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Distributing jobs in Delay-Tolerant Networks: Is optimization worth it?

机译:在延迟容忍网络中分配作业:优化值得吗?

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Delay-Tolerant Networks (DTNs) refer to mobile wireless networks that lack continuous network connectivity among the nodes. To deal with such intermittent characteristics, DTNs use store-carry-and-forward based routing protocols instead of instantaneous end-to-end path transmissions. Many real-life applications of such networks have been identified and some of them pose complex computational challenges. DTN nodes, however, do not necessarily possess high degree of computational power and are also limited by their energy constraints. Distributed computing has the ability to solve computationally complex and lengthy problems by dividing them into many tasks, which are then spread over the network to be solved simultaneously, resulting in faster execution and significantly lower costs. In this paper, we study the prospect of distributed computing techniques in DTNs. We investigate different job distribution algorithms and their performance across multiple DTN scenarios. We simulate a distributed job processing system on top of a DTN for various scenarios and analyze the effect of node density, job slicing, and mobility models on their performance.
机译:时延容忍网络(DTN)指的是在节点之间缺乏连续网络连接的移动无线网络。为了处理这种间歇性特性,DTN使用基于存储转发的路由协议,而不是瞬时的端到端路径传输。已经确定了此类网络的许多实际应用,其中一些构成了复杂的计算挑战。但是,DTN节点不一定具有高度的计算能力,并且还受到其能量约束的限制。通过将分布式计算分为许多任务,分布式计算具有解决计算复杂和冗长问题的能力,然后将这些任务分散到要同时解决的网络中,从而可以更快地执行并显着降低成本。在本文中,我们研究了DTN中分布式计算技术的前景。我们研究了不同的工作分配算法及其在多个DTN场景中的性能。我们针对各种情况在DTN之上模拟了分布式作业处理系统,并分析了节点密度,作业切片和移动性模型对其性能的影响。

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