In emergency situations like the recent Australian bushfires, it is crucial for civilians and firefighters to receive critical information such as available escape routes with guarantees on accuracy, timeliness, reliability, and completeness. Mobile Ad-hoc Networks (MANETs) can provide communications in bushfires but guaranteeing information delivery that meets user needs is not easy with current MANET forwarding solutions. Quality of Information (QoI) based source selection has recently been developed in MANETs for this purpose. The most popular QoI scheme uses the analytic hierarchy process (AHP), an intensive pairwise comparison procedure to score sources using a linear combination of low-level network metrics in a hierarchical two-step process. Current QoI-AHP, by directing traffic to a single high scoring source, often creates additional bottlenecks and does not guarantee the higher-level information needs of users. In this work, we develop a novel low overhead source selection scheme, QoI with Thresholds (QoIT), that is designed to deliver the required target performance thresholds for users. QoIT introduces two modifications to QoI-AHP. Firstly, it replaces the raw network performance value by the ratio of the network metric value to the user’s demand for that performance, a goodness measure of how far the value of the network metric is from meeting the user’s demand. The ratios are fed into QoIT’s process for assigning multi-dimensional scores to each source. Secondly, QoIT uses new source selection criteria to choose the source that best delivers the information that meets the user needs. To evaluate QoIT and QoI-AHP performances in emergency communications, we develop a novel simulation software with realistic models across multiple network layers. Our QoIT algorithm works with any combination of quality thresholds for any subset of network metrics. Simulation results show that QoIT out-performs QoI-AHP by increasing user usability by 57%, ensuring high priority requirements are met, reducing source bottlenecks, and decreasing the source selection time by 62.5%.

在最近的澳大利亚丛林大火等紧急情况下，平民和消防员获得至关重要的信息（例如可用的逃生路线）并保证准确性，及时性，可靠性和完整性至关重要。移动自组织网络（MANET）可以在丛林大火中提供通信，但是要保证满足用户需求的信息传递，使用当前的MANET转发解决方案并不容易。为此，最近在MANET中开发了基于信息质量（QoI）的源选择。最受欢迎的QoI方案使用层次分析两步法（AHP），这是一种密集的成对比较过程，可使用低级网络指标的线性组合对源进行评分。当前的QoI-AHP，通过将流量定向到一个高得分来源，通常会造成其他瓶颈，并且不能保证用户的更高级别的信息需求。在这项工作中，我们开发了一种新颖的低开销源选择方案，即具有阈值的QoI（QoIT），旨在为用户提供所需的目标性能阈值。QoIT对QoI-AHP进行了两项修改。首先，它用网络度量值与用户对该性能的需求之比来代替原始网络性能值，这是衡量网络度量值与满足用户需求相差多少的有效度量。这些比率被输入到QoIT的过程中，以为每个来源分配多维得分。其次，QoIT使用新的来源选择标准来选择最能提供满足用户需求的信息的来源。为了评估紧急通信中的QoIT和QoI-AHP性能，我们开发了一种新颖的仿真软件，该软件具有跨多个网络层的逼真的模型。我们的QoIT算法适用于网络指标的任何子集的质量阈值的任意组合。仿真结果表明，QoIT的性能比QoI-AHP高出57％，可提高用户可用性，确保满足高优先级要求，减少源瓶颈，并将源选择时间减少62.5％。