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延迟容忍网络的范围感知消息丢弃策略

Range aware message drop policy for delay tolerant networks.

作者信息

Khan Samiullah, Saeed Khalid, Majeed Muhammad Faran, Aurangzeb Khursheed, Ahmad Zahoor, Anwar Muhammad Shahid, Allayarov Piratdin

机构信息

Department of Computer Science, Shaheed Benazir Bhutto University Sheringal, Upper Dir, Khyber Pakhtunkhwa, Pakistan.

Department of Computer Science, Kohsar University Murree, Murree, Punjab, Pakistan.

出版信息

PeerJ Comput Sci. 2024 Jul 12;10:e2099. doi: 10.7717/peerj-cs.2099. eCollection 2024.

DOI:10.7717/peerj-cs.2099
PMID:39145252
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11323192/
Abstract

In delay tolerant networks (DTNs) the messages are often not delivered to the destination due to a lack of end-to-end connectivity. In such cases, the messages are stored in the buffer for a long time and are transmitted when the nodes come into the range of each other. The buffer size of each node has a limited capacity, and it cannot accommodate the new incoming message when the buffer memory is full, and as a result network congestion occurs. This leads to a low delivery probability and thus increases the overhead ratio. In this research work, a new buffer management scheme called Range Aware Drop (RAD) is proposed which considers metrics such as message size and time to live (TTL). RAD utilizes TTL as an important metric and as a result, reduces the unnecessary message drop. Simulation results reveal that RAD performs significantly better than drop oldest (DOA) and size aware drop (SAD) in terms of delivery probability and overhead ratio. The obtained results also revealed that the hop-count average of SAD is 3.9 and DOA is 3.4 while the hop-count average of RAD is just 1.7. Also, the message drop ratio of the RAD is 36.2% while SAD and DOA have message drop ratios of 73.3% and 84.9% respectively.

摘要

在延迟容忍网络(DTN)中,由于缺乏端到端连接,消息往往无法送达目的地。在这种情况下,消息会在缓冲区中长时间存储,并在节点相互进入通信范围时进行传输。每个节点的缓冲区大小具有有限的容量,当缓冲内存已满时,它无法容纳新传入的消息,从而导致网络拥塞。这会导致低交付概率,进而增加开销比率。在这项研究工作中,提出了一种名为范围感知丢弃(RAD)的新缓冲区管理方案,该方案考虑了消息大小和生存时间(TTL)等指标。RAD将TTL用作重要指标,从而减少了不必要的消息丢弃。仿真结果表明,在交付概率和开销比率方面,RAD的性能明显优于丢弃最旧消息(DOA)和大小感知丢弃(SAD)。获得的结果还表明,SAD的平均跳数为3.9,DOA的平均跳数为3.4,而RAD的平均跳数仅为1.7。此外,RAD的消息丢弃率为36.2%,而SAD和DOA的消息丢弃率分别为73.3%和84.9%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/3460d49193c5/peerj-cs-10-2099-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/4c34bdf5f2a9/peerj-cs-10-2099-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/13f6275f1fd3/peerj-cs-10-2099-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/0ac4755a21b7/peerj-cs-10-2099-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/1b149f8b1630/peerj-cs-10-2099-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/715b35d35e39/peerj-cs-10-2099-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/8bb8389ecfa1/peerj-cs-10-2099-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/e1d9ba96c51d/peerj-cs-10-2099-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/2ecb0ef087d6/peerj-cs-10-2099-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/86dc5c0be1b7/peerj-cs-10-2099-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/963ef1a6e495/peerj-cs-10-2099-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/3460d49193c5/peerj-cs-10-2099-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/4c34bdf5f2a9/peerj-cs-10-2099-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/13f6275f1fd3/peerj-cs-10-2099-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/0ac4755a21b7/peerj-cs-10-2099-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/1b149f8b1630/peerj-cs-10-2099-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/715b35d35e39/peerj-cs-10-2099-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/8bb8389ecfa1/peerj-cs-10-2099-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/e1d9ba96c51d/peerj-cs-10-2099-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/2ecb0ef087d6/peerj-cs-10-2099-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/86dc5c0be1b7/peerj-cs-10-2099-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/963ef1a6e495/peerj-cs-10-2099-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd2/11323192/3460d49193c5/peerj-cs-10-2099-g011.jpg

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