The ever-increasing popularity of recommendation systems allows users to find appropriate services without excessive effort. However, due to the unstable and complex network environment, the historical behavior data of users are quite sparse in most cases. The inherent drawbacks render preference prediction infeasible for cold-start users and have become a crucial issue to be resolved in recommendation systems. To deal with the problems, we first present a Trust-based Collaborative Filtering (TbCF) algorithm to perform basic rating prediction in a manner consistent with the existing CF methods. Then, we propose the Hybrid Collaborative Filtering Recommendation approach with User-Item-Trust Records ( $\text {UIT}_{\text {hybrid}}$ ), a novel approach that incorporates user trust into the existing CF-based methods in a harmonious way to supplement rating information. $\text {UIT}_{\text {hybrid}}$ employs multiple perspectives to extract proper services and achieves a good tradeoff between the robustness, accuracy, and diversity of the recommendation. We conduct extensive real-world experiments on the Epinions data set to demonstrate the feasibility and efficiency of $\text {UIT}_{\text {hybrid}}$ .

This article presents a hybrid wireless network integration scheme in cloud services-based enterprise information systems (EISs). With the emerging hybrid wireless networks and cloud computing technologies, it is necessary to develop a scheme that can seamlessly integrate these new technologies into existing EISs. By combining the hybrid wireless networks and computing in EIS, a new framework is proposed, which includes frontend layer, middle layer and backend layers connected to IP EISs. Based on a collaborative architecture, cloud services management framework and process diagram are presented. As a key feature, the proposed approach integrates access control functionalities within the hybrid framework that provide users with filtered views on available cloud services based on cloud service access requirements and user security credentials. In future work, we will implement the proposed framework over SwanMesh platform by integrating the UPnP standard into an enterprise information system.

The emerging blockchain technology shows promising potential to enhance industrial systems and the Internet of things (IoT) by providing applications with redundancy, immutable storage, and encryption. In the past few years, many more applications in industrial IoT (IIoT) have emerged and the blockchain technologies have attracted huge amounts of attention from both industrial and academic researchers. In this paper, we address the integration of blockchain and IIoT from the industrial prospective. A blockchain-enabled IIoT framework is introduced and involved fundamental techniques are presented. Moreover, the main applications and key challenges are addressed. A comprehensive analysis for the most recent research trends and open issues is provided associated with the blockchain-enabled IIoT.