物聯網資訊採集與群組多播的機制設計

Mechanism Design for IoT Information Gathering and Multicast Distribution

柯君翰(Chun-Han Ko)

指導教授 ： 魏宏宇

國立臺灣大學/電機資訊學院/電信工程學研究所/博士(2017年)

https://doi.org/10.6342/NTU201701588

摘要

物聯網是智能設備、車輛、機器還有其他智能物體等互相聯通而形成的網路。實現複雜物聯網的關鍵因素則在於許多新型通信協定和技術的整合，它們將使物聯網設備能夠進行協作、溝通並作出決策。物聯網設備的互相聯通作用可以簡單的資料流說明：諸如無線感應器的物聯網設備從環境中收集資料，並將資料傳輸到資料伺服器進行信息處理。爾後伺服器會將處理獲得的信息傳輸分送到諸如用戶設備的物聯網設備以實現更好的使用者效用。由於物聯網的快速發展，無處不在的信息收集、處理和分送，均使無線電資源的需求不斷上升，這也使原本就有限的無線電資源更為稀少。此外，無線傳輸通道會隨著時間波動。而能量採集技術雖能實現自我維持運作的物聯網設備，但採集的能量通常是間歇並隨時間變化的。因此，考量到無線電資源的稀少性、無線通道的時間波動和能量的時間變化，如何有效地在空間和時間上分配運用無線電資源將是物聯網中極為重要的一項議題。此外，我們也考慮了物聯網設備的自私特性與物聯網環境的不完整信息。不完整信息意味著網路環境中如無線通道狀況與設備的能量儲存量等信息通常僅為設備本身所知。為了最佳化網路效能，網路設計者將需要設備回饋這些不完整信息。由於整體網路最佳化通常會犧牲部分設備的個別效能，因此自私的設備可能會通過虛假的信息回饋來操縱網路最佳化結果，以使自己的效能表現變得更好。此時整體網路效能表現將可能不是網路設計者所希望達到的最佳結果。有鑑於此，我們在物聯網中制定了無線電資源分配問題，並以機制設計的概念提出了創新的物聯網資源分配機制。透過理論研究，我們證明設計的資源配置機制將可使物聯網設備回饋真實的信息，並從而實現最佳的均衡資源分配。均衡資源分配實現了數個效率和公平的度量，包括最大系統吞吐量/環境資料保真度，柏拉圖效率，最大公平性，與比例公平性。而透過提出的定價方案，我們證明均由設備付錢給機制。換言之，我們設計的機制將不需要付錢給設備才能確保真實的反饋（預算平衡）。此外，我們也證明所有設備將加入設計的機制以獲得比沒有加入時更高的效用（個別理性）。

關鍵字

物聯網 ； 能量採集 ； 無線電資源分配 ； 機制設計 ； 賽局理論

並列摘要

The Internet of Things (IoT) is the inter-networking of smart devices, vehicles, machines, and other items. The key factor for enabling this sophisticated paradigm is the integration of novel communication protocols and technologies, which allows IoT devices to cooperate, communicate, and make decisions. The interconnection of IoT devices can be explained in simple data flows: Devices such as wireless sensors gather data from the environment and transmit the data to data servers for information processing. The processed information is then distributed to devices such as user equipments to achieve greater user utility. Due to the rapid development of the IoT, ubiquitous information gathering, processing, and distribution have escalated the demand of radio resources, which makes radio resources even scarcer. In addition, wireless channels are time-fluctuating. Energy harvesting technology enables self-sustainable IoT devices but harvested energy is usually intermittent and time-varying. Therefore, taking into account radio resource scarcity, channel fluctuations, and energy variations, efficient radio resource allocation in space and time is particularly important in the IoT. Moreover, we also consider selfishness of IoT devices and incomplete information of the network environment. Incomplete information means that the network environment, such as channel conditions and energy levels, is only known to devices themselves. To optimize the network performance, feedback of the incomplete information from devices is required. Note that overall network optimization usually sacrifices individual performance of some devices. Selfish devices can manipulate the network optimization result through untruthful feedback if doing so increase their own performance. The network performance may not be optimal. In this regard, we formulate radio resource allocation problems in the IoT and adopt a mechanism design approach to propose novel IoT resource allocation mechanisms. Our theoretic findings show that the proposed resource allocation mechanisms can induce truthful information feedback from devices so as to achieve optimal equilibrium resource allocation. The equilibrium resource allocation achieves several efficiency and fairness metrics, including maximum system throughput/data fidelity, Pareto efficiency, max-min fairness, proportional fairness. With the proposed pricing schemes, the payment is always made from the devices to the mechanisms. In other words, the mechanisms do not need to pay to ensure truthful feedback (budget balance). Moreover, all devices will join the proposed mechanisms to gain higher utility than without joining (individual rationality).

並列關鍵字

The IoT ； energy harvesting ； radio resource allocation ； mechanism design ； game theory

參考文獻

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