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Big data represents one of the most profound and most pervasive evolutions in the digital world (Arena, F., & Pau, G. 2020). Examples of big data come from Internet of Things (IoT) devices, as well as smart cars, but also the use of social networks, industries, and so on. The sources of data are numerous and continuously increasing, and, therefore, what characterizes big data is not only the volume but also the complexity due to the heterogeneity of information that can be obtained. The fastest growth in spending on big data technologies is happening within banking, healthcare, insurance, securities and investment services, and telecommunications. In fact, the definition of big data analysis refers to the process that encompasses the gathering and analysis of big data to obtain useful information for the business.
In recent years, wireless multimedia sensors have developed rapidly, their functions are becoming more and more powerful, and their costs are declining. The development of battery technology has increased the lifespan of these devices and also promoted the development of these devices (Sarisaray-Boluk P & Akkaya K, 2015). A solution is introduced based on fuzzy logic aimed at optimizing the energy management of electric bikes (Giliberto, M., Arena, F., & Pau, G. 2019). The design of three-port converters (TPCs) is presented for smooth transitions (i.e., fast settling time, and no obvious overshoot/undershoot) of 7 distinctive operating modes, depending on sources and loads scheduling (Aljarajreh, H.,et al. 2021). A systematic extension of second-order compensated inductive power transfer (IPT) converters is presented (Liu, Y. C., et al. 2021), it is designed for achieving load-independent current (LIC) or load-independent voltage (LIV) output. The rapid development of wireless multimedia sensors has made them widely used in many fields, and the threshold for using these sensors has become lower and lower. Using sensors, cloud servers and clients provided by sensor manufacturers can quickly create a monitoring system.
The widespread use of wireless sensors has brought a lot of multimedia data, such as video sensor data. This type of multimedia data is generally real-time and continuous. Therefore, it is very important to maintain the efficiency and stability of data transmission. In the process of multimedia data transmission, the loss of some data may affect the availability of other data. Due to bandwidth limitations and network stability, the sensor may not be able to obtain a stable connection link when communicating with the server. The instability of the wireless link itself will cause the sensor node to temporarily fail to access the server. A problem with a network node in the link will cause a link to be unavailable. As a result, the connection is abnormally disconnected, the delay increases and the user experience decreases.
Some researchers have conducted research on the reliability of wireless sensors and the reliability of data transmission on wireless sensors, and have obtained some results. The routing protocol optimization in the wireless multimedia sensor network (WMSN) is a method that can control the data flow (Nguyen X T, et al., 2015). This method is very effective in WMSN, but it is not designed for portable smart devices, and it cannot avoid network abnormalities caused by network status. One way to enhance transmission stability in wireless sensor networks is to restore the connection as soon as possible when the connection is disconnected (Joshi Y K & Younis M, 2014). However, this method will still cause data loss and congestion. Another method is to use multiple connections to reduce delay and enhance the stability of data transmission (Kim D & Chung K, 2014). This method does not solve the problem of disconnection during data transmission. Finding the shortest path between the sensor and the server to reduce latency is also a way to enhance stability. In distributed and independent sensors, this method is effective, but when the network condition is not good, the delay will still occur, and this method mainly focuses on improving energy utilization (Chaudhary D D & Waghmare L M, 2013). Multi-homed (multi-homed) is also an available mode to improve data transfer. Multi-homing means that a device has multiple addresses for other devices to access, thereby enhancing the stability of data transmission (Sousa B M, et al., 2011; Wallace T D & Shami A,2012; Capela N & Sargento S, 2014; Kuntz R, et al., 2013). However, it is unrealistic for each device to hold multiple addresses, and it is also very difficult for all devices to support multi-homed protocols.