Description:
Resource sharing between Book-Ahead (BA) and Instantaneous Request (IR) reservation often results in high preemption rate of on-going IR calls. High IR call preemption rate causes interruption to service continuity which is considered as detrimental in a QoS-enabled network. A number of call admission control models have been proposed in literature to reduce the preemption rate of on-going IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an Artificial Neural Network (ANN) model to dynamically control the preemption rate of on-going calls in a QoS-enabled network. The model maps network traffic parameters and desired level of preemption rate into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired level of preemption rate. Simulation results show that the preemption rate attained by the model closely matches with the target rat
Description:
Resource sharing between book-ahead (BA) and instantaneous request (IR) reservation often results in high preemption rates for ongoing IR calls in computer networks. High IR call preemption rates cause interruptions to service continuity, which is considered detrimental in a QoS-enabled network. A number of call admission control models have been proposed in the literature to reduce preemption rates for ongoing IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an artificial neural network (ANN) model to dynamically control the preemption rate of ongoing calls in a QoS-enabled network. The model maps network traffic parameters and desired operating preemption rate by network operator providing the best for the network under consideration into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired operating preemption rates. Simulation results show that the preemption rate attained by the model closely matches with the target rate.
Description:
Wireless access technology has come a long way in its relatively short but remarkable lifetime, which has so far been led by WiFi technology. WiFi enjoys a high penetration in the market.Most of the electronic gadgets such as laptop, notepad, mobile set, etc., boast the provision ofWiFi. Currently most WiFi hotspots are connected to the Internet via wired connections (e.g., Ethernet), and the deployment cost of wired connection is high. On the other hand, since WiMAX can provide a high coverage area and transmission bandwidth, it is very suitable for the backbone networks of WiFi. WiMAX can also provide the better QoS needed for many 4G applications. WiMAX devices, however, are not as common as WiFi devices and it is also expensive to deploy aWiMAX-only infrastructure. An integrated WiMAX/WiFi architecture (using WiMAX as backhaul connection for WiFi) can support 4G applications with QoS assurance and mobility, and provide high-speed broadband services in rural, regional and urban areas while reducing the backhaul cost. WiMAX and WiFi have different MAC mechanisms to handle QoS. WiMAX MAC architecture is connection-oriented providing the platform for strong QoS control. In contrast,WiFi MAC is not connection-oriented, hence can provide only best effort services. Delivering improved QoS in an integrated WiMAX/WiFi architecture poses a serious technological challenge. The paper depicts a converged architecture of WiMAX and WiFi, and then proposes an adaptive resource distribution model for the access points. The resource distribution model ultimately allocates more time slots to those connections that need more instantaneous resources to meet QoS requirements. A dynamic splitting technique is also presented that divides the total transmission period into downlink and uplink transmission by taking the minimum data rate requirements of the connections into account. This ultimately improves the utilization of the available resources, and the QoS of the connections. Simulation results show that the proposed schemes significantly outperform the other existing resource sharing schemes, in terms of maintaining QoS of different traffic classes in an integratedWiMAX/WiFi architecture
Description:
When network resources are shared between Instantaneous Request (IR) and Book-Ahead (BA) connections, activation of future BA connections may cause preemption of on-going IR connections due to resource scarcity. Rerouting of preempted calls via alternative feasible paths is often considered as the final option to restore and maintain service continuity. Existing rerouting techniques, however, do not ensure acceptably low service disruption time and suffer from high failure rate and low network utilization. In this work, a new rerouting strategy is proposed that estimates the future resource scarcity, identifies the probable candidate connections for preemption and initiates the rerouting process in advance for those connections. Simulations on a widely used network topology suggest that the proposed rerouting scheme achieves a higher successful rerouting rate with lower service disruption time, while not compromising other network performance metrics like utilization and call blocking rate.