Despite extensive research efforts, underwater sensor networks (UWSNs) still suffer from serious performance issues due to their inefficient and uncoordinated channel access and resource management. For example, due to the lack of holistic knowledge on the network resources, existing decentralized routing protocols fail to provide globally optimal performance. On the other hand, Software Defined Networking (SDN), as a promising paradigm to provide prominent centralized solutions, can be employed to address the aforementioned issues in UWSNs. Indeed, SDN brings unprecedented opportunities to improve the network performance through the development of advanced algorithms at controllers. In this paper, we study the routing problem in such a network with new features including centralized route decision, global network-state awareness, seamless route discovery while considering the optimization of several long-term global performance metrics. We formulate the entire routing problem of a multi-modal UWSN as an optimization problem while considering the interference phenomenon of ad hoc scenarios and some long-term global performance metrics of an ideal routing protocol. Our formulated problem nicely captures all possible flexibilities of a sensor node no matter it has the full-duplex or half-duplex functionality. Upon the formulation, we recognize the NP-hard nature of the problem for all possible scenarios. We adopt a rounding technique based on the convex programming relaxation concept to solve the formulated routing problem that considers full-duplex scenarios, whereas we solve the problem for half-duplex scenarios using a greedy method upon interpreting it as a submodular function maximization problem. Through extensive simulation via our Python-based in-house simulator, we verify that our proposed globally optimal routing scheme always outperforms three existing decentralized routing protocols (each of these protocols are selected from each of three prominent protocol types, i.e., flooding, cross-layer information and adaptive machine learning based, respectively) in terms of reliability, latency, energy efficiency, lifetime and fairness.

中文翻译：

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水下多模通信网络中启用 SDN 的能量感知路由

尽管进行了广泛的研究，水下传感器网络 (UWSN) 仍然由于其低效和不协调的信道访问和资源管理而遭受严重的性能问题。例如，由于缺乏对网络资源的全面了解，现有的分散式路由协议无法提供全局最优性能。另一方面，软件定义网络 (SDN) 作为提供突出集中式解决方案的有前途的范例，可用于解决 UWSN 中的上述问题。事实上，SDN 带来了前所未有的机会，通过在控制器上开发高级算法来提高网络性能。在本文中，我们研究了具有新特性的网络中的路由问题，包括集中式路由决策、全局网络状态感知、无缝路由发现，同时考虑优化几个长期全局性能指标。我们将多模式 UWSN 的整个路由问题表述为一个优化问题，同时考虑了 ad hoc 场景的干扰现象和理想路由协议的一些长期全局性能指标。我们制定的问题很好地捕获了传感器节点的所有可能的灵活性，无论它具有全双工还是半双工功能。在制定时，我们认识到所有可能场景下问题的 NP-hard 性质。我们采用基于凸规划松弛概念的舍入技术来解决考虑全双工场景的公式化路由问题，而我们使用贪婪方法解决半双工场景的问题，将其解释为子模块函数最大化问题。通过我们基于 Python 的内部模拟器的广泛模拟，我们验证了我们提出的全局最优路由方案始终优于三种现有的分散式路由协议（这些协议中的每一种都选自三种主要协议类型中的每一种，即泛洪、交叉层信息和自适应机器学习，分别）在可靠性、延迟、能源效率、寿命和公平性方面。