Special Issue "Managing Quality-of-Service and Security in Mobile Heterogeneous Environments"

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A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (15 December 2012)

Special Issue Editor

Guest Editor
Dr. Glenford Mapp (Website)

Department of Computer Communications, Hendon Campus, Middlesex University, The Burroughs, London NW4 4BT, UK
Phone: +44 208 411 6517
Interests: future mobile architectures; heterogeneous environments; Quality-of-Service; security; vertical handover

Special Issue Information

Dear Colleagues,

The development and deployment of several wireless networks mean that mobile devices will have several wireless interfaces including 3G, WLAN, WiMAX and LTE. This represents a significant development as users will want to be always connected from anywhere and at any time. This will be achieved using vertical handover techniques where connections will be seamlessly switched between available networks.

However, these heterogeneous environments raise many issues in terms of Quality-of-Service (QoS) and Security as different wireless networks may display huge disparities with regard to these two major network properties. These differences become serious problems in heterogeneous environments as mobile nodes need to quickly adapt while moving from one network to another.  This Special Issue looks at the design, development, implementation and evaluation of mechanisms to manage Quality-of-Service and Security in mobile heterogeneous environments.

Dr. Glenford Mapp
Guest Editor

Published Papers (3 papers)

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Research

Open AccessArticle Investigating the Tradeoffs between Power Consumption and Quality of Service in a Backbone Network
Future Internet 2013, 5(2), 268-281; doi:10.3390/fi5020268
Received: 8 February 2013 / Revised: 12 April 2013 / Accepted: 9 May 2013 / Published: 24 May 2013
Cited by 2 | PDF Full-text (727 KB) | HTML Full-text | XML Full-text
Abstract
Energy saving in networks has traditionally focussed on reducing battery consumption through smart wireless network design. Recently, researchers have turned their attention to the energy cost and carbon emissions of the backbone network that both fixed and mobile communications depend on, proposing [...] Read more.
Energy saving in networks has traditionally focussed on reducing battery consumption through smart wireless network design. Recently, researchers have turned their attention to the energy cost and carbon emissions of the backbone network that both fixed and mobile communications depend on, proposing primarily mechanisms that turn equipments OFF or put them into deep sleep. This is an effective way of saving energy, provided that the nodes can return to working condition quickly, but it introduces increased delays and packet losses that directly affect the quality of communication experienced by the users. Here we investigate the associated tradeoffs between power consumption and quality of service in backbone networks that employ deep sleep energy savings. We examine these tradeoffs by conducting experiments on a real PC-based network topology, where nodes are put into deep sleep at random times and intervals, resulting in a continuously changing network with reduced total power consumption. The average power consumption, the packet loss and the average delay of this network are examined with respect to the average value of the ON rate and the ON/OFF cycle of the nodes. Full article
Open AccessArticle QoS Self-Provisioning and Interference Management for Co-Channel Deployed 3G Femtocells
Future Internet 2013, 5(2), 168-189; doi:10.3390/fi5020168
Received: 21 February 2013 / Revised: 7 March 2013 / Accepted: 22 April 2013 / Published: 2 May 2013
PDF Full-text (622 KB) | HTML Full-text | XML Full-text
Abstract
A highly efficient self-provisioning interference management scheme is derived for 3G Home Node-Bs (HNB). The proposed scheme comprises self-adjustment of the HNB transmission parameters to meet the targeted QoS (quality of service) requirements in terms of downlink and uplink guaranteed minimum throughput [...] Read more.
A highly efficient self-provisioning interference management scheme is derived for 3G Home Node-Bs (HNB). The proposed scheme comprises self-adjustment of the HNB transmission parameters to meet the targeted QoS (quality of service) requirements in terms of downlink and uplink guaranteed minimum throughput and coverage. This objective is achieved by means of an autonomous HNB solution, where the transmit power of pilot and data are adjusted separately, while also controlling the uplink interference pollution towards the macro-layer. The proposed scheme is evaluated by means of extensive system level simulations and the results show significant performance improvements in terms of user throughput outage probability, power efficiency, femtocell coverage, and impact on macro-layer performance as compared to prior art baseline techniques. The paper is concluded by also showing corresponding measurements from live 3G high-speed packet access (HSPA) HNB field-trials, confirming the validity of major simulation results and assumptions. Full article
Figures

Open AccessArticle Energy–QoS Trade-Offs in Mobile Service Selection
Future Internet 2013, 5(2), 128-139; doi:10.3390/fi5020128
Received: 28 February 2013 / Revised: 5 March 2013 / Accepted: 12 April 2013 / Published: 19 April 2013
Cited by 6 | PDF Full-text (369 KB) | HTML Full-text | XML Full-text
Abstract
An attractive advantage of mobile networks is that their users can gain easy access to different services. In some cases, equivalent services could be fulfilled by different providers, which brings the question of how to rationally select the best provider among all [...] Read more.
An attractive advantage of mobile networks is that their users can gain easy access to different services. In some cases, equivalent services could be fulfilled by different providers, which brings the question of how to rationally select the best provider among all possibilities. In this paper, we investigate an answer to this question from both quality-of-service (QoS) and energy perspectives by formulating an optimisation problem. We illustrate the theoretical results with examples from experimental measurements of the resulting energy and performance. Full article

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