![]() ![]() The delay in data transmission is the expected delay in communication between devices and is mainly attributable to communication protocols. Transmitting and storing data reliably and quickly is critical. In most cases, nodes work based on a duty cycle, i.e., nodes periodically shift between the active and sleep modes to save energy. Therefore, network nodes should sleep when possible to save energy. The first three states consume the most energy. Under normal circumstances, node energy consumption is divided into four states as follows: (a) sending data (b) receiving data (c) idle listening and (d) sleeping. Generally, most sensing devices are powered by batteries, which provide very limited energy, creating a need for high energy efficiency. The two most important aspects of communication it influences are as follows. Communication performance is also affected by other communication constraints such as bandwidth and communication noise. It influences every aspect of communication performance. The MAC protocol is an important protocol of D2D communication. Device-to-device (D2D) communication has attracted considerable research interest as a basic mode of network computing. Communication between sensing devices follows a basic protocol and creates challenges in big data networks due to its influence on every aspect of big data network performance. However, numerous challenges still emerge when massive data enter big data networks. ![]() Data transmission, data protection and intrusion detection technologies can help guarantee the security of IoT data. Data flows are still increasing, continuously promoting the development of big data networks. A Cisco report shows that data flows generated by the Internet of Things (IoT) account for 69% of data flows generated by the Internet, reflecting a 30-fold increase relative to levels in 2000. We can obtain large amounts of data because these sensing devices can sense surrounding environments anytime and anywhere. However, most of these large devices are embedded sensing devices, which are the main source of big data networks. This has resulted in a computation shift from the cloud to the edge, and the combination of edge and cloud networks has formed the edge cloud computing mode, which has considerably changed existing networks. The computing, storage, and communication power of these devices has also developed considerably with network edges accumulating numerous resources for computing, storage, and communication, forming the so-called edge network. In recent years, with the development of microprocessor technologies, devices connected to the Internet have become more prevalent with the number of such devices anticipated to increase to 23 billion by 2020 according to relevant research. A sensor-cloud system (SCS) combines cloud computing with sensor nodes to sense, collect, process, analyze, store and share data for various applications this combination has largely promoted the development of big data networks. However, the development of big data networks is attributable to the development of numerous applications with several sensing devices. At the same time, big data networks have attracted the attention of numerous researchers. Extensive experiments show that the DWT-MAC protocol reduces the average delay in the transmission of data of the highest priority by 49.3%.Ĭloud computing has been widely used by the scientific community and industry, because users can benefit from computing infrastructures at low costs. While the DWT-MAC protocol cannot ensure wait times of the optimal value, it can ensure that it quickly comes close to the optimal value, which is suitable for dynamically changing networks. A dynamic time adjustment algorithm, which causes the wait time to always trail the optimal value, is proposed to reduce delays. In the DWT-MAC protocol, the wait time changes according to the number of senders, which can ensure that it always approaches the optimal value. The DWT-MAC protocol is novel in that it changes the receiver wait time, which has been fixed in previous MAC protocols, and it reduces the delay in data transmission by dynamically adjusting the wait time. In this paper, a Dynamic Wait time-based MAC (DWT-MAC) protocol is proposed for data differentiated services of a sensor-cloud system (SCS). Transmitting high-priority data to control centers quickly to manage emergencies is essential for sensor-cloud applications. The energy-aware MAC protocol is the basic communication protocol for device-to-device communication in sensor-cloud computing and facilitates data sensing, computing, and sharing for applications.
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