Conference Paper

Efficient bandwidth management in Broadband Wireless Access Systems using CAC-based dynamic pricing

Sch. of Comput., Queen's Univ., Kingston, ON
DOI: 10.1109/LCN.2008.4664208 Conference: Local Computer Networks, 2008. LCN 2008. 33rd IEEE Conference on
Source: IEEE Xplore


While the demand for mobile broadband wireless services continues to increase, radio resources remain scarce. Even with the substantial increase in the supported bandwidth in next generation Broadband Wireless Access Systems (BWASs), it is expected that these systems will severely suffer from congestion due to the rapid increase in demand of bandwidth intensive applications. Without efficient bandwidth management and congestion control schemes, network operators may not be able to meet the increasing demand of users for multimedia services, and hence they may suffer immense amount of revenue loss. In this paper, we propose an admission-level bandwidth management scheme consisting of Call Admission Control (CAC) and dynamic pricing. The main aim of our proposed scheme is to provide monetary incentives to users to use the wireless resources efficiently and rationally, hence, allowing efficient bandwidth management at the admission level. By dynamically determining the prices of units of bandwidth, the proposed scheme can guarantee that the arrival rates to the system are less than or equal to the optimal ones computed dynamically, hence, guaranteeing a congestion-free system. Simulation results show the effectiveness and strengths of our proposed approach.

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Available from: Najah Abu Ali, Mar 06, 2014
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    • "The purpose of this model is to support multiple types of service with different QoS requirements in heterogeneous wireless networks. The model presented in [9] allows a packet transfer in the switch and admits packets depending on the switch and network occupancy. Packets are transferred if the required bandwidth FULL PAPER "
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    ABSTRACT: As real-time traffic requires more attention, it is given priority over non-real-time traffic in Cellular IP networks. Bandwidth reservation is often applied to serve such traffic in order to achieve better Quality of Service (QoS). Evolutionary Algorithms are quite useful in solving optimization problems of such nature. This paper employs Genetic Algorithm (GA) for bandwidth management in Cellular IP network. It compares the performance of the model with another model used for optimizing Connection Dropping Probability (CDP) using Particle Swarm Optimization (PSO). Both models, GA based and PSO based, try to minimize the Connection Dropping Probability for real-time users in the network by searching the free available bandwidth in the user's cell or in the neighbor cells and assigning it to the real-time users. Alternatively, if the free bandwidth is not available, the model borrows the bandwidth from non-real time-users and gives it to the real-time users. Experimental results evaluate the performance of the GA based model. The comparative study between both the models indicates that GA based model has an edge over the PSO based one. Index Terms—Genetic Algorithm, Cellular IP networks, Quality of Service, Connection Completion Probability, Bandwidth Reservation, Particle Swarm Optimization. There are many Evolutionary Algorithms e.g. Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Ant Colony Optimization (ACO) etc. Evolutionary Algorithms often offer well approximating solutions to all types of problems. The proposed work uses Genetic Algorithms (GA) for bandwidth management in Cellular IP networks and compares the performance of the model with the performance of the PSO based model, proposed earlier (3), with the same objective.
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    ABSTRACT: Next Generation of Wireless Networks are expected to be heterogeneous, whereby multiple Radio Access Technologies will work together in a coordinated fashion. These networks will be required to accommodate different types of users with different QoS requirements. Effective Joint Call Admission Control (JCAC) algorithms are a prerequisite in NGWN to ensure that users are offered optimal QoS. Studies have therefore been undertaken where JCAC algorithms for NGWN have been proposed. Correspondingly, pricing has been used with JCAC to obtain optimal QoS. In these studies, the revenue obtained by network operators has not been analysed. This paper proposes a dynamic pricing model for NGWN. The price of services will determine how users behave as they access the network. Users are considered to be price sensitive whereby user demand increases when the price is lowed and vice versa. This phenomenon is used to increase utility during periods of low load and reduce congestion during periods of overload. The revenue obtained by network operators in the NGWN is hence determined over a 24-hour period. To bench mark the dynamic pricing model, comparison is made with flat pricing incorporated in the NGWN. The dynamic pricing model is found to offer higher revenue, better user utility and improved system performance.
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    ABSTRACT: In this paper, we proposed a dynamic network pricing scheme, which considers both Call Admission Control (CAC) and Network Congestion Control (NCC), denoted as Contract Binded CAC {CBCAC). CAC calculates the optimal arrival rates and limits the admitted calls at every time. When the network is underlized, all the users are charged for service consumption normally. But if it is congested, they are charged for NCC in addition, and then make a decision for congestion control. The numerical simulation results show that by dynamically computing these prices, our scheme can strike the right balance between the utilization of WANs resources and the blocking probabilities.
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