论文标题
机会性路由指标:及时的一站式教程调查
Opportunistic Routing Metrics: A Timely One-Stop Tutorial Survey
论文作者
论文摘要
5G的高速,低潜伏期和异质性特征是许多新兴和经典无线应用程序的共同点,它使无线技术重新成为焦点。在多HP方案中,低功率和广泛网络中的连续连通性要求强调了对稀缺无线资源进行更有效的路由的需求。在这方面,利用无线媒体的广播性质在选定数量的偷听节点之间提供传输合作的机会主义路由(OR)变得比以往任何时候都更有希望。对于整体网络性能至关重要,该网络性能是由用户定义或指标嵌入或协议中的,即将参与传输优先级层次结构的位置。因此,选择或设计适当或指标的任务是至关重要的。多样性,专有符号以及或指标的客观各种性可能会导致感兴趣的研究人员失去洞察力并变得不知所措,从而使指标选择或设计努力密集型。尽管文献中没有任何全面或指标的调查,但是那些部分解决该主题的人是无尽的,并且缺乏详细的详细信息。此外,他们还提供了有关相关分类法和未来研究建议的有限见解。在本文中,从具有新外观或 / / / / / /或指标的自定义教程开始,我们为或者设计了一个新的框架或公制设计。引入新的分类学使我们能够采用大量模拟支持的结构化,调查和比较方法或指标。用统一符号提出的详尽覆盖范围或指标有足够的细节。提供了自我解释,易于抓紧和视觉友好的快速参考,可以独立于本文的其余部分使用。
High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by user-defined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper.