| 摘要: | 本計畫為兩年期之規劃，主要目的在探討物聯網服務中包括無線存取效率、及資料安全管理兩大議題，並透過區塊鏈與機器學習技術，實作出物聯網資料管理與交易控制平台。計畫內容的研究部份包括，IEEE 802.11ah無線網路的存取控制、與資源管理，及區塊鏈網絡的最小跳躍(hop)數連線演算法設計；在實作部份包括，IoT私有區塊鏈實作、智能合約，及整合機器學習與802.11ah擬真模組，完成具學習能力區塊鏈IoT服務生態實驗平台。實作完成之平台，能提供物聯網服務資料提供者、資料彙整加值者、服務提供者、及使用者高效率的互動環境。兩年之主要計畫內容略述如下：第一年度：主要探討IEEE 802.11ah網路，在提供大量物聯網元件上傳週期性與緊急資料時，無線網路資源的有效存取及排程。演算法之設計，將依網路負荷狀況，以彈性方式調整802.11的TIM間隔，及RAW slot長度，以提升上鏈資料之效率。在IoT區塊鏈實作方面，將以Ethereum先進行區塊鏈架設，將物聯網元件加入成為鏈上的參與者，依據服務流程設計鏈上之資料合約、帳戶合約、及資料分散管理等模型，架構設計上，將把控制與資料流分離，以提供物聯網資料管理之安全性，及服務提供模式之彈性。第二年度：本計畫將研究當新節點加入區塊鏈網絡時，如何讓整體網絡之跳躍數為最少，以提升當鏈上有交易(控制)啟動時，可以減少網路的傳送負擔。我們將設計包括限制新加入節點連線數，及要求整體網路最大連線數的兩種演算法。在實作部份，將以第一年度完成之IoT區塊鏈為基礎，擴充包括實體與虛擬的連網元件數量、加入802.11ah擬真模組，並加強智能合約與機器學習功能，完成具學習功能之區塊鏈IoT服務生態實驗平台，並透過範例在實驗平台上驗證物聯網服務生態鏈之運作。 ;This is a two-year proposal. The main focus of this proposal is to study the technical issues for the deployment of internet of things (IoT) service. The study issues can be divided into two topics: one is the effective radio access, and the other is the secure data management of IoT devices. Additionally, we will implement the data management and contract control platform for IoT services by using blockchain and machine learning technologies. The research part of this proposal include the radio access and resource allocation in IEEE 802.11ah network, and the algorithms to minimize the maximum hop count in blockchain network. In the implementation part, we will implement the learning based IoT service ecology experimental platform by using 802.11ah emulation module, the intelligent contract of blockchain, and machine learning technologies. The implemented platform provides highly efficient interactions environment among information provider, information aggregator, service provider, and end users. The main research contents of each year are provided as follows:In the first year, we will study the uplink radio access and resource allocation schemes of IEEE 802.11ah wireless network for massive IoT devices. The algorithm design will flexibly adjust the TIM interval and the length of RAW slots to improve the performance of uplink traffic transmission. For the implement of IoT blockchain platform, we will implement the private blackchain for IoT devices by using Ethereum and will establish models of data, account, and distributed management for the IoT blockchain..We will separate the data and control layers in architecture design for more security of data and more flexible of service models.In the second year, the issue of minimizing the maximum hop count of blockchain network will be investigated. Two algorithms, including limited connection number of new-join node, and limited maximum hop count of the blockchain, will be proposed and analyzed. For the experimental system implementation, more IoT devices (including physical nodes and virtual nodes) and 802.11ah emulation module will be included, and the learning based IoT service ecology experimental platform will be completed by enhancing the smart contract and machine learning technologies. We will also verify the operation of IoT service ecology in the platform through the experimental example. |
