]. RFC 4838, 2007.

[2] Zhang X, Neglia G, Kurose J, et al. Performance modeling of epidemic routing[J]. Computer Networks, 2007, 51(10): 2 867-2 891.

[3] Rashid S, Abdullah A, Ayub Q, et al. Dynamic prediction based multi queue (DPMQ) drop policy for probabilistic routing protocols of delay tolerant network[J]. Journal of Network and Computer Applications, 2013, 36(5): 1 395-1 402.

[4] Lenas S A, Dimitriou S, Tsapeli F, et al. Queue management architecture for delay tolerant networking[C]//WWIC. 2011: 470-482.

[5] Elwhishi A, Ho P H, Naik K, et al. A novel message scheduling framework for delay tolerant networks routing[J]. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(5): 871-880.

[6] Rashid S, Ayub Q, Zahid M S M, et al. Message drop control buffer management policy for dtn routing protocols[J]. Wireless Personal Communications, 2013, 72(1): 653-669.

[7] Shin K, Kim K, Kim S. Traffic management strategy for delay-tolerant networks[J]. Journal of Network and Computer Applications, 2012, 35(6): 1 762-1 770.

[8] Samaras C V, Tsaoussidis V. Adjusting transport segmentation policy of DTN bundle protocol under synergy with lower layers[J]. Journal of Systems and Software, 2011, 84(2): 226-237.

[9] Khalili R, Salamatian K. A new analytic approach to evaluation of packet error rate in wireless networks[C]//Proceedings of the 3rd Annual Communication Networks and Services Research Conference. 2005: 333-338.

[10] Ramadas M, Burleigh S, Farrell S. Licklider transmission protocol-specification[S]. RFC 5326, 2008.

[11] Samaras C V, Tsaoussidis V. Design of delay tolerant transport protocol (DTTP) and its evaluation for Mars[J]. Acta Astronautica, 2010, 67(7/8): 863-880.

[12] Papastergiou G, Psaras I, Tsaoussidis V. Deep space transport protocol: a novel transport scheme for space DTNs[J]. Computer Communications, 2009, 32(16): 1 757-1 767.

[13] Jiang F K, Lu H C. Packet size optimization in delay tolerant networks[C]//Proceedings of the 11th Annual Consumer Communications and Networking Conference. 2014.

[14] Boyd S, Vandenberghe L. Convex optimization[M]. Cambridge University Press, 2004.

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