Congestion control in multi-serviced heterogeneous wireless networks using dynamic pricing

Includes bibliographical references.Service providers, (or operators) employ pricing schemes to help provide desired QoS to subscribers and to maintain profitability among competitors. An economically efficient pricing scheme, which will seamlessly integrate users’ preferences as well as service providers’ preferences, is therefore needed. Else, pricing schemes can be viewed as promoting social unfairness in the dynamically priced network. However, earlier investigations have shown that the existing dynamic pricing schemes do not consider the users’ willingness to pay (WTP) before the price of services is determined. WTP is the amount a user is willing to pay based on the worth attached to the service requested. There are different WTP levels for different subscribers due to the differences in the value attached to the services requested and demographics. This research has addressed congestion control in the heterogeneous wireless network (HWN) by developing a dynamic pricing scheme that efficiently incentivises users to utilize radio resources. The proposed Collaborative Dynamic Pricing Scheme (CDPS), which identifies the users and operators’ preference in determining the price of services, uses an intelligent approach for controlling congestion and enhancing both the users’ and operators’ utility. Thus, the CDPS addresses the congestion problem by firstly obtaining the users WTP from users’ historical response to price changes and incorporating the WTP factor to evaluate the service price. Secondly, it uses a reinforcement learning technique to illustrate how a price policy can be obtained for the enhancement of both users and operators’ utility, as total utility reward obtained increases towards a defined ‘goal state’

Analysis of a pricing method for elastic services with guaranteed GoS

Service Providers (SPs), which offer services based on elastic reservations with a guaranteed Grade of Service (GoS), should know how to price these services and how to quantify the benefits in different scenarios. This paper analyzes a method for evaluating the price of a service based on elastic reservations with a guaranteed Grade of Service. The method works as follows: First, the SP determines the requirements of the service that wants to offer; Second, the SP evaluates the average rate of the accepted elastic reservations of the service with a guaranteed GoS; Third, the SP calculates the price that guarantees the GoS with an aggregate demand function that depends on a demand modulation factor of the elastic reservations that is the mean reserved bandwidth, Bres; and Finally, the SP obtains the optimum value of the elasticity of the reservations that gives the maximum revenue, and the required access bandwidth in this case. The paper not only applies the method to a class i of elastic reservations when a linear-based demand and a revenue function are selected, but it also analyzes the influence of each one of the considered parameters. This method could be extended to the case of multiple classes of independent and guaranteed elastic services, applying the method to each service with its estimated demand and revenue functions.Peer ReviewedPostprint (published version

Oligopolies in private spectrum commons: analysis and regulatory implications

In an effort to make more spectrum available, recent initiatives by the FCC let mobile providers offer spot service of their licensed spectrum to secondary users, hence paving the way to dynamic secondary spectrum markets. This dissertation investigates secondary spectrum markets under different regulatory regimes by identifying profitability conditions and possible competitive outcomes in an oligopoly model. We consider pricing in a market where multiple providers compete for secondary demand. First, we analyze the market outcomes when providers adopt a coordinated access policy, where, besides pricing, a provider can elect to apply admission control on secondary users based on the state of its network. We next consider a competition when providers implement an uncoordinated access policy (i.e., no admission control). Through our analysis, we identify profitability conditions and fundamental price thresholds, including break-even and market sharing prices. We prove that regardless of the specific form of the secondary demand function, competition under coordinated access always leads to a price war outcome. In contrast, under uncoordinated access, market sharing becomes a viable market outcome if the intervals of prices for which the providers are willing to share the market overlap. We then turn our attention to how a network provider use carrier (spectrum) aggregation in order to lower its break-even price and gain an edge over its competition. To this end, we determine the optimal (minimum) level of carrier aggregation that a smaller provider needs. Under a quality-driven (QD) regime, we establish an efficient way of numerically calculating the optimal carrier aggregation and derive scaling laws. We extend the results to delay-related metrics and show their applications to profitable pricing in secondary spectrum markets. Finally, we consider the problem of profitability over a spatial topology, where identifying system behavior suffers from the curse of dimensionality. Hence, we propose an approximation model that captures system behavior to the first-order and provide an expression to calculate the break-even price at each network location and provide simulation results for accuracy comparison. All of our results hold for general forms of demand, thus avoid restricting assumptions of customer preferences and the valuation of the spectrum

Efficient joint call admission control and bandwidth management schemes for QoS provisioning in heterogeneous wireless networks

Includes abstract.Includes bibliographical references (leaves 150-157).Next generation wireless network (NGWN) will be heterogeneous where different radio access technologies (RATs) coexist. This coexistence of different RATs necessitates joint radio resource management (JRRM) for enhanced QoS provisioning and efficient radio resource utilization. Joint call admission control (JCAC) algorithm is one of the joint radio resource management algorithms. The basic functions of a JCAC algorithm are to decide whether or not an incoming call can be accepted into a heterogeneous wireless network, and to determine which of the available RATs is most suitable to admit the incoming call. The objective of a JCAC algorithm is to guarantee the QoS requirements of all accepted calls and at the same time make the best use of the available radio resources. Traditional call admission control algorithms designed for homogeneous wireless networks do not provide a single solution to address the heterogeneous architecture, which characterizes NGWN. Consequently, there is need to develop JCAC algorithms for heterogeneous wireless networks. The thesis proposes three JCAC schemes for improving QoS and radio resource utilization, which are of primary concerns, in heterogeneous wireless networks. The first scheme combines adaptive bandwidth management and joint call admission control. The objectives of the first scheme are to enhance average system utilization, guarantee QoS requirements of all accepted calls, and reduce new call blocking probability and handoff call dropping probability in heterogeneous wireless networks. The scheme consists of three components namely: joint call admission controller, bandwidth reservation unit, and bandwidth adaptation unit. Using Markov decision process, an analytical model is developed to evaluate the performance of the proposed scheme considering three performance metrics, which are new call blocking probability, handoff call dropping probability, and system utilization. Numerical results show that the proposed scheme improves system utilization and reduces both new call blocking probability and handoff call dropping probability. The second proposed JCAC scheme minimizes call blocking probability by determining the optimal call allocation policy among the available RATs. The scheme measures the arrival rates of different classes of calls into the heterogeneous wireless network. Using linear programming technique, the JCAC scheme determines the call allocation policy that minimizes call-blocking probability in the heterogeneous network. Numerical results show that the proposed scheme reduces call-blocking probability in the heterogeneous wireless network

Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks

Abstract—We propose to combine social trust derived from social networks with quality-of-service (QoS) trust derived from communication networks to obtain a composite trust metric as a basis for evaluating trust of mobile nodes in mobile ad hoc network (MANET) environments. We develop a novel modelbased approach to identify the best protocol setting under which trust bias is minimized, that is, the peer-to-peer subjective trust as a result of executing our distributed trust management protocol is close to ground truth status over a wide range of operational and environment conditions with high resiliency to malicious attacks and misbehaving nodes. Keywords—trust management; mobile ad hoc networks; QoS trust; social trust; trust bias minimization. I

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization