战术无线网络中智能应用的持久性

Ta Chen, V. Kaul, F. Sultan, K. Parmeswaran, S. Samtani, D. Shur, T. Kiernan, S. Thomas, W. Zimmerman
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引用次数: 8

摘要

移动战术manet受到间歇性连接和重大数据包丢失的瞬态事件的影响。由于这种中断,已经提出了具有中断和延迟容忍的协议和技术。一类这样的系统通过在网络中存储消息/数据包来工作。如果与邻居的连通性丢失,则可能在恢复与邻居的连通性时下发丢失的消息。这种容忍延迟网络(DTN)技术旨在可靠地传递源指向接收节点的所有数据。我们认为,在某些情况下,在中断事件期间,坚持并交付所有丢失的数据包几乎没有什么用处,甚至可能适得其反。例如,在态势感知应用中,重新传输丢失的GPS跟踪数秒或数分钟是不合适的。相反,最好是所有被跟踪实体当前位置的快照。类似地,在多媒体流或VOIP呼叫中,只需要重播丢失的关键信息。所有丢失的数据包的完全重传不仅在重传过程中引入延迟,而且在重传过程中消耗的带宽也被浪费了。注意,每个应用程序可能有不同的语义。因此,为了从临时断开中恢复,确定为给定应用程序交付哪些数据是合适的,需要了解应用程序语义。在之前的工作中,我们提出了异构智能过滤(HIF),这是一种智能过滤和转换数据以匹配网络容量和最终用户能力的技术。在HIF中,最终用户不需要的无关信息由HIF代理过滤。在这项工作中,我们展示了如何将HIF概念扩展到中断期间保存的数据和信息。存储以供以后重新传输到先前断开连接的接收器的信息可以由丢失数据的应用程序状态快照、摘要或转录本组成,或者仅仅是在给定时间点被判断为与用户相关的媒体流的那些部分。我们描述了我们在实时多媒体和战术态势感知应用的应用感知持久性方面的工作。在前面的工作中报告的HIF系统的中间件基础设施被扩展为支持应用程序感知的持久性。我们分析了战术态势感知场景下应用程序持久化的性能优势。当终端设备的处理能力和呈现数据的能力受到限制时,应用程序持久化特别有用,因为它减少了对客户机应用程序的需求。因此,我们还说明了应用程序感知持久性中间件在支持手持Android设备上实现的多媒体和态势感知应用程序方面的有用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent application persistence in tactical wireless networks
Mobile tactical MANETs are subject to periods of intermittent connectivity and transient events of significant packet loss. Because of such disruptions, protocols and technologies have been proposed that are disruption and delay tolerant. One class of such systems works by storing messages/packets in the network. If connectivity to neighbors is lost, missing messages may be delivered when connectivity to neighbors is restored. This delay tolerant networking (DTN) technology aims to reliably deliver all the data that a source directs towards a receiver node. We suggest that in some cases it is of little utility and may even be counter-productive to persist and deliver all packets lost during a disruption episode. For example, in situational awareness applications, retransmitting many seconds or minutes of lost GPS tracks is not appropriate. Instead a snapshot of the current position of all tracked entities is preferable. Similarly in a multimedia stream or VOIP call, just the key missing information should be replayed. Not only does full retransmission of all missing packets introduce delays during retransmission, but also the bandwidth consumed during retransmission is wasted. Note that each application may have different semantics. Therefore determining what data is appropriate to deliver for a given application in order to recover from a temporary disconnection requires knowledge of the application semantics. In previous work, we proposed Heterogeneous Intelligent Filtering (HIF), a technology that intelligently filters and transforms data to match network capacity and end-user capability. In HIF, extraneous information not needed by the end-user is filtered by HIF agents. In this work2, we show how the HIF concept can be extended to the data and information persisted during disruptions. The information stored for later retransmission to previously disconnected receivers may consist of application state snapshots, summaries or transcripts of the missing data, or just those portions of a media stream judged to be relevant to the user at a given point in time. We describe our work on application aware persistence for real-time multimedia and tactical situational awareness applications. The middleware infrastructure of the HIF systems reported on in previous work is extended to support application aware persistence. We analyze the performance benefit of application persistence on a tactical situational awareness scenario. Application persistence is particularly useful when the end-device may be limited in its processing power and ability to render data, since it reduces the demands on the client application. Accordingly, we also illustrate the usefulness of our application aware persistence middleware in supporting multimedia and situational awareness applications implemented on handheld Android devices.
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