Resource Allocation for Machine-Type Communication of Energy-Harvesting Devices in Wi-Fi HaLow Networks

An Analytical Model for the Aggregate Throughput of IEEE 802.11ah Networks under the Restricted Access Window Mechanism

The IEEE 802.11ah is an amendment to the IEEE 802.11 standard to support the growth of the Internet of Things (IoT). One of its main novelties is the restricted access window (RAW), which is a channel access feature designed to reduce channel contention by dividing stations into RAW groups. Each RAW group is further divided into RAW slots, and stations only attempt channel access during the RAW slot they were assigned to. In this paper, we propose a discrete-time Markov chain model to evaluate the average aggregate throughput of IEEE 802.11ah networks using the RAW mechanism under saturated traffic and ideal channel conditions. The proposed analytical model describes the behavior of an active station within its assigned RAW slot. A key aspect of the model is the consideration of the event of RAW slot time completion during a station's backoff operation. We study the average aggregate network throughput for various numbers of RAW slots and stations in the network. The numerical results derived from our analytical model are compared to computer simulations based on an IEEE 802.11ah model developed for the ns-3 simulator by other researchers, and its performance is also compared to two other analytical models proposed in the literature. The presented results indicate that the proposed analytical model reaches the closest agreement with independently-derived computer simulations.

Resource Allocation Strategy of the Educational Resource Base for MEC Multiserver Heuristic Joint Task

This paper analyzes the application of MEC multiserver heuristic joint task in resource allocation of the educational resource database. After constructing the scenario of educational resource database, a mathematical model is constructed from the dimensions of local execution strategy, unloading execution, and given educational resource allocation, in order to optimize the optimal allocation of educational resources through MEC. The results show that the DOOA scheme has good performance in terms of calculation cost and timeout rate. Compared with other benchmark schemes, the DQN-based unloading scheme has better performance, can effectively balance the load, and is better than the random unloading scheme and the SNR-based unloading scheme in terms of delay and calculation cost. The results show that the total hits of all category 1 users' content requests account for the proportion of the total content requests. The images have a small downward trend at the 15000 and 30000 time slots and then continue to rise. This shows that the proposed scheme can automatically adjust the caching strategy to adapt to the changes of content popularity, which proves that the agent can correctly perceive the changing trend of content popularity when the popularity of network content is unknown and improve the caching strategy accordingly to improve the cache hit rate. Therefore, the allocation of educational resources based on the MEC multiserver heuristic joint task is more reasonable and can achieve the optimal solution.

Analytical Study of Periodic Restricted Access Window Mechanism for Short Slots

The tremendous number of devices involved in the Internet of Things is bringing new challenges to wireless networking. The more devices that transmit in a wireless network, the higher the contention for the channel. The novel Wi-Fi HaLow standard introduces a new channel access mechanism called the Periodic Restricted Access Window (PRAW), which aims to reduce this contention. With this mechanism, an access point can define a series of time intervals during which only a predefined group of stations can transmit data while the other stations are forbidden to access the channel. Unfortunately, the standard does not suggest how to configure the PRAW mechanism according to scenario-specific requirements and restrictions. Many Internet of Things scenarios require the fast and low energy consumption delivery of measurement data from wireless sensors while saving channel resources for other stations that transmit, for example, multimedia traffic. Therefore, this paper studies the problem of the minimization of the channel timeshare consumed by the PRAW with restrictions on the average delay and power consumption. To solve the problem and configure the PRAW optimally, a novel analytical model is developed. The key feature of the model is the consideration of the case of short PRAW slots that allow the computational complexity to be reduced and high accuracy to be achieved. These properties make the model suitable for implementation in real devices.

Wireless technologies, medical applications and future challenges in WBAN: a survey

Interest and need for Wireless Body Area Networks (WBANs) have significantly increased recently. WBAN consists of miniaturized sensors designed to collect and transmit data through wireless network, enabling medical specialists to monitor patients during their normal daily life and providing real time opinions for medical diagnosis. Many wireless technologies have proved themselves in WBAN applications, while others are still under investigations. The choice of the technology to adopt may depend on the disease to monitor and the performance requirements, i.e. reliability, latency and data rate. In addition, the suitable sensor is essential when seeking to extract the data related to a medical measure. This paper aims at surveying the wireless technologies used in WBAN systems. In addition to a detailed survey on the existing technologies, the use of the emerging Low Power Wide Area Network (LPWAN) technologies, and the future 5G, B5G and 6G is investigated, where the suitability of these technologies to WBAN applications is studied from several perspectives. Furthermore, medical applications of WBAN are discussed by presenting their methodologies, the adopted wireless technologies and the used sensors. Given that each medical application requires the appropriate sensor to extract the data, we highlight a wide range of the sensors used in the market for medical systems. Recent and future challenges in WBAN systems are given related to the power consumption, the emergence of the Internet of Things (IoT) technologies in WBAN and others.