物联网（IoT）中数据汇集和无线通信的经济分析和定价模型：综述
Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey
摘要：
本文综述了物联网（IoT）中数据汇集和无线通信的经济分析和定价模型。无线传感器网络是物联网的主要组成部分，它从环境中收集数据并将数据传输到汇聚节点。为了延长服务时间和降低维护成本，无线传感器网络需要自适应和鲁棒的设计来解决许多问题，例如，数据汇集、拓扑形成、分组转发、资源和功率优化、覆盖优化、高效任务分配和安全性。对于这些问题，传感器必须根据当前的能力和可用的策略做出最优决策，以实现期望的目标。本文回顾了许多应用的经济和定价模型，被称为智能理性决策方法，开发自适应算法和协议的无线传感器网络。此外，我们调查了各种定价策略，为手机用户提供激励，在人群传感应用程序，以贡献他们的传感数据。此外，我们考虑在机器对机器（M2M）通信中使用一些定价模型。最后，我们强调了一些重要的开放研究问题以及将经济和定价模型应用于物联网的未来研究方向。
英文摘要：
This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless Sensor Networks (WSNs) are the main component of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in Machine-to-Machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.
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。
