Biology Inspired Autonomic Networking Protocols: Analysis and Implementation

信息技术的进步导致了新的环境的出现，如移动自组网、无线传感器和参与者网络、大规模网格和对等网络，本质上是由联网的自治节点组成的。尽管这些环境为促进新的应用程序和服务提供了巨大的潜力，但它们也带来了困难的设计挑战--这些环境本质上是动态的、不可靠的和大规模的。传统的设计方法假设系统由可靠的组件组成，和/或系统规模相对较小，在这样的环境中不适用。此外，基于对系统整体的集中和/或显式控制的方法要么引入单点故障，要么使系统不能适应，这在这种环境中也不适用。因此，探索不受这些缺陷影响的新的设计范式和方法是至关重要的。自组织现象在自然界中普遍存在，生物有机体通过自组织大量不可靠的动态变化的组件来发展不同的功能。此外，这些生物有机体具有对单个组件失效的稳健性、对不断变化的条件的适应性以及缺乏明确的中央协调的理想特性。这项研究从对自然界中的群体行为(如黏菌)的研究中寻找灵感，以设计和分析适用于上述环境的健壮、自主的网络协议。该项目旨在开发基于简单交互单元的自下而上建模的自主网络协议。这种方法的优点是可以将复杂系统的维度降低为一小部分控制组成系统的简单单元的原始函数和参数。特别是，研究人员试图对粘液霉菌疟原泡菌的行为进行建模，以设计用于无线传感器和作用器网络的自主网络协议。

Advances in information technology have resulted in the emergence of new environments, such as mobile ad hoc networks, wireless sensor and actor networks, large-scale Grid and peer-to-peer networks, which inessence are constituted by networked autonomous nodes. Although these environments present enormous potential to facilitate new applications and services, they also pose difficult design challenges--these environments are intrinsically dynamic, unreliable, and large scale. Traditional design approaches that assume that the system is composed of reliable components, and/or that the system is of relatively small scale are not applicable in such environments. In addition, approaches that are based on central and/orexplicit control over the system as a whole either introduce a single point of failure or make the system not adaptable, which are not applicable in such environments either. It is therefore critical to explore new design paradigms and approaches that do not suffer from these defects.The phenomenon of self-organization is pervasive in nature, where biological organisms self-organize a large number of unreliable and dynamically changing components to develop diverse functions. In addition,these biological organisms possess the desirable properties of robustness to failure of individual components, adaptivity to changing conditions, and lack of explicit central coordination. This research seeks inspiration from the study of swarm behavior in nature, such as slime mold, to design and analyze robust, autonomic networking protocols for the aforementioned environments. This project aims to develop autonomic networking protocols based upon bottom-up modeling of simple, interacting units. The advantage to this approach is that one can reduce the dimensionality of the complex system to a small set of primitivefunctions and parameters governing the simple units that comprise the system. In particular, the investigators seek to model the behavior of slime mold physarum plasmodium to design autonomic networking protocols for wireless sensor and actor networks.