On the number of candidates in opportunistic routing for multi-hop wireless networks
On the number of candidates in opportunistic routing for multi-hop wireless networks
复制标题
多跳无线网络机会路由中的候选数
DOI：
10.1145/2508222.2508224
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Sonny Chaiwala
中科院分区：
文献类型：
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作者：
A. Darehshoorzadeh;M. Almulla;A. Boukerche;Sonny Chaiwala
启发式路由（OR）是一种新的模式，已被研究作为一种新的方式来提高多跳无线网络的性能，通过利用无线介质的广播性质。与传统路由相比，在OR中，选择一组有序的节点作为潜在的下一跳转发器（候选者）。在OR中使用更多数量的候选减少了网络中的传输数量，但是这是以增加信令开销以及具有重复传输的可能性为代价的，这反过来降低了OR协议的性能。每个节点可以选择的候选人的数量是一个问题，在文献中没有得到很好的研究。在本文中，我们提出了一个基于距离的最大候选估计数（D-MACE）作为一种方法来找到在每个节点的候选人的数量。与传统的OR方法不同，D-MACE根据节点与目的地之间的距离减少每个节点中的候选节点数量。我们评估我们的建议的性能，使用两个相关的候选人选择算法。我们的研究结果表明，D-MACE有效地减少了网络中选择的候选人的数量，从而提高了网络性能的情况下，在所有节点的候选人数量相同。
Opportunistic Routing (OR) is a new paradigm that has been investigated as a new way to improve the performance of multihop wireless networks by exploiting the broadcast nature of the wireless medium. In contrast to traditional routing, in OR an ordered set of nodes is selected as potential next-hop forwarders (candidates). Using more number of candidates in OR decreases the number of transmissions in the network, but this comes at the cost of increasing the signaling overhead and also the possibility of having duplicated transmissions which in turn reduces the performance of the OR protocol. The number of candidates that each node can select is an issue which is not well investigated in the literature. In this paper, we propose a Distance-based MAximum number of Candidate Estimation (D-MACE) as an approach to find the number of candidates in each node. In contrast to the traditional approaches in OR which consider an identical number of candidates for all nodes, D-MACE reduces the number of candidates in each node according to the distance between the node and the destination. We evaluate the performance of our proposal, using two relevant candidate selection algorithms. Our results show that D-MACE reduces the number of selected candidates effectively in the network, which improves the network performance compared to the case with the same number of candidates in all nodes.