Performance Analysis of IoT-based Healthcare Heterogeneous Delay-sensitive Multi-Server Priority Queuing System

Asingwire, Barbara K.; Ngenzi, Alexander; Sibomana, Louis; Kabiri, Charles

doi:10.14569/ijacsa.2021.0121073

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Queuing systems uses a low-latency queue (LLQ) or priority queue to meet the QoS requirements for low delay, low jitter, and low loss of traffic in that queue by providing a high weight, which results in a greater time or bandwidth to this queue. However, if the traffic is mostly a type of voice traffic, then the scheduler never services the other queues, which is known as starvation and leads to packet loss when packets are not forwarded [5,[30][31][32].…”

Section: Queuing and Priorities In Routersmentioning

confidence: 99%

Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm

Ghani

Al-Jobouri

2023

Electronics

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Software-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS) requirements. The main problem is that when packets from different applications pass through computer networks, they have different QoS criteria. To meet the requirements of packets, routers classify these packets, add them to multiple weighting queue systems, and forward them according to their priorities. Multiple queue systems in routers usually use a class-based weighted round-robin (CBWRR) scheduling algorithm with pre-configured fixed weights for each priority queue. The problem is that the intensity of traffic in general and of each packet class occasionally changes. Therefore, in this work, we suggest using the particle swarm optimization algorithm to find the optimal weights for the weighted fair round-robin algorithm (WFRR) by considering the variable densities of the traffic. This work presents a framework to simulate router operations by determining the weights and schedule packets and forwarding them. The proposed algorithm to optimize the weights is compared with the conventional WFRR algorithm, and the results show that the particle swarm optimization for the weighted round-robin algorithm is more efficient than WFRR, especially in high-intensity traffic. Moreover, the average packet-loss ratio does not exceed 7%, and the proposed algorithms are better than the conventional CBWRR algorithm and the related work results.

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Section: Queuing and Priorities In Routersmentioning

confidence: 99%

Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm

Ghani

Al-Jobouri

2023

Electronics

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“…In emergency situations, it is important for healthcare traffic to have low latency to allow the healthcare personnel to respond on time [4,5]. However, due to the heterogeneity of IoT servers and applications with varying degrees of service requirements, traditional computing server scheduling schemes cannot deliver services to IoT-based healthcare services [6]. Therefore, the standard server scheduling algorithms should be enhanced to efficiently schedule packets by taking into account the heterogeneity of servers and various service requirements in order to satisfy user expectations.…”

Section: Introductionmentioning

confidence: 99%

“…In literature, IoT servers are widely assumed to be homogeneous (having equal service rates and consisting of similar devices) [13,14]. Furthermore, our previous work [6] introduced the idea of applying priority at two levels based on the delay and size of healthcare packets, based on the assumption that the servers are homogeneous. However, IoT consists of various heterogeneous devices that operate at different service rates [9].…”

Section: Introductionmentioning

confidence: 99%

Delay and size‐dependent priority‐aware scheduling for IoT‐based healthcare traffic using heterogeneous multi‐server priority queueing system

Asingwire,

Sibomana,

Ngenzi

et al. 2023

IET Communications

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Internet of Things (IoT) based healthcare applications are time‐sensitive and any delay can cause alarming situations, including death of patients. The Earliest Deadline First (EDF) scheduling scheme has been proposed for use in IoT‐based healthcare applications. However, the EDF scheme performs poorly under overloaded conditions due to giving highest priority to packets that are close to missing their deadlines. Some studies have proposed the use of Priority EDF to overcome the challenges of EDF; however, Priority EDF still favours higher priority queues which increases the waiting times of lower priority queues. In order to overcome the limitation of EDF and its variants, this paper proposes a system model for a prioritized scheduling (PS) scheme. The PS scheme is an improvement of the Earliest Deadline First (EDF) scheme and its variants for IoT‐based healthcare applications. The PS scheme uses a heterogeneous multi‐server priority queuing system to provide service differentiation by prioritizing short packets over large packets and delay sensitive packets are serviced before delay tolerant packets. Numerical results demonstrate that the PS scheme minimizes the mean slowdown for both delay sensitive short and large packets at low and high load values. Additionally, the PS scheme performs better than the EDF and Priority EDF schemes in terms of reducing mean slowdown of packets and the PS scheme performs better than the EDF in terms of throughput for all packet sizes at both low and high load values. The performance improvement in terms of throughput is more pronounced at high load values. This addresses the challenge of the EDF scheme which performs poorly under overloaded conditions and the challenge of the Priority EDF scheme which favours higher priority queues at the expense of low priority queues.

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Performance Analysis of Delay and Size-Dependent Scheduling for IoT-based Healthcare Traffic Using Heterogeneous Multi-Server Priority Queueing System

Asingwire,

Sibomana,

Ngenzi

et al. 2024

2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

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Performance Analysis of IoT-based Healthcare Heterogeneous Delay-sensitive Multi-Server Priority Queuing System

Cited by 3 publications

References 25 publications

Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm

Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm

Delay and size‐dependent priority‐aware scheduling for IoT‐based healthcare traffic using heterogeneous multi‐server priority queueing system

Performance Analysis of Delay and Size-Dependent Scheduling for IoT-based Healthcare Traffic Using Heterogeneous Multi-Server Priority Queueing System

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