传感器网络中的能量感知交互通信
Energy Conscious Interactive Communication for Sensor Networks
摘要：
在这项工作中，我们关注的是最大限度地提高寿命的一个集群的传感器从事单跳通信与基站。在数据收集网络中，传感器数据的时空相关性导致数据冗余。此外，通信双方之间的交互作用是公知的，以降低通信复杂性。本文提出了一种形式主义，利用这两个机会，以减少在一个集群中的传感器节点发送的比特数，从而提高其寿命。我们认为，我们的方法有几个固有的优势，在场景中的传感器节点是尖锐的能源和计算能力的限制，但基站不是这样。这为我们提供了一个开发通信协议的机会，其中大部分计算和通信都是由基站完成的。所提出的框架铸造的传感器节点和基站的通信问题的问题，多个线人与相关的信息与收件人进行通信，并试图扩展现有的工作之间的交互式通信的线人-收件人对这样的场景。我们的工作作出了四个主要贡献。首先，我们明确地表明，在这种情况下，互动可以帮助降低通信复杂性。第二，我们发现信息提供者与接受者的沟通顺序决定了通信复杂性。第三，我们提供的框架来计算在这种情况下的$m$ -消息通信复杂性。最后，我们证明了在一个典型的传感器网络的情况下，所提出的形式主义显着降低了通信和计算复杂性。
英文摘要：
In this work, we are concerned with maximizing the lifetime of a cluster of sensors engaged in single-hop communication with a base-station. In a data-gathering network, the spatio-temporal correlation in sensor data induces data-redundancy. Also, the interaction between two communicating parties is well-known to reduce the communication complexity. This paper proposes a formalism that exploits these two opportunities to reduce the number of bits transmitted by a sensor node in a cluster, hence enhancing its lifetime. We argue that our approach has several inherent advantages in scenarios where the sensor nodes are acutely energy and computing-power constrained, but the base-station is not so. This provides us an opportunity to develop communication protocols, where most of the computing and communication is done by the base-station. The proposed framework casts the sensor nodes and base-station communication problem as the problem of multiple informants with correlated information communicating with a recipient and attempts to extend extant work on interactive communication between an informant-recipient pair to such scenarios. Our work makes four major contributions. Firstly, we explicitly show that in such scenarios interaction can help in reducing the communication complexity. Secondly, we show that the order in which the informants communicate with the recipient may determine the communication complexity. Thirdly, we provide the framework to compute the $m$-message communication complexity in such scenarios. Lastly, we prove that in a typical sensor network scenario, the proposed formalism significantly reduces the communication and computational complexities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
