Wireless Technologies for Mobile Computing and Commerce

Mobile Computing ◽

10.4018/978-1-60566-054-7.ch097 ◽

2009 ◽

pp. 1175-1182

Author(s):

David Wright

Keyword(s):

Mobile Computing ◽

New Technologies ◽

Base Stations ◽

Wifi Networks ◽

Municipal Governments ◽

Wireless Technologies ◽

Community Associations ◽

Data Rates ◽

Business Analysis ◽

British Telecom

At the time of writing (1Q06) most countries have a small number (2-6) of major cellular operators offering competing 2.5G and 3G cellular services. In addition, there is a much larger number of operators of WiFi networks. In some cases, a major cellular operator, for example, Deutsche Telekomm and British Telecom, also offers a WiFi service. In other cases, WiFi services are provided by a proliferation of smaller network operators, such as restaurants, laundromats, airports, railways, community associations and municipal governments. Many organizations offer WiFi free of charge as a hospitality service, for example, restaurants. Cellular services offer ubiquitous, low data rate communications for mobile computing and commerce, whereas WiFi offers higher data rates, but less ubiquitous coverage, with limitations on mobility due to business as opposed to technology reasons. Emerging networks for mobile computing and commerce include WiMAX and WiMobile (Wright, 2006), which offer higher data rates, lower costs and city-wide coverage with handoff of calls among multiple base stations. These new technologies may be deployed by the organizations that currently deploy cellular and WiFi networks, and also may give rise to a new group of competitive wireless network operators. This article identifies the capabilities needed for mobile computing and commerce and assesses their technology and business implications. It identifies developments in the wireless networks that can be used for mobile computing and commerce, together with the services that can be provided over such networks. It provides a business analysis indicating which network operators can profitably deploy new networks, and which network operators need to establish business and technology links with each other so as to better serve their customers. The resulting range of next generation service, technologies and network operators available for mobile computing and commerce is identified.

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Wireless Technologies for Mobile Computing and Commerce

Selected Readings on Electronic Commerce Technologies ◽

10.4018/978-1-60566-096-7.ch012 ◽

2009 ◽

pp. 173-179

Author(s):

David Wright

Keyword(s):

Mobile Computing ◽

New Technologies ◽

Base Stations ◽

Wifi Networks ◽

Municipal Governments ◽

Wireless Technologies ◽

Community Associations ◽

Data Rates ◽

Business Analysis ◽

British Telecom

At the time of writing (1Q06) most countries have a small number (2-6) of major cellular operators offering competing 2.5G and 3G cellular services. In addition, there is a much larger number of operators of WiFi networks. In some cases, a major cellular operator, for example, Deutsche Telekomm and British Telecom, also offers a WiFi service. In other cases, WiFi services are provided by a proliferation of smaller network operators, such as restaurants, laundromats, airports, railways, community associations and municipal governments. Many organizations offer WiFi free of charge as a hospitality service, for example, restaurants. Cellular services offer ubiquitous, low data rate communications for mobile computing and commerce, whereas WiFi offers higher data rates, but less ubiquitous coverage, with limitations on mobility due to business as opposed to technology reasons. Emerging networks for mobile computing and commerce include WiMAX and WiMobile (Wright, 2006), which offer higher data rates, lower costs and city-wide coverage with handoff of calls among multiple base stations. These new technologies may be deployed by the organizations that currently deploy cellular and WiFi networks, and also may give rise to a new group of competitive wireless network operators. This article identifies the capabilities needed for mobile computing and commerce and assesses their technology and business implications. It identifies developments in the wireless networks that can be used for mobile computing and commerce, together with the services that can be provided over such networks. It provides a business analysis indicating which network operators can profitably deploy new networks, and which network operators need to establish business and technology links with each other so as to better serve their customers. The resulting range of next generation service, technologies and network operators available for mobile computing and commerce is identified.

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Handoff Management in Next Generation Wireless Networks

Networking and Telecommunications ◽

10.4018/978-1-60566-986-1.ch115 ◽

2010 ◽

pp. 1790-1811

Author(s):

Nidal Nasser ◽

Tarek Bejaoui

Keyword(s):

Wireless Networks ◽

Wireless Network ◽

Heterogeneous Wireless Networks ◽

User Preferences ◽

Fourth Generation ◽

Vertical Handoff ◽

Next Generation ◽

Wireless Technologies ◽

Handoff Management ◽

4G Wireless

Major research challenges in the next generation of wireless networks include the provisioning of worldwide seamless mobility across heterogeneous wireless networks, the improvement of end-to-end Quality of Service (QoS), supporting multmedia services over wide area and enabling users to specify their personal preferences. The integration and interoperability of this multitude of available networks will lead to the emergence of the fourth generation (4G) of wireless technologies. 4G wireless technologies have the potential to provide these features and many more, which at the end will change the way we use mobile devices and provide a wide variety of new applications. However, such technology does not come without its challenges. One of these challenges is the user’s ability to control and manage handoffs across heterogeneous wireless networks. This chapter proposes a solution to this problem using Artificial Neural Networks (ANNs). The proposed method is capable of distinguishing the best existing wireless network that matches predefined user preferences set on a mobile device when performing a vertical handoff. The overall performance of the proposed method shows 87.0 % success rate in finding the best available wireless network.

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Mobile computing in next generation wireless networks

Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications - DIALM '99 ◽

10.1145/313239.313277 ◽

1999 ◽

Cited By ~ 3

Author(s):

Prathima Agrawal ◽

David Famolari

Keyword(s):

Wireless Networks ◽

Mobile Computing ◽

Next Generation ◽

Next Generation Wireless Networks

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Handoff Management in Next Generation Wireless Networks

Handbook of Research on Wireless Multimedia ◽

10.4018/978-1-59904-820-8.ch003 ◽

2010 ◽

pp. 55-76

Author(s):

Nidal Nasser ◽

Tarek Bejaoui

Keyword(s):

Wireless Networks ◽

Wireless Network ◽

Heterogeneous Wireless Networks ◽

User Preferences ◽

Fourth Generation ◽

Vertical Handoff ◽

Next Generation ◽

Wireless Technologies ◽

Handoff Management ◽

4G Wireless

Major research challenges in the next generation of wireless networks include the provisioning of worldwide seamless mobility across heterogeneous wireless networks, the improvement of end-to-end Quality of Service (QoS), supporting multmedia services over wide area and enabling users to specify their personal preferences. The integration and interoperability of this multitude of available networks will lead to the emergence of the fourth generation (4G) of wireless technologies. 4G wireless technologies have the potential to provide these features and many more, which at the end will change the way we use mobile devices and provide a wide variety of new applications. However, such technology does not come without its challenges. One of these challenges is the user’s ability to control and manage handoffs across heterogeneous wireless networks. This chapter proposes a solution to this problem using Artificial Neural Networks (ANNs). The proposed method is capable of distinguishing the best existing wireless network that matches predefined user preferences set on a mobile device when performing a vertical handoff. The overall performance of the proposed method shows 87.0 % success rate in finding the best available wireless network.

Download Full-text