A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

Tshiningayamwe, Loini; Lusilao-Zodi, G. A.; Dlodlo, Mqhele E.

doi:10.1007/978-3-319-27400-3_31

Cited by 11 publications

(8 citation statements)

References 39 publications

(59 reference statements)

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“…In [55], a priority rate-based routing protocol (PRRP) is proposed for congestion control in low-resource bandwidth networks such as wireless multimedia sensor networks. Due to the high bandwidth demand for multimedia traffic, congestion may easily occur in low-resource bandwidth networks.…”

Section: A Congestion Control Schemesmentioning

confidence: 99%

5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions

2019

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Healthcare is undergoing a rapid transformation from traditional hospital and specialist focused approach to a distributed patient-centric approach. Advances in several technologies fuel this rapid transformation of healthcare vertical. Among various technologies, communication technologies have enabled to deliver personalized and remote healthcare services. At present, healthcare widely uses the existing 4G network and other communication technologies for smart healthcare applications and are continually evolving to accommodate the needs of future intelligent healthcare applications. As the smart healthcare market expands the number of applications connecting to the network will generate data that will vary in size and formats. This will place complex demands on the network in terms of bandwidth, data rate, and latency, among other factors. As this smart healthcare market matures, the connectivity needs for a large number of devices and machines with sensor-based applications in hospitals will necessitate the need to implement Massive-Machine Type Communication. Further use cases such as remote surgeries and Tactile Internet will spur the need for Ultra Reliability and Low Latency Communications or Critical Machine Type Communication. The existing communication technologies are unable to fulfill the complex and dynamic need that is put on the communication networks by the diverse smart healthcare applications. Therefore, the emerging 5G network is expected to support smart healthcare applications, which can fulfill most of the requirements such as ultra-low latency, high bandwidth, ultra-high reliability, high density, and high energy efficiency. The future smart healthcare networks are expected to be a combination of the 5G and IoT devices which are expected to increase cellular coverage, network performance and address securityrelated concerns. This paper provides a state-of-the-art review of the 5G and IoT enabled smart healthcare, Taxonomy, research trends, challenges, and future research directions.INDEX TERMS 5G, smart healthcare, software-defined network, network function virtualization, the Internet of Things (IoT), device-to-device (D2D), ultra reliability and low latency communications.

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Section: A Congestion Control Schemesmentioning

confidence: 99%

5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions

2019

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“…Swain et al [10] have used the notion of traffic class priority to propose a priority-based adaptive rate control mechanism to control the congestion at each node. Priority concept is also used by different researchers [30], [31], [32] to improve the QoS of the network. It is found from the literature that using the notion of priority, QoS of the network could be improved but this could not overcome the issue of hotspots arising out of high data rate in the network.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Queue Management and Traffic Class Priority Based Fairness Rate Control in Wireless Sensor Networks

Swain

Nanda

2021

IEEE Access

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Congestion control in Wireless Sensor Networks (WSNs) is one of the key areas of research and different algorithms have been proposed using either of the notions of fair rate allocation, traffic class priority, and queue management. Use of the any one of the above is not adequate to address the challenges. Hence, in this paper, we have proposed a novel congestion control algorithm using the combined notions of fair allocation of bandwidth, prioritizing traffic classes, and Adaptive Queue Management (ADQM). The proposed Weighted Priority based Fair Queue Gradient Rate Control (WPFQGRC) scheme achieves the fair distribution of spare bandwidth by considering the traffic class priority, average queue size, and the connected loads of a node. Average queue size at every node is adapted based on the proposed notion of the gradient of the differential of Global Priority (GP) with respect to the differential of queue size. The output rate of a given node is computed based on the GP of the node and the average queue size. The spare bandwidth of a node is fairly distributed by taking into account the connected load of the given node. The proposed algorithm is developed to suit to a general topology of WSN, however for the sake of illustration, we have considered a tree topology network that deals with both Real-Time (RT) and Non-Real Time (NRT) traffic classes. The proposed algorithm is implemented in NS3 platform in Linux environment and the performance of the algorithm is evaluated in terms of throughput, packet loss, and packet delay. Besides the effect of traffic class patterns, effects of node mobility and the average queue size on throughput have also been studied. The performance of the proposed algorithm is found to be superior to that of Yaghmaee et al.

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“…In the traffic class priority strategy, by and large, RT traffic is given high priority. But Tshiningayamwe et al [10] have proposed a priority based routing protocol to differentiate the service requirements by mixing a RT traffic with three NRT traffic. Besides the notion of priority, transmission of critical patient data in real time environment has been dealt by Yaakob and Khalil [29], where they have attempted to overcome congestion by combining notions of Relaxation Theory and Max-Min fairness.…”

Section: Related Workmentioning

confidence: 99%

“…where, GP Sink w is the weighted GP of the sink node and is determined as GP Sink w = i∈C(Sink) GP i w , which is the sum of the weighted GP of the connected child nodes of the sink. With the modified GP of (16) and output rate of (17), the updated rates of the sink node and the parent nodes are computed analogous to (9), (10) and (11). They are expressed as follows,…”

Section: B Wpddrc Based Rate Control Strategymentioning

confidence: 99%

“…The performance of this protocol has been evaluated with different metrics. A priority based routing protocol with service requirements has also been proposed for the congestion control in WSN [10]. Recently, the notion of priority based rate control has been used by Monowar and Bajaber [11] to overcome the congestion and hotspot avoidance in body area networks.…”

Section: Introductionmentioning

confidence: 99%

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Priority Based Adaptive Rate Control in Wireless Sensor Networks: A Difference of Differential Approach

Swain

Nanda

2019

IEEE Access

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Wireless Sensor Networks (WSN), when deployed in a real world scenario have to deal with a wide variety of data. Because of the constrained bandwidth, different types of data need to be handled with different priorities in order to prevent congestion in a network. Traffic class priority based rate control algorithms have been proposed by Yaghmaee et al. for congestion avoidance and these are based on the rate difference at a given node. In this research work, we have proposed a Difference of Differential Rate Control (DDRC) algorithm at a given node, which is based on the difference of differential rate between sink node and the given node. The next proposed one is Weighted Priority Difference of Differential Rate Control (WPDDRC) algorithm which is based on the combination of the weighted priority of the traffic class and the difference of differential rate of a given node. This is intended to handle Real Time (RT) data, which may be bursty in nature, and also a combination of the RT and Non-Real Time (NRT) data. Though the proposed algorithms are validated on a fixed topology, they are also valid for the general topology of WSN. The proposed algorithms have been implemented in NS3 platform and the performances of the algorithms have been found to be superior to those of counterpart techniques. INDEX TERMS Rate control, traffic class priority, wireless sensor networks.

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A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

Cited by 11 publications

References 39 publications

5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions

5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions

Adaptive Queue Management and Traffic Class Priority Based Fairness Rate Control in Wireless Sensor Networks

Priority Based Adaptive Rate Control in Wireless Sensor Networks: A Difference of Differential Approach

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