130 research outputs found
The effect of competition among brokers on the quality and price of differentiated internet services
Price war, as an important factor in undercutting competitors and attracting customers, has spurred considerable work that analyzes such conflict situation. However, in most of these studies, quality of service (QoS), as an important decision-making criterion, has been neglected. Furthermore, with the rise of service-oriented architectures, where players may offer different levels of QoS for different prices, more studies are needed to examine the interaction among players within the service hierarchy. In this paper, we present a new approach to modeling price competition in (virtualized) service-oriented architectures, where there are multiple service levels. In our model, brokers, as the intermediaries between end-users and service providers, offer different QoS by adapting the service that they obtain from lower-level providers so as to match the demands of their clients to the services of providers. To maximize profit, players, i.e. providers and brokers, at each level compete in a Bertrand game while they offer different QoS. To maintain an oligopoly market, we then describe underlying dynamics which lead to a Bertrand game with price constraints at the providers' level. Numerical simulations demonstrate the behavior of brokers and providers and the effect of price competition on their market shares.This work has been partly supported by National Science Foundation awards: CNS-0963974, CNS-1346688, CNS-1536090 and CNS-1647084
The effect of (non-)competing brokers on the quality and price of differentiated internet services
Price war, as an important factor in undercutting competitors and attracting customers, has spurred considerable work that analyzes such conflict situation. However, in most of these studies, quality of service (QoS), as an important decision-making criterion, has been neglected. Furthermore, with the rise of service-oriented architectures, where players may offer different levels of QoS for different prices, more studies are needed to examine the interaction among players within the service hierarchy. In this paper, we present a new approach to modeling price competition in (virtualized) service-oriented architectures, where there are multiple service levels. In our model, brokers, as intermediaries between end-users and service providers, offer different QoS by adapting the service that they obtain from lower-level providers so as to match the demands of their clients to the services of providers. To maximize profit, players, i.e. providers and brokers, at each level compete in a Bertrand game while they offer different QoS. To maintain an oligopoly market, we then describe underlying dynamics which lead to a Bertrand game with price constraints at the providers’ level. We also study cooperation among a subset of brokers. Numerical simulations demonstrate the behavior of brokers and providers and the effect of price competition on their market shares.Accepted manuscrip
Multi-attribute demand characterization and layered service pricing
As cloud computing gains popularity, understanding the pattern and structure of its workload is increasingly important in order to drive effective resource allocation and pricing decisions. In the cloud model, virtual machines (VMs), each consisting of a bundle of computing resources, are presented to users for purchase. Thus, the cloud context requires multi-attribute models of demand. While most of the available studies have focused on one specific attribute of a virtual request such as CPU or memory, to the best of our knowledge there is no work on the joint distribution of resource usage. In the first part of this dissertation, we develop a joint distribution model that captures the relationship among multiple resources by fitting the marginal distribution of each resource type as well as the non-linear structure of their correlation via a copula distribution. We validate our models using a public data set of Google data center usage.
Constructing the demand model is essential for provisioning revenue-optimal configuration for VMs or quality of service (QoS) offered by a provider. In the second part of the dissertation, we turn to the service pricing problem in a multi-provider setting: given service configurations (qualities) offered by different providers, choose a proper price for each offered service to undercut competitors and attract customers. With the rise of layered service-oriented architectures there is a need for more advanced solutions that manage the interactions among service providers at multiple levels. Brokers, as the intermediaries between customers and lower-level providers, play a key role in improving the efficiency of service-oriented structures by matching the demands of customers to the services of providers. We analyze a layered market in which service brokers and service providers compete in a Bertrand game at different levels in an oligopoly market while they offer different QoS. We examine the interaction among players and the effect of price competition on their market shares. We also study the market with partial cooperation, where a subset of players optimizes their total revenue instead of maximizing their own profit independently. We analyze the impact of this cooperation on the market and customers' social welfare
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Network Game Theory Models of Services and Quality Competition with Applications to Future Internet Architectures and Supply Chains
The Internet has transformed the way in which we conduct business and perform economic and financial transactions. One key challenge of the Internet is the inefficiency of the mechanisms by which technology is deployed and the business and economic models surrounding these processes (Wolf et al. (2014)). Equilibrium models for the Internet generally assume basic economic relationships. However, in new paradigms for the Internet and in supply chain networks, price is not the only factor; quality of service (QoS) is also of increasing importance.
Supply chains networks, which give us the means to manufacture products and deliver them to points of demand across the globe, are also under many pressures to offer differentiated products and services (Nagurney (2014)). It is well-known today that success is determined by how well the entire supply chain performs, rather than the performance of its individual entities.
This dissertation contributes to the analysis, design, and management of the future Internet and supply chain networks with a focus on price and quality competition in service-oriented networks.
Specifically, I focus on economic models for the Internet of the future by developing both a basic and a general network economic game theory model of a quality-based service-oriented Internet to study competition among service providers. To study and analyze the underlying dynamics of the various economic decision-makers, subsequently, I develop a dynamic network economic model of a service-oriented Internet with price and quality competition using projected dynamical systems theory. Then, to assess the prices for various contract durations at the demand markets, I consider a game theory model of a service-oriented Internet in which the network providers compete in usage service rates, quality levels, and duration-based contracts. Finally, I construct a model that captures the competition among manufacturers and freight service providers in a supply chain network. This model is the first one in the literature that handles both price and quality competition with multiple modes of shipment from both equilibrium and dynamic perspectives.
For each model, I derive the governing equilibrium conditions and provide the equivalent variational inequality formulations. In order to illustrate the modeling framework and the algorithm, I present computed solutions to several numerical examples for each model as well as sensitivity analysis results.
This dissertation is heavily based on the following papers: Saberi, Nagurney, and Wolf (2014), Nagurney et al. (2014a), Nagurney et al. (2015b), and Nagurney et al. (2015a) as well as additional results and conclusions
Dynamic Pricing of Applications in Cloud Marketplaces using Game Theory
The competitive nature of Cloud marketplaces as new concerns in delivery of
services makes the pricing policies a crucial task for firms. so that, pricing
strategies has recently attracted many researchers. Since game theory can
handle such competing well this concern is addressed by designing a normal form
game between providers in current research. A committee is considered in which
providers register for improving their competition based pricing policies. The
functionality of game theory is applied to design dynamic pricing policies. The
usage of the committee makes the game a complete information one, in which each
player is aware of every others payoff functions. The players enhance their
pricing policies to maximize their profits. The contribution of this paper is
the quantitative modeling of Cloud marketplaces in form of a game to provide
novel dynamic pricing strategies; the model is validated by proving the
existence and the uniqueness of Nash equilibrium of the game
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’
Secondary user pricing strategies in a cognitive radio environment
There has been a growing demand for spectrum availability due to inefficient management of the radio
frequency spectrum and underutilization of all spectrum bands. Spectrum has been managed with the
same approach for over the last decade and only recently due to the phenomenal growth in mobile and
broadband communications has attention been given to it. Intelligent communication systems such as
cognitive radio have been identified in assisting the need for the limited resource, wireless spectrum. If
spectrum trading becomes commercially successful, it can provide great economic and social benefits
for the service provider, primary and secondary users. In order to maintain viability of spectrum trading,
a pricing strategy is necessary for secondary users, it is also imperative to find a game theory model that
minimally impacts the primary users in terms of their service, however it should aid in decreasing the
cost to the primary users. Game theory along with economic theory is used to analyse the
relationships/cooperation between the users and service provider. This work contributes to the field of
dynamic spectrum access and aims to compare pricing strategies of secondary users in terms of the
revenue earned by the primary service providers as well as investigate the impact of regulations on said
pricing strategies. The pricing strategies modelled and simulated in MATLAB include the market-equilibrium pricing
strategy and the competitive pricing strategy. These two strategies are chosen as they are the most
relevant in South Africa. The two pricing strategies are compared in terms of advantages and
disadvantages as well the revenue earned by each of the primary services. The framework for testing is
provided along with the test cases. The influence of telecommunication regulations and policy on the
frameworks and results are discussed in detail as well as the impact of the telecommunication regulation
and policy in South Africa
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