Collaborative Research: NeTS-NBD: Construction of Robust and Efficient Disruption Tolerant Networks

传统网络，无论是有线网络还是无线网络，都具有节点之间端到端路径相对稳定的特性。然而，并非所有需要通信的环境都允许创建稳定的端到端路径。例如，严重地震灾害的后果将包括倒塌的建筑物，被困在废墟中的人员，损坏的公用设施和道路，以及火灾和二次爆炸。在这种情况下，通信能力，即使在低速率，是极其宝贵的共享重要信息，如幸存者的人数和位置和救援人员的活动。为了在这些具有挑战性的环境中提供通信，必须明确地设计网络协议，使其能够在网络组件（即链路和节点）的可用性和性能频繁中断的情况下执行。由此产生的系统被称为中断容忍网络（DTNs）。这项工作的重点是构建远远超出寻找单播路径任务的ddn。相反，这些ddn在不确定性和攻击下具有鲁棒性，并且在节点和链路资源的利用方面效率很高。具体而言，本项目侧重于以下基本功能：群通信，单跳传输和电源管理。这项工作的基础是在合作大学的试验台进行实验。该项目提供了算法、协议和平台，以创建在最关键的环境中实现通信的健壮和高效的ddn，并暴露了可能在较少挑战的网络中具有更广泛适用性的成本-性能权衡。

Traditional networks, both wired and wireless, have the property that end-to-end paths between nodes are relatively stable. However, not all environments that require communication will allow the creation of stable end-to-end paths. For example, the aftermath of a severe earthquake disaster will include collapsed buildings, persons trapped in debris, damaged utilities and roads, as well as fires and secondary explosions. Under this situation, the ability to communicate, even at low rates, is extremely valuable for sharing vital information, such as the number and location of survivors and the activities of rescue workers. To provide communication in these challenged environments, the network protocols must be explicitly designed to perform despite frequent disruptions in the availability and performance of network components (i.e., links and nodes). The resulting systems are termed Disruption Tolerant Networks (DTNs).This work focuses on the construction of DTNs that go far beyond the task of finding unicast paths. Instead, these DTNs are robust under uncertainty and attack, and are highly efficient in their use of the node and link resources. Specifically, this project focuses on the following fundamental functions: group communication, single-hop transfers, and power management. The work is grounded by experimentation in testbeds at the collaborating universities. The project provides algorithms, protocols, and platforms to create robust and efficient DTNs enabling communication in the most critical of environments, as well as exposes cost-performance tradeoffs that might have broader applicability in less challenged networks.