To address limitations of cross-chain openness， security issues， network congestion， and increased transaction costs in the circulation mechanism of existing Non-Fungible Token （NFT）， an open semantic-rich Non-Fungible Data Element （NFDE） chain-network integration architecture named IEN NFDE （Intelligent Eco Networking Non-Fungible Data Element） was designed. Firstly， a transmission protocol for the overlay network was designed， encompassing naming rules， data structure and encoding rules of packets， as well as a data forwarding and verification mechanism based on named addressing. Then， the semantic-rich NFDE was defined by encapsulating metadata and digital assets themselves into an independent digital entity with semantic attributes， enabling free circulation of on-chain and off-chain data， and decoupling the binding limitations between blockchain systems and data elements， and improving the flexibility of data element circulation. Finally， a prototype system of the IEN NFDE architecture was designed and implemented， and its performance was tested. Experimental results showed that when the data transmission frequency exceeds 600 times， compared to the NFT trading platforms based on Transmission Control Protocol/Internet Protocol （TCP/IP） architecture， the prototype system of IEN NFDE architecture reduced the average data transmission delay by at least 46.34%， the total data transmission delay by at least 52.43%， the network communication overhead by at least 36.98%， and increased the throughput by at least 135.71%. These metrics indicate that the prototype system of the IEN NFDE architecture significantly improves the efficiency of cross-chain data circulation while markedly reducing the consumption of network resource. The IEN NFDE architecture not only provides a new efficient solution for the efficient circulation of NFDE， but also effectively alleviates network congestion， reduces transaction costs in practical applications， and offers technical support for the healthy development of NFT market.

Aiming at the problem that traditional localization algorithm has a slow convergence speed, combining with the characteristics of perfect immunity to time in UWB (Ultra Wide-Band) communication, a novel Davidon-Fletcher-Powell (DFP) algorithm based on Armijo step size was proposed to locate the target node on TDOA (Time Difference Of Arrival) location model. Taylor series expansion algorithm was further introduced to acquire final location at the initial position, achieving the precise location of UWB communication system. The experimental results show that the proposed algorithm not only decreases the demand of localization optimization algorithm to initial position, but also improves the average localization precision 7 times than the steepest decent method with precise measure time. The proposed localization algorithm has better performance on localization accuracy and efficiency.