论文标题
在线分布式分布式进化优化时间分段多个访问协议
Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols
论文作者
论文摘要
随着廉价,微型电子产品的出现,无处不在的网络已经达到了前所未有的复杂性,规模和异质性,成为了几种现代应用,例如智能行业,智能建筑和智能城市的核心。网络性能的关键要素是协议堆栈,即确定网络交换信息中节点的规则和数据格式集。从系统规格和网络环境中的严格假设开始,已经付出了巨大的努力来设计正式技术来综合(离线)网络协议。但是,由于数值复杂性,或者由于环境可能未知并且规格可能无法使用,因此很难在最现代的网络应用程序中应用离线设计。在这些情况下,在线协议设计和适应有可能提供更可扩展和强大的解决方案。然而,到目前为止,仅在线自动协议设计进行了一些尝试。在这里,我们设想了一个协议作为网络的新兴属性,该协议是由环境驱动的分布式山坡攀爬算法获得的,该算法使用节点 - 局部加固信号在运行时进化,而没有任何中央协调,从scratch中进行了网络协议。我们使用三态时间划分多访问(TDMA)中型访问控制(MAC)协议测试这种方法,并在各种规模和各种设置的网络中观察到它的出现。我们还展示了分布式山坡攀岩如何在能源消耗和协议性能方面达到不同的权衡。
With the advent of cheap, miniaturized electronics, ubiquitous networking has reached an unprecedented level of complexity, scale and heterogeneity, becoming the core of several modern applications such as smart industry, smart buildings and smart cities. A crucial element for network performance is the protocol stack, namely the sets of rules and data formats that determine how the nodes in the network exchange information. A great effort has been put to devise formal techniques to synthesize (offline) network protocols, starting from system specifications and strict assumptions on the network environment. However, offline design can be hard to apply in the most modern network applications, either due to numerical complexity, or to the fact that the environment might be unknown and the specifications might not available. In these cases, online protocol design and adaptation has the potential to offer a much more scalable and robust solution. Nevertheless, so far only a few attempts have been done towards online automatic protocol design. Here, we envision a protocol as an emergent property of a network, obtained by an environment-driven Distributed Hill Climbing algorithm that uses node-local reinforcement signals to evolve, at runtime and without any central coordination, a network protocol from scratch. We test this approach with a 3-state Time Division Multiple Access (TDMA) Medium Access Control (MAC) protocol and we observe its emergence in networks of various scales and with various settings. We also show how Distributed Hill Climbing can reach different trade-offs in terms of energy consumption and protocol performance.