• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5286-5306
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• 2016

Emerging applications in automation, medical imaging, traffic monitoring and surveillance need real-time data transmission over Wireless Sensor Networks (WSNs). Guaranteeing Quality of Service (QoS) for real-time traffic over WSNs creates new challenges. Rapid penetration of smart devices, standardization of Machine Type Communications (MTC) in next generation 5G wireless networks have added new dimensions in these challenges. In order to satisfy such precise QoS constraints, in this paper, we propose a new cross-layer QoS-provisioning strategy in Wireless Multimedia Sensor Networks (WMSNs). The network layer performs statistical estimation of sensory QoS parameters. Identifying QoS-routing problem with multiple objectives as NP-complete, it discovers near-optimal QoS-routes by using evolutionary genetic algorithms. Subsequently, the Medium Access Control (MAC) layer classifies the packets, automatically adapts the contention window, based on QoS requirements and transmits the data by using routing information obtained by the network layer. Performance analysis is carried out to get an estimate of the overall system. Through the simulation results, it is manifested that the proposed strategy is able to achieve better throughput and significant lower delay, at the expense of negligible energy consumption, in comparison to existing WMSN QoS protocols.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.149-159
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• 2011

In this paper, we study the problem of how to design a medical-grade wireless local area network (WLAN) for healthcare facilities. First, unlike the IEEE 802.11e MAC, which categorizes traffic primarily by their delay constraints, we prioritize medical applications according to their medical urgency. Second, we propose a mechanism that can guarantee absolute priority to each traffic category, which is critical for medical-grade quality of service (QoS), while the conventional 802.11e MAC only provides relative priority to each traffic category. Based on absolute priority, we focus on the performance of real-time patient monitoring applications, and derive the optimal contention window size that can significantly improve the throughput performance. Finally, for proper performance evaluation from a medical viewpoint, we introduce the weighted diagnostic distortion (WDD) as a medical QoS metric to effectively measure the medical diagnosability by extracting the main diagnostic features of medical signal. Our simulation result shows that the proposed mechanism, together with medical categorization using absolute priority, can significantly improve the medical-grade QoS performance over the conventional IEEE 802.11e MAC.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.518-528
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• 2009

IEEE 802.11 wireless local area network (WLAN) has become the prevailing solution for wireless Internet access while transport control protocol (TCP) is the dominant transport-layer protocol in the Internet. It is known that, in an infrastructure-based WLAN with multiple stations carrying long-lived TCP flows, the number of TCP stations that are actively contending to access the wireless channel remains very small. Hence, the aggregate TCP throughput is basically independent of the total number of TCP stations. This phenomenon is due to the closed-loop nature of TCP flow control and the bottleneck downlink (i.e., access point-to-station) transmissions in infrastructure-based WLANs. In this paper, we develop a comprehensive analytical model to study TCP dynamics in infrastructure-based 802.11 WLANs. We calculate the average number of active TCP stations and the aggregate TCP throughput using our model for given total number of TCP stations and the maximum TCP receive window size. We find out that the default minimum contention window sizes specified in the standards (i.e., 31 and 15 for 802.11b and 802.11a, respectively) are not optimal in terms of TCP throughput maximization. Via ns-2 simulation, we verify the correctness of our analytical model and study the effects of some of the simplifying assumptions employed in the model. Simulation results show that our model is reasonably accurate, particularly when the wireline delay is small and/or the packet loss rate is low.