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.
|Effective start/end date||1/08/18 → 30/09/19|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):