Communication networks for healthcare environments support various application types and should be capable of providing them with the required Quality of Service (QoS) in terms of reliable data delivery, considerable data rate and low latency. The introduction of Tactile Internet (TI) healthcare applications is expected to upgrade the level of provided services to patients. The requirements of these applications are very stringent and a major requirement is that the existing network infrastructure must support them. Passive Optical Networks (PONs) have been proposed as an ideal candidate to support such demanding environments. One of the major challenges of such networks, which significantly affects the provided QoS, is the effective resource allocation in both the time and the wavelength domains. The existing resource allocation algorithms for PONs were designed without considering the stringent requirements of TI applications thus making PON support for TI inefficient. In this paper, a new double per priority queue dynamic wavelength and bandwidth allocation algorithm is presented. This algorithm allocates the network resources efficiently and fairly using several techniques, in order to meet the QoS demands of Tactile and other types of healthcare applications. Extensive simulation results indicate the effectiveness of the proposed algorithm to provide the required QoS for medical applications under various simulation scenarios whereas other well-known schemes are shown to lack such support. INDEX TERMS Healthcare applications, passive optical networks, quality of service, tactile Internet.
Low Power Wide Area Networks have emerged as a leading communications technology in the field of Internet of Things sensor and monitoring networks. In such networks, uplink traffic is characterized as a combination of periodic data reports and event-triggered alarm reports. When an many devices detect an event in a short timespan, a burst of concurrent transmissions can occur, leading to a surge of collisions, and thus severe data delivery performance degradation. In this paper, a hybrid random/scheduled access strategy is proposed for mitigating the impact of traffic-triggering events on network performance. Under periodic report traffic the LoRaWAN standard Class A protocol is in effect, but after an event a TDMA scheme is applied. Three implementations of this strategy are described. The first is a pair of novel MACs for LoRaWAN, allowing (a) synchronization of end devices with the network using the event detection as a crude synchronization point, and (b) the dynamic scheduling of groups of devices. The other two implementations build upon a single-hop and a two-hop previously proposed LoRaWAN-based wake-up architectures, respectively. The above approaches are validated and studied through extensive simulation. The results show improved packet delivery ratio over the Class A MAC. The effect is more prominent as the event propagation velocity increases. The proposed approach also surpasses LoRaWAN in energy per delivered bit for high event propagation velocities. Finally, the novel protocol has a lower hardware and deployment complexity than the wake up radio based alternatives, at the cost of higher energy consumption.
In recent years, the Internet of Things (IoT) is growing rapidly and gaining ground in a variety of fields. Such fields are environmental disasters, such as forest fires, that are becoming more common because of the environmental crisis and there is a need to properly manage them. Therefore, utilizing IoT for event detection and monitoring is an effective solution. A technique for monitoring such events over a large area is proposed in this research. This work makes use of the Long-Range Wide Area Network (LoRaWAN) protocol, which is capable to connect low-power devices distributed on large geographical areas. A learning-automata-based hybrid MAC model is suggested to reduce the transmission delay, when a small part of the network produces event packets stemming from an event occurrence that is related to environmental monitoring applications, such as events related to forest fires. The proposed hybrid MAC is evaluated via simulation, which indicates that it achieves significantly higher performance in terms of packet delay, when compared to traditional LoRaWAN schemes.
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