保证信息质量的绿色物联网能耗管理技术研究

Considering physical sensors with certain sensing capabilities in an Internet-of-Things (IoT) sensory environment, in this research, we aim to investigate an efficient energy management framework to control the duty cycles of these sensors under the quality-of-information (QoI) expectations in a multi-task-oriented IoT sensory environment. Contrary to all past research efforts, the design goal of our proposal is to be transparent and compatible both with the underlying low-layer communications/networking protocols and up-running diverse applications (potentially) in multiple IoT domains, and more importantly preserving energy-efficiency in the long run without sacrificing the QoI levels attained. Specifically, in this research we aim to investigate a novel concept of QoI-aware "sensor-to-task relevancy" to explicitly consider the sensing capabilities offered by a sensor to the IoT sensory environments, and QoI requirements required by a task. Second, we aim to propose a novel concept of the "critical service set" of any given task in selecting the sensors to service a task over time. Third, energy management decision is to be investigated that makes control decisions dynamically at runtime, to reach the optimum for long-term application arrivals and departures under the constraint of their service delay.We further plan to investigate the signal transmission and processing latency of a given IoT sensory environment into the proposal, and provide a thorough analysis on its impact on average measured delay probability. As to demonstrate the effectiveness of our system, we shall first perform a complete set of performance analysis by computer simulations to understand the impact of different system parameters. Then, we plan to perform a case study by implementing the proposed algorithms and system in a Smart Campus environment at Beijing Institute of Technology that utilizes a variety of sensors to offer different IoT services to students and staffs.

本研究旨在提出一种在多任务绿色物联网环境中的高效能耗管理平台和算法，优化传感设备工作状态、保证物联网应用和服务的多元信息质量。与以往相关研究不同的是，本研究将关注物联网中间件层算法，兼容异构网络通信协议和多种上层应用。研究将从理论层面描述传感设备所提供的感知能力与感知任务的多元信息质量需求之间的关联关系，提出保障信息质量的"传感设备-感知任务"关联度概念和模型。研究将提出物联网"关键服务集"的概念，用以选择服务于特定感知任务的传感设备集合。基于以上理论建模，研究将设计绿色物联网能耗管理平台及核心算法，实时优化传感设备的工作状态，最大化全网能量资源利用率，进而通过理论建模分析由于能耗控制信号传输和处理延迟对该绿色物联网系统的影响。为了验证所提出理论和算法的有效性，本研究将不仅通过完整的计算机仿真实验评估系统理论性能，并且通过智慧校园试点部署验证提出的绿色物联网能耗管理平台和算法。

本研究旨在提出一种在多任务绿色物联网环境中的高效能耗管理平台和算法，优化传感设备工作状态、保证物联网应用和服务的多元信息质量。与以往相关研究不同的是，本研究将关注物联网中间件层算法，兼容异构网络通信协议和多种上层应用。研究从理论层面提出了传感设备所提供的感知能力与感知任务的多元信息质量需求之间的关联关系，提出了保障信息质量的“传感设备-感知任务”关联度概念和模型，设计了绿色物联网能耗管理平台及核心算法，实时优化传感设备的工作状态，最大化全网能量资源利用率，进而通过理论建模分析由于能耗控制信号传输和处理延迟对该绿色物联网系统的影响。依托项目编写学术书籍4本，发表学术论文10篇，其中SCI检索9篇，其中IEEE/ACM Transactions系列论文6篇，申报国家发明专利1项、授权发明专利7项，培养博士生3名，硕士生5名。研发了“轻工产品大数据挖掘与全生命周期追溯系统”，获得中国物流与采购联合会科技进步一等奖（第三完成人）、中国轻工业联合会科技进步三等奖（第一完成人）、项目负责人也因此入选国家“十二五”轻工业创新先进个人。