A Dynamic Macroeconomic Model for the US Telecommunications Industry

Dynamic models have been used in most businesses serving different purposes. The increased changes of the Telecommunications environment have created a dynamic industry emerging new dynamic economic models. We investigated the Telecom industry by conducting macroeconomic and infrastructure analysis. However, this paper uses recent data from the Telecommunications industry to reveal the infrastructure trends and predict the US wireless growth. The analysis is focused on several factors such as the infrastructure described by the Teledensity, the employment and the Telecom revenues in comparison with the Gross Domestic Product (GDP). The purpose of this analysis is to understand the industry’s behavior during a specific period of time, 1984-2003, propose an appropriate economic dynamic model, wireless oriented that identifies the current driving forces and detects the impact of some critical events and trends.Dynamic Economic Model, Macroeconomic Analysis, Telecom Act, Teledensity

Flexible Investment Decisions in the Telecommunications Industry: Case Applications using Real Options

The telecommunications sector is one of the most innovative, high-growth, capitalintensive yet volatile sector of the economy. This research addresses critical concerns of how, when, and why an enterprise or a service provider should undertake new investments. The study investigates the power of flexibility in investment decision making process, by applying the real options methodology. Five case applications are studied: a) investment decisions in next generation wireless networks; b) investing in integrated wireless networks; c) migration to wireless broadband internet services; d) valuing deployment of Wi-Fi networks in enterprise markets; and e) valuing Hosted VOIP services for enterprise markets. The case studies are analyzed both qualitatively and quantitatively

On the Impact of Practical P2P Incentive Mechanisms on User Behavior

In this paper we report on the results of a large-scale measurement study of two popular peer-topeer systems, namely BitTorrent and eMule, that use practical and lightweight incentive mechanisms to encourage cooperation between users. We focus on identifying the strategic behavior of users in response to those incentive mechanisms. Our results illustrate a gap between what system designers and researchers expect from users in reaction to an incentive mechanism, and how users react to those incentives. In particular, we observe that the majority of BitTorrent users appear to cooperate well, despite the existence of known ways to tamper with the incentive mechanism, users engaging in behavior that could be regarded as cheating comprised only around 10% of BitTorrent’s population. That is, although we know that users can easily cheat, they actually do not currently appear to cheat at a large enough scale. In the eMule system, we identify several distinct classes of users based on their behavior. A large fraction of users appears to perceive cooperation as a good strategy, and openly share all the files they obtained. Other users engage in more subtle strategic choices, by actively optimizing the number and types of files they share in order to improve their standing in eMule’s waiting queues; they tend to remove files for which downloading is complete and keep a limited total volume of files shared

On the Impact of Practical P2P Incentive Mechanisms on User Behavior

In this paper we report on the results of a large-scale measurement study of two popular peer-topeer systems, namely BitTorrent and eMule, that use practical and lightweight incentive mechanisms to encourage cooperation between users. We focus on identifying the strategic behavior of users in response to those incentive mechanisms. Our results illustrate a gap between what system designers and researchers expect from users in reaction to an incentive mechanism, and how users react to those incentives. In particular, we observe that the majority of BitTorrent users appear to cooperate well, despite the existence of known ways to tamper with the incentive mechanism, users engaging in behavior that could be regarded as cheating comprised only around 10% of BitTorrent’s population. That is, although we know that users can easily cheat, they actually do not currently appear to cheat at a large enough scale. In the eMule system, we identify several distinct classes of users based on their behavior. A large fraction of users appears to perceive cooperation as a good strategy, and openly share all the files they obtained. Other users engage in more subtle strategic choices, by actively optimizing the number and types of files they share in order to improve their standing in eMule’s waiting queues; they tend to remove files for which downloading is complete and keep a limited total volume of files shared

IEEE 802.11 Inter-WLAN Mobility Control with Broadband Supported Distribution System Integrating WLAN and WAN

Abstract. The integration of wireless local area networks (WLANs) and the high speed wide area network (WAN) using ‘always on ’ broadband access that could provide an efficient and cost effective inter-WLAN mobility management requires the current WLAN internetworking protocol enhanced. The Inter Access Point Protocol (IAPP) defines methods for access point coordination over a distribution system to support WLAN interworking without any central intelligence to support mobility. The implementation of mobility management with any external central control in a distribution system, including broadband such as DSL, is not specified in any WLAN, including 802.11. This paper, first, presents an implementation of a distribution system with broadband DSL accessed central network control for IEEE 802.11 inter-WLAN mobility. Then the modification to the IAPP protocol messaging required for the broadband supported mobility management for inter-WLAN is presented. Preliminary simulation results demonstrating the effectiveness of the proposed distribution and its signaling are also provided. 1

Towards a Wi-Fi ecosystem: Technology integration and emerging service models

This paper outlines emerging business models of heterogeneous wireless networks that are mainly Wi-Fi centric. Wi-Fi networks can be integrated with the Internet and cellular infrastructures to offer innovative services (data and voice) to individuals and businesses. In the metro area network or a "hot city" type of coverage, an integration of WiMAX and Wi-Fi technologies will provide the most cost-effective solution of backhaul and access, for both voice and data services. In the cellular arena, as mobile operators look for new ways to connect, Wi-Fi can easily be integrated with the existing mobile data networks (2.5 G/3 G). An integrated offering that combines the mobility of cellular and the speed of Wi-Fi is an ideal mix for mobile broadband subscribers. This article also analyzes how Wi-Fi technology is being complementary to other wireless technologies, leading to an expansion of an organized Wi-Fi ecosystem. From an integration standpoint, this article shows the importance of Wi-Fi for cellular operators and also shows how Wi-Fi is crucial for WiMAX technology to evolve, till the mobile version of WiMAX becomes a reality. Finally, the paper describes why regulators and policy makers should seek suitable strategies to promote or encourage Wi-Fi as an alternative broadband access technology.Wi-Fi WiMAX Cellular Bluetooth VoWi-Fi Strategy Integration Service models

Migration to 3G wireless broadband internet and real options: The case of an operator in India

The paper focuses on third generation wireless technologies and on alternative technologies for wireless local area networks. The authors present the evolutionary migration path from second to third generation systems. Technological, economic and behavioral factors related to decision-making towards the migration are proposed. As an example, the paper studies the case of the national incumbent operator of India. It analyzes qualitatively the migration problem from the perspective of the operator, the equipment manufacturer and the users. For the quantitative analysis, real options are used to value the investment decisions. The analysis suggests that the initial (sunk) investment cost, the average revenue per user, the growth of the subscriber base and the volatility of the markets are the key factors in the investment process.3G GSM CDMA Wireless Broadband India UMTS India Wi-Fi Real options

Investment decisions in the wireless industry applying real options

The wireless industry is one of the most capital intensive high-technology industries. This paper applies real options techniques to estimate investments under uncertainty in two new ventures: (a) deferral of the expansion from 2.5G to 3G networks; and (b) expansion of a 2.5G network using Wi-Fi as an alternative technology. The cases are examined and analyzed both qualitatively and quantitatively, using realistic assumptions and parameters. Investment cost, number of subscribers, pricing of services, and risk are at the core of investment decision processing. In both cases, sensitivity analysis of the value of the (real) option considering the above key parameters was conducted, to extrapolate useful findings that should be taken into consideration by the decision makers in wireless companies.Wireless networks 3G GSM UMTS Wi-Fi Real options Investment decisions