The emergence of wireless body area network (WBAN) technology has brought hope and dawn to solve the problems of population aging, various chronic diseases, and medical facility shortage. The increasing demand for real-time applications in such networks, stimulates many research activities. Designing such a scheme of critical events while preserving the energy efficiency is a challenging task, due to the dynamic of the network topology, severe constraints on the power supply, and the limited computation power. The design of routing protocols becomes an essential part of WBANs and plays an important role in the communication stacks and has a significant impact on the network performance. In this paper, we briefly introduce WBAN and focus on the analysis of the routing protocol, classify, and compare the advantages and disadvantages of various routing protocols. Lastly, we put forward some problems and suggestions, which provides ideas for the follow-up routing design.
Smart cities can effectively improve the quality of urban life. Intelligent Transportation System (ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow plays an important role in ITSs. To improve the prediction accuracy, we propose a novel traffic flow prediction method, called AutoEncoder Long Short-Term Memory (AE-LSTM) prediction method. In our method, the AutoEncoder is used to obtain the internal relationship of traffic flow by extracting the characteristics of upstream and downstream traffic flow data. Moreover, the Long Short-Term Memory (LSTM) network utilizes the acquired characteristic data and the historical data to predict complex linear traffic flow data. The experimental results show that the AE-LSTM method had higher prediction accuracy. Specifically, the Mean Relative Error (MRE) of the AE-LSTM was reduced by 0.01 compared with the previous prediction methods. In addition, AE-LSTM method also had good stability. For different stations and different dates, the prediction error and fluctuation of the AE-LSTM method was small. Furthermore, the average MRE of AE-LSTM prediction results was 0.06 for six different days.
The precision of the conventional user identification algorithm is not satisfactory because it ignores the role of user-generated data in identity matching. In this paper, we propose a frequent pattern mining-based cross-social network user identification algorithm that analyzes user-generated data in a personalized manner. We adopt the posterior probability-based information entropy weight allocation method that improves the precision rate and recall rate compared to the empirical weight allocation method. The extensive simulations are provided to demonstrate that the proposed algorithm can enhance the precision rate, recall rate, as well as the F-Measure (F1).INDEX TERMS User identification, frequent pattern, cross-social network, information entropy.
A novel, non‐coherent bit‐level detection scheme is proposed to compensate for the frequency offset efficiently in IEEE 802.15.4 binary phase shift keying (BPSK) receivers. In the proposed scheme, the frequency‐offset estimation process only requires comparison, division, and addition operations. The proposed scheme first creates a suitable estimation‐region division, thus the mathematical approximation tan−1(x) ≈ x is efficiently utilised to simplify the conventional optimal estimation. The frequency offset and signal‐to‐noise ratio conditions do not need a priori knowledge. Simulations demonstrate that the proposed scheme is as reliable as the conventional optimal algorithm, but with a significant reduction of complexity.
With the development of Unmanned Air Vehicle (UAV) communication, Flying Ad Hoc Network (FANET) has become a hot research area in recent years, which is widely used in civil and military fields due to its unique advantages. FANET is a special kind of networks which are composed of UAV nodes, and can be used to implement data transfer in certain unique scenarios. To achieve reliable and robust communication among UAVs, a routing algorithm is the key factor and should be designed elaborately. Because of its importance and usefulness, this topic has attracted many researchers, and various routing protocols have also been put forward to improve the quality of data transmission in FANETs. Thus, in this paper, we give a survey on the state-of-the-art of routing protocols proposed in recent years. First, an in-depth research of the routing in FANETs recently has been brought out by absolutely differentiating them based on their routing mechanism. Then, we give a comparative analysis of each protocol based on their characteristics and service quality indicators. Finally, we propose some unsolved problems and future research directions for FANET routing.
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