Extracting a Mobility Model from Real User Traces

Understanding user mobility is critical for simulations of mobile devices in a wireless network, but current mobility models often do not reflect real user movements. In this paper, we provide a foundation for such work by exploring mobility characteristics in traces of mobile users. We present a method to estimate the physical location of users from a large trace of mobile devices associating with access points in a wireless network. Using this method, we extracted tracks of always-on Wi-Fi devices from a 13-month trace. We discovered that the speed and pause time each follow a log-normal distribution and that the direction of movements closely reflects the direction of roads and walkways. Based on the extracted mobility characteristics, we developed a mobility model, focusing on movements among popular regions. Our validation shows that synthetic tracks match real tracks with a median relative error of 17%

Media independent handovers : network selection for mobile IP nodes in heterogeneous wireless networks

Includes abstract.Includes bibliographical references (p. 79-82).In Next Generation Networks (NGN), also known as 4G, Beyond 3G, Converged, Integrated and Interworked Network, user node mobility in wireless and wired environments will seamlessly cross disparate network boundaries. The effort to offer ubiquitous computing, providing access to services anywhere and anytime, strongly encourages the ability to roam across the different existing and future networks. Literature shows investigation of concepts such as Always Best Connected (ABC) when heterogeneous networks co-exist , which will work or compete with other schemes like Home Network Default (HND), Compatibility and Network Operator Agreements (CNOA) to guide network selection or access . With the variety of available networks, the mobile node may be faced with having to decide which network to connect to. We concentrate on the network selection aspects of these envisaged mobile, overlay and integrated environment in heterogeneous networks. The standard developments by the IEEE802.21 Working group and the IETF Networking group form the base of our approach that seeks to see mobility across heterogeneous networks a reality. We propose an IEEE802.21 Media Independent Handover Function (MIHF) based network discovery and network selection, leading to a handover. The selection may be further assisted by an MIHF capable Broker Node that is Third party to the Network Providers to provide a central yet distributed database of the available networks as encountered by the Mobile Node, to cater for Nodes with no prior knowledge of networks and software repository. A Mobile Node (MN) in our solution uses 802.21 communication messages to obtain information about foreign networks encountered before selecting the networks to connect to. Our evaluation through simulations, shows that network selection in heterogeneous wireless networks environment for the appropriately equipped devices is greatly enhanced by the use of the Media Independent Handover Protocol. In scenarios where the mobile node has no prior knowledge of the encountered different network architectures, the use of a Broker node can, for an optimal number of available networks also greatly enhance the mobile node’s network selection by reducing the delay associated and the packet losses incurred

Multi-Dimensional-Personalization in mobile contexts

During the dot com era the word "personalisation” was a hot buzzword. With the fall of the dot com companies the topic has lost momentum. As the killer application for UMTS or the mobile internet has yet to be identified, the concept of Multi-Dimensional-Personalisation (MDP) could be a candidate. Using this approach, a recommendation of mobile advertisement or marketing (i.e., recommendations or notifications), online content, as well as offline events, can be offered to the user based on their known interests and current location. Instead of having to request or pull this information, the new service concept would proactively provide the information and services – with the consequence that the right information or service could therefore be offered at the right place, at the right time. The growing availability of "Location-based Services“ for mobile phones is a new target for the use of personalisation. "Location-based Services“ are information, for example, about restaurants, hotels or shopping malls with offers which are in close range / short distance to the user. The lack of acceptance for such services in the past is based on the fact that early implementations required the user to pull the information from the service provider. A more promising approach is to actively push information to the user. This information must be from interest to the user and has to reach the user at the right time and at the right place. This raises new requirements on personalisation which will go far beyond present requirements. It will reach out from personalisation based only on the interest of the user. Besides the interest, the enhanced personalisation has to cover the location and movement patterns, the usage and the past, present and future schedule of the user. This new personalisation paradigm has to protect the user’s privacy so that an approach supporting anonymous recommendations through an extended "Chinese Wall“ will be described

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse