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Improving DTNs Performance by Reduction of Bundles Redundancy using Clustering Algorithm

机译:通过使用聚类算法减少捆绑冗余来提高DTNS性能

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This article presents complex clustering algorithm for Delay Tolerant Networks (DTNs) including neighborhood discovery, cluster creation, and data distribution within cluster. The general idea is to reduce the amount of messages being sent and of buffer utilization, by taking advantage of the nodes tendency to create groups and to share similar mobility patterns among each other. The main purpose of the algorithm is to improve the network performance without major changes in communication schemes between nodes. Almost no extra message type is added. Most extra features are available thanks to adding small extra fields into transmitted packages. Neighborhood discovery is being realized passively by listening to other nodes messages. The proposed algorithms allow to reduce both the bandwidth occupation, as well as the problems related to the media access. Furthermore, it can increase message delivery probability thanks to intelligent package distribution inside created cluster. Simulations were carried out to evaluate the effectiveness of the proposed solution in terms of package delivery probability, mean buffer occupancy and mean hop number to delivery the message. Results of simulation show that this solution is not necessary or recommended for small-scale networks with few nodes using clustering algorithms. However, with increasing number of nodes and messages, the performance of non-clustered DTNs drops significantly while clustered network works efficiently.
机译:本文为延迟容差网络(DTN)提供复杂的聚类算法,包括群集内的邻域发现,群集创建和数据分发。一般思想是通过利用节点趋势来创建组并在彼此之间共享类似的移动性模式来减少正在发送和缓冲利用率的消息量。算法的主要目的是提高网络性能,没有节点之间的通信方案的主要变化。几乎没有添加额外的消息类型。由于将小额外的字段添加到传输的包装中,因此提供了大多数额外功能。通过收听其他节点消息被动地实现了邻里发现。所提出的算法允许减少带宽占用,以及与媒体访问相关的问题。此外,由于创建的群集内部智能包分发,它可以提高消息传递概率。进行了仿真以评估所提出的解决方案的有效性,在包装递送概率方面,平均缓冲占用和平均跳号来交付消息。仿真结果表明,使用聚类算法,不需要使用少数节点的小规模网络而不是必需的。然而,随着节点数量和消息数量的越来越多,非聚类DTN的性能显着下降,而聚类网络有效地工作。

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