DCA-CT-UFRN, Campus Universitário, Lagoa Nova, Universidade Federal do Rio Grande do Norte, 59072-970 Natal RN, Brazil.
Sensors (Basel). 2011;11(5):5439-68. doi: 10.3390/s110505439. Epub 2011 May 18.
Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks.
由配备低分辨率摄像头的电池供电电子设备组成的视觉传感器网络 (VSN) 扩展了一系列监测应用的适用性。这些类型的传感器通过自组织易错的无线链路相互连接，对可用带宽、端到端延迟和数据包错误率施加了严格的限制。在这种情况下，多媒体编码需要进行数据压缩和容错处理，还需要确保在通往接收器的路径上节约能源，并提高接收媒体的端到端感知质量。跨层优化可以提高 VSN 应用的预期效率，打破协议层的传统信息流。当多媒体编码技术的内在特性被跨层协议和架构利用时，视觉传感器网络的效率可能会提高。本文调查了基于多媒体的跨层优化的最新研究，提出了用于传输速率调整、拥塞控制、多径选择、节能和错误恢复的建议策略和机制。我们注意到，近年来已经提出了许多基于多媒体的跨层优化解决方案，每一种解决方案都为视觉传感器网络带来了丰富的贡献。
