Stefan Michaelis

Comparison of User Mobility Pattern Prediction Algorithms to increase Handover Trigger Accuracy

The estimation of correct triggers for handover in cellular networks belongs to the critical tasks for accurate network operation. The importance of seamless handover even rises according to the increasing number of available radio access technologies, demanding for a reliable vertical handover. To aid the handover process, mobility prediction technologies gain interest and provide the possibility to prepare for handover in advance. The approaches presented here feature prediction of macro-mobility as an additional measure to aid handover decisions. The prediction is based on statistical data gained from the observation of movement across multiple cells. One of the main features lies in a generic user centric calculation of the most likely next hop during user movement, compared to network specific technological methods

Network-centric Middleware for Service Oriented Architectures across Heterogeneous Embedded Systems

The increasing ubiquity of mobile embedded systems has been matched by the evolution of a variety of wireless network standards and technologies. The major constraints of wireless embedded systems are limitations of communication bandwidth, processing capabilities, and battery power. Remote wireless embedded systems often act as sensors, which provide data to a certain community. The exchange of data is nowadays usually realized through Web services. For standard Web services an XML parser is required, which demands a lot of processing power whereas embedded devices with their resource constraints provide only limited processing capabilities. Another drawback of standard Web services is the huge communication overhead due to the use of human readable XML. On the other hand using standard Web service technology enables service developers to easily integrate new embedded devices to their network or to the Internet. This paper reports on the on-going work of the key European research project MORE, which brings the embedded system world together with the Web services world. MORE introduces a new connector concept easing the handling of heterogeneous communication channels and muSOA for reducing the message size and processing demands for parsing XML messages.

A comprehensive mobility management solution for handling peak load in cellular network scenarios

First responders are suffering from insufficient information about the incident during alerting and operations at the scene itself. Particularly at major incident operations detailed and up-to-date multimedia information are indispensable and have to be provided as fast and reliable as possible to the rescue forces. Thus, challenging requirements on the mobile communication system like traffic prioritization, seamless handover and everywhere connectivity arise from this use case. In this paper we present a holistic approach for a suitable heterogeneous communication architecture considering the complete mobility management process that consists of mobility modeling, handover trigger algorithms and IP-based handover protocols applied on a big public event at a stadium.

In-cabin localization solution for optimizing manufacturing an d maintenance proces ses for civil aircrafts

This indoor localization solution enables optimization of manufacturing and maintenance processes of civil aircrafts. The use cases include localization of fixed entities like life vests, passenger service units, and seats and mobile entities like flight attendance panels and devices of maintenance workers. Following these use cases, the solution approach features the combination of fingerprinting approaches using Support Vector Machines and distance-based approaches like Trilateration and Weighted Centroid. The proposal has been intensively studied in an Airbus A340 cabin mock-up model by measurement campaigns with a real system deployment.

Distributed pervasive services using group service communication supporting body area networks

Body Area Network (BAN) provide critical data in healthcare monitoring environments, where such monitoring can be performed in a ubiquitous manner using various miniature device technologies. However, a key requirement in supporting the full capacity of a BAN is an efficient distribution, processing and application of the acquired data. The architecture and applications which capitalize on the huge potential of this data, provide significant added value to BANs. This paper proposes an architecture which is service oriented and integrates the data produced by BANs into a healthcare environment, supporting remote interactions between medical officers to maximise patient care. The dynamic interaction of distributed services in this diverse environment is a key ingredient in the way technology can enhance healthcare. The architecture defines group services which facilitate the control of the dynamic behaviour of services within this heterogeneous environment.

Balancing High-Load Scenarios with Next Cell Predictions and Mobility Pattern Recognition

Knowing where a mobile user will be next can deliver a tremendous increase in network performance under high load, as this knowledge enables pro-active load balancing. To derive this information, sequences of traversed cells are fed into pattern detection algorithms. After the training phase the learned model predicts each users next cell. Even for complex scenarios, the prediction accuracy can exceed 90%. Predictions are used to rearrange mobile connections in a simulated high- load scenario centered around an event at a soccer stadium. To prevent call drops for mobile users targeting the stadium, apropriate resources in the predicted next cell are reserved. The results exceed 20% in improvements for throughput and call drop rates, enabling the network to bear a much higher load before stalling.

Verkehrslastprognose durch Wissensentdeckung oder Warum Telefonieren immer noch zu teuer ist

SummaryThe highly competitive telecommunication market demands for efficient operation of the underlying networks. The effective maintenance rises the need for accurate prognosis of prospective network loads. In this article the basic concepts for network management and traffic prognosis using machine learning or knowledge discovery techniques are introduced. The aim is to motivate the solution of similar tasks and to show limits and feasibilities.

Macromobility prediction for high-priority resource reservation in wireless networks

Efficient management of mobile network resources is a critical task for successful operation. Giving higher priority and quality of service to applications with a high return on invest value, demands for intelligent distribution of bit rates and radio access. The research approach proposed here is based on the fact, that users cannot move freely, but are restricted to streets or rails in position, direction and speed. Following the geographical topology while in motion some locations generate a unique signature by forcing the user to traverse similar sequences of base stations. The signatures can be revealed by applying pattern detection methods on the historical user movements, allowing to predict future positions of the user on a large time scale, especially to reserve resources for rescue workers. In this paper we discuss the effect of different attributes about the users movement for the prediction quality on different pattern detection algorithms in order to improve and accelerate the process of rescue missions. Further the availability of these attributes will be discussed for different scenarios and validated by traces from an actual large scale HSDPA/GSM network.

Dynamic group management as an enhancement to emergency healthcare using policies

Successful medical emergency preventative measures or actual emergency resolution is not entirely down to one individual, but more the result of the establishment and behaviour of a group of individuals and services. This is highly evident in the healthcare domain: the introduction of pervasive healthcare systems allows for the interconnection of various stake holders, such as patients, doctors, medical monitoring services, and the patientpsilas family. Communication within a group can be extremely useful to manage and resolve emergency situations, such as helping a patient affected by a life-threatening hypogylcemic condition. At the same time, it also requires new tools for managing these groups in an effective and secure way. However, as more specialist services become available the management of these groups is increasing in magnitude. This paper defines different group types and proposes a framework, which allows for the dynamic management of such groups using policies. The applicability of this generic framework for the purpose of pervasive healthcare applications is demonstrated by concrete examples and use cases.

Aspects of Switching System Analysis a Centuries Evolution

Summary Traffic Theory has accompanied the evolution from early switching systems to an omnipresent communication infrastructure through the last century. Targeting at the mathematical modelling of call attempts at first the main goal was the dimensioning of telephone infrastructure. Emerging new services, mobile communication environments and the integration of packet style communication links into by then well known switched circuit equipment has put new challenges to traffic theory. Still new interpretations and facets of the basic models are found and elaborated to make traffic theory useful for modern systems as the internet.