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A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks
Mobile wireless resources demand is rapidly growing due to the proliferation of bandwidth-hungry mobile devices and applications. This has resulted in congestion in mobile wireless networks (MWN) especially during the peak hours when user traffic can be as high as tenfold the average traffic. Mobile...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2017
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| _version_ | 1867614142610800640 |
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| access_status_str | Open Access |
| author | Mutungi, Jeremiah Nzioka |
| author2 | Falowo, Olabisi E |
| author_browse | Falowo, Olabisi E Mutungi, Jeremiah Nzioka |
| author_facet | Falowo, Olabisi E Mutungi, Jeremiah Nzioka |
| author_sort | Mutungi, Jeremiah Nzioka |
| collection | Thesis |
| description | Mobile wireless resources demand is rapidly growing due to the proliferation of bandwidth-hungry mobile devices and applications. This has resulted in congestion in mobile wireless networks (MWN) especially during the peak hours when user traffic can be as high as tenfold the average traffic. Mobile network operators (MNOs) have been trying to solve this problem in various ways. First, MNOs have tried to expand the network capacity but have still been unable to meet the peak hour demand. Focus has then shifted to economic and behavioral mechanisms. The widely used of these economic mechanisms is dynamic pricing which varies the MWN resources' price according to the congestion level in the MWN. This encourages users to shift their non-critical traffic from the busy hour, when the MWN is congested, to off-peak hours when the network is under-utilized. As a result, congestion of the MWN during the peak hours is reduced. At the same time, the MWN utilization during the off-peak hours is also increased. The current dynamic pricing schemes, however, only consider the congestion level in the call-originating cell and neglect the call-destination cell when computing the dynamic price. Due to this feature, we refer the current dynamic pricing schemes as source–based dynamic pricing (SDP) schemes in this work. The main problem with these schemes is that, when the majority of the users in a congested cell are callees, dynamic pricing is ineffective because callers and not callees pay for network services, and resources used by callers and callees are the same for symmetric services. For example, application of dynamic pricing does not deter a callee located in a congested cell from receiving a call, which originates from a caller located in an uncongested cell. Also, when the distribution of prospective callees is higher than that of callers in an underutilized cell, SDP schemes are ineffective as callees do not pay for a call and therefore low discounts do not entice them to increase utilization. In this distribution, dynamic pricing entices prospective callers to make calls but since their distribution is low, the MWN resource utilization does not increase by any significant margin. To address these problems, we have developed a source-destination based dynamic pricing (SDBDP) scheme, which considers congestion levels in both the call-originating and calldestination cells to compute the dynamic price to be paid by a caller. This SDBDP scheme is integrated with a load-based joint call admission control (JCAC) algorithm for admitting incoming service requests in to the least utilized radio access technology (RAT). The load-based JCAC algorithm achieves uniform traffic distribution in the heterogeneous wireless network (HWN). To test the SDBDP scheme, we have developed an analytical model based on M/M/m/m queuing model. New or handoff service requests, arriving when all the RATs in the HWN are fully utilized, lead to call blocking for new calls and call dropping for handoff calls. The call blocking probability, call dropping probability and percentage MWN utilization are used as the performance metrics in evaluating the SDBDP scheme. An exponential demand model is used to approximate the users' response to the presented dynamic price. The exponential demand model captures both the price elasticity of demand and the demand shift constant for different users. The matrix laboratory (MATLAB) tool has been used to carry out the numerical simulations. An evaluation scenario consisting of four groups of co-located cells each with three RATs is used. Both SDP and the developed SDBDP schemes have been subjected under the evaluation scenario. Simulation results show that the developed SDBDP scheme reduces both the new call blocking and handoff call dropping probabilities during the peak hours, for all callercallee distributions. On the other hand, the current SDP scheme only reduces new call blocking and handoff call dropping probabilities only under some caller –callee distributions (When the callers were the majority in the HWN). Also, the SDBDP scheme increases the percentage MWN utilization during the off-peak for all the caller-callee distributions in the HWN. On the other hand, the SDP scheme is found to increase the percentage MWN utilization only when the distribution of callers is higher than that of callees in the HWN. From analyzing the simulations results, we conclude that the SDBDP scheme achieves better congestion control and MWN resource utilization than the existing SDP schemes, under arbitrary caller-callee distribution. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/23743 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:47:20.765Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/23743 A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks Mutungi, Jeremiah Nzioka Falowo, Olabisi E Electrical Engineering Mobile wireless resources demand is rapidly growing due to the proliferation of bandwidth-hungry mobile devices and applications. This has resulted in congestion in mobile wireless networks (MWN) especially during the peak hours when user traffic can be as high as tenfold the average traffic. Mobile network operators (MNOs) have been trying to solve this problem in various ways. First, MNOs have tried to expand the network capacity but have still been unable to meet the peak hour demand. Focus has then shifted to economic and behavioral mechanisms. The widely used of these economic mechanisms is dynamic pricing which varies the MWN resources' price according to the congestion level in the MWN. This encourages users to shift their non-critical traffic from the busy hour, when the MWN is congested, to off-peak hours when the network is under-utilized. As a result, congestion of the MWN during the peak hours is reduced. At the same time, the MWN utilization during the off-peak hours is also increased. The current dynamic pricing schemes, however, only consider the congestion level in the call-originating cell and neglect the call-destination cell when computing the dynamic price. Due to this feature, we refer the current dynamic pricing schemes as source–based dynamic pricing (SDP) schemes in this work. The main problem with these schemes is that, when the majority of the users in a congested cell are callees, dynamic pricing is ineffective because callers and not callees pay for network services, and resources used by callers and callees are the same for symmetric services. For example, application of dynamic pricing does not deter a callee located in a congested cell from receiving a call, which originates from a caller located in an uncongested cell. Also, when the distribution of prospective callees is higher than that of callers in an underutilized cell, SDP schemes are ineffective as callees do not pay for a call and therefore low discounts do not entice them to increase utilization. In this distribution, dynamic pricing entices prospective callers to make calls but since their distribution is low, the MWN resource utilization does not increase by any significant margin. To address these problems, we have developed a source-destination based dynamic pricing (SDBDP) scheme, which considers congestion levels in both the call-originating and calldestination cells to compute the dynamic price to be paid by a caller. This SDBDP scheme is integrated with a load-based joint call admission control (JCAC) algorithm for admitting incoming service requests in to the least utilized radio access technology (RAT). The load-based JCAC algorithm achieves uniform traffic distribution in the heterogeneous wireless network (HWN). To test the SDBDP scheme, we have developed an analytical model based on M/M/m/m queuing model. New or handoff service requests, arriving when all the RATs in the HWN are fully utilized, lead to call blocking for new calls and call dropping for handoff calls. The call blocking probability, call dropping probability and percentage MWN utilization are used as the performance metrics in evaluating the SDBDP scheme. An exponential demand model is used to approximate the users' response to the presented dynamic price. The exponential demand model captures both the price elasticity of demand and the demand shift constant for different users. The matrix laboratory (MATLAB) tool has been used to carry out the numerical simulations. An evaluation scenario consisting of four groups of co-located cells each with three RATs is used. Both SDP and the developed SDBDP schemes have been subjected under the evaluation scenario. Simulation results show that the developed SDBDP scheme reduces both the new call blocking and handoff call dropping probabilities during the peak hours, for all callercallee distributions. On the other hand, the current SDP scheme only reduces new call blocking and handoff call dropping probabilities only under some caller –callee distributions (When the callers were the majority in the HWN). Also, the SDBDP scheme increases the percentage MWN utilization during the off-peak for all the caller-callee distributions in the HWN. On the other hand, the SDP scheme is found to increase the percentage MWN utilization only when the distribution of callers is higher than that of callees in the HWN. From analyzing the simulations results, we conclude that the SDBDP scheme achieves better congestion control and MWN resource utilization than the existing SDP schemes, under arbitrary caller-callee distribution. 2017-01-31T07:56:51Z 2017-01-31T07:56:51Z 2016 Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/23743 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Mutungi, Jeremiah Nzioka A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| thesis_degree_str | Master's |
| title | A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| title_full | A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| title_fullStr | A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| title_full_unstemmed | A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| title_short | A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| title_sort | source destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/23743 |
| work_keys_str_mv | AT mutungijeremiahnzioka asourcedestinationbaseddynamicpricingschemetooptimizeresourceutilizationinheterogeneouswirelessnetworks AT mutungijeremiahnzioka sourcedestinationbaseddynamicpricingschemetooptimizeresourceutilizationinheterogeneouswirelessnetworks |