Mobility Prediction for Multimedia Services

Mobility Prediction for Multimedia Services

Damien Charlet (INRIA-Rocquencourt (ARLES Project), France), Frédéric Lassabe (University of Franche-Comté, France), Philippe Canalda (University of Franche-Comté, France), Pascal Chatonnay (University of Franche-Comté, France) and François Spies (University of Franche-Comté, France)
Copyright: © 2009 |Pages: 14
DOI: 10.4018/978-1-60566-046-2.ch066
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Advances in technology have enabled a proliferation of mobile devices and a broad spectrum of novel and out breaking solutions for new applications and services. In the present, more and more people and companies are demanding mobile access to multimedia services such as real-time rich media. Today, it is necessary to be able to predict adaptation behaviour which concerns and addresses not only the mobile usage or the infrastructure availability, but the service quality especially the continuity of service. Our chapter provides insight to new challenges of mobile multimedia services and applications: Wifi indoor positioning system adapted to heterogeneous building, static and learning mobility prediction, predictive handover policy for multimedia cache management, mobile multimedia guide (such as museum), and network scalability.
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The rapid deployment and growth of multimedia applications are increasing with the appearance of new mobile services and new usages. Nowadays, taking advantage of the arrival of large bandwidth of wireless networks, it is becoming more feasible to stream numerous rich media flows towards mobile and terminal devices. However, some bottlenecks subsist when addressing, firstly, the heterogeneity of Wifi covered territories and secondly the intrinsic rich media constraints. We compare mobility to, first of all, a continuous move within a geographical space, and second a discrete space on a logical scale of the diffusion’s network (from access point to access point).

This chapter deals with applications handling large size and continuous rich media communication (i.e., audio or video media). Continuous media require the installation of a specific infrastructure of diffusion guaranteeing the delivery periods. We are interested in mobiles implemented within a space provided with multiple access points, with a more or less homogeneous space cover. In such context, it is important the infrastructure reacts rapidly, or use preventive measures during the changes of access point.

In this chapter, we do not consider the dynamic flow adaptation but rather, we consider already optimized flows dedicated to mobile devices. Thus, whatever the device nature is (pda, tablet pc, etc.), we assume there is a suitable flow adapted to each target. The reader interested in flow adaptation may refer to (Bourgeois, Mory, & Spies, 2003). (See Figure 1)

Figure 1.

Synthetic schema of GUINUMO’s platform

To illustrate our purpose, we use GUINUMO, a mobile numerical guide. Such guide demonstrates the accuracy and pertinence of retrieving and making use of both the visual or audio information, and the localization of the pervasive device, during the time-visit of scenarized museums. Within this framework, the media are suited to fit the specific device.

In the sequel, first of all we present the techniques of localization of the devices connected by hertzian way. We further investigate the trilateration technique and evaluate the efficiency of various methods according to several conditions of implementation.

In order to set up a preventive treatment of mobility we show that it is necessary to determine, at least statistically, the future position of a mobile. Then, we describe the methods allowing predicting, in the short run, the position of a mobile. We detail how, thanks to methods of training, it is possible to refine this prediction. In the second part of this chapter, we introduce the concept of cache, as a necessary element in the chain of continuous media diffusion. Caches make it possible to ensure the continuity and the extensibility of the diffusion’s infrastructure. We start off by describing the standard methods of managements and co-operation of the caches for continuous media. We proceed by explaining the mechanisms required to manage the change of access point: handoff. Then we detail how preventive methods allow optimizing the continuity of flows diffusion. We also present how to integrate these mechanisms in a platform of diffusion and reception (GUINUMO). We describe use-cases of this device. Finally, we conclude with future trends about preventive treatment of mobility. We specify how the coming standards will allow optimizing the handoff and positioning determination mechanisms.

Key Terms in this Chapter

Service Continuity: Property of a service over a mobile network. When continue, a service is not interrupted by changes in its logical position (change of AP / BTS). For example in the GSM standard, as long as you stay in covered areas, phone conversations are not interrupted when you change your BTS.

Streaming: Technique of transfer in a continuous flow to allow the display of the media while downloading.

Removal Policy: Management algorithm of caches, decides which stored documents should be deleted to make room for new and more popular documents.

Ad Hoc Mode: Every client can talk to each other on a peer-to-peer basis.

Start Latency: Time elapsed between the moment where a user requests of a document and the time it is displayed on its peripheral.

Sibling: Exchange of data between two caches.

Cooperation Policy: Used between distributed caches to cooperate and share data.

Mobility: The action to move. We are interested in particular in the logical mobility (change of network, BTS, etc.) triggered by the geographical move (the action of changing physical coordinates in space).

Handoff: Name of the mechanism which takes place when a user is roaming.

Roaming: Action of a human moving from one zone to another.

Mobile Terminal: Every apparatus light-enough to be humanly transported and with embedded computation power, like laptops, PDA, new generation mobile phones.

Prefetch: Inserting documents into a cache in the hope that they are going to be requested in a near future to reduce start latency for the user. Contrarily to normal insertion, it is not triggered by clients.

Insertion Policy: Algorithm of caches, decides which documents should be stored.

Video Cache: A cache with specific policies, optimized for the delivery of video data.

Cache: A cache gathers the functions of a server and of client. It takes place between them and can store and deliver popular documents. Being near the client, it helps resolve the problems of bottlenecks and increase reactivity.

Signal Strength: It is the power of the signal measured.

Admission Policy: Algorithm used when a new client wants to fetch data from a cache to decide if the cache has sufficient capabilities left to serve him.

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