Sophie Chabridon

Mobile databases: a selection of open issues and research directions

This paper reports on the main results of a specific action on mobile databases conducted by CNRS in France from October 2001 to December 2002. The objective of this action was to review the state of progress in mobile databases and identify major research directions for the French database community. Rather than provide a survey of all important issues in mobile databases, this paper gives an outline of the directions in which the action participants are now engaged, namely: copy synchronization in disconnected computing, mobile transactions, database embedded in ultra-light devices, data confidentiality, P2P dissemination models and middleware adaptability.

Disconnected operations in mobile environments

The execution of distributed applications involving mobile terminals and fixed servers connected by wireless links raises the need for handling network disconnections, both involuntary during unexpected connection breakdowns, and voluntary when the user wants to save money and energy. In this paper, we investigate how standard CORBA mechanisms (Objects By Value and Portable Interceptors) can be used for enhancing legacy CORBA-based distributed applications in order to support voluntary and involuntary disconnections. We show that the first mechanism can be used for handling easily voluntary disconnections by copying on the terminal all the data necessary for running the application in a disconnected mode. The second mechanism allows also to handle involuntary disconnections; a switch between connected mode and disconnected mode can be performed transparently to the user.

INCOME : multi-scale context management for the internet of things

Nowadays, context management solutions in ambient networks are well-known. However, with the IoT paradigm, ambient information is not anymore the only source of context. Context management solutions able to address multiple network scales ranging from ambient networks to the Internet of Things (IoT) are required. We present the INCOME project whose goal is to provide generic software and middleware components to ease the design and development of mass market context-aware applications built above the Internet of Things. By revisiting ambient intelligence (AmI) context management solutions for extending them to the IoT, INCOME allows to bridge the gap between these two very active research domains. In this landscape paper, we identify how INCOME plans to advance the state of the art and we briefly describe its scientific program which consists of three main tasks: (i) multi-scale context management, (ii) management of extrafunctional concerns (quality of context and privacy), and (iii) autonomous deployment of context management entities.

A survey on addressing privacy together with quality of context for context management in the Internet of Things

Making the Internet of Things (IoT) a reality will contribute to extend the context-aware ability of numerous sensitive applications. We can foresee that the context of users will include not only their own spatio-temporal conditions but also those of the things situated in their ambient environment and at the same time, thanks to the IoT, those that are located in other remote spaces. Consequently, next-generation context managers have to interact with the IoT underlying technologies and must, even more than before, address both privacy and quality of context (QoC) requirements. In this article, we show that the notions of privacy and QoC are intimately related and sometimes contradictory and survey the recent works addressing them. Current solutions usually consider only one notion, and very few of them started to bridge privacy and QoC. We identify some of the remaining challenges that next-generation context managers have to deal with to favour users’ acceptability by providing both the optimal QoC level and the appropriate privacy protection.

Building ubiquitous QoC-aware applications through model-driven software engineering

As every-day mobile devices can easily be equipped with multiple sensing capabilities, ubiquitous applications are expected to exploit the richness of the context information that can be collected by these devices in order to provide the service that is the most appropriate to the situation of the user. However, the design and implementation of such context-aware ubiquitous appplications remain challenging as there exist very few models and tools to guide application designers and developers in mastering the complexity of context information. This becomes even more crucial as context is by nature imperfect. One way to address this issue is to associate to context information meta-data representing its quality. We propose a generic and extensible design process for context-aware applications taking into account the quality of context (QoC). We demonstrate its use on a prototype application for sending flash sale offers to mobile users. We present extensive performance results in terms of memory and processing time of both elementary context management operations and the whole context policy implementing the Flash sale application. The cost of adding QoC management is also measured and appears to be limited to a few milliseconds. We show that a context policy with 120 QoC-aware nodes can be processed in less than 100 ms on a mobile phone. Moreover, a policy of almost 3000 nodes can be instantiated before exhausting the resources of the phone. This enables very rich application scenarios enhancing the user experience and will favor the development of new ubiquitous applications.

Trust-Based Context Contract Models for the Internet of Things

With the Internet of Things (IoT) paradigm, potentially private data could be made available on the Internet. Such data could then, be consumed by a growing number of applications. The acceptance and success of new pervasive applications depend on both the protection of privacy and the guarantee of quality of context (QoC). As in the IoT producers and consumers of context are decoupled, they are not aware of each other. Therefore, it is essential to provide them with means to express their guarantees and requirements concerning QoC and privacy. For this purpose, we propose meta-models to design context contracts defining privacy and QoC agreements, independently of the consumer and the producer sides. The contracts are key to an autonomous management of QoC and privacy in the IoT. Firstly, contracts may be modified at runtime to add, edit or remove clauses. Secondly, the middleware in charge of transmitting data from context producers to context consumers (e.g., context managers) will be able to match QoC/privacy requirements and guarantees. Finally, the matching process can adapt dynamically, for instance, to the current trust level between the two parties. These contracts will participate to build trust among IoT participants.

A QoC-Aware Discovery Service for the Internet of Things

The Internet of Things (IoT) is an emergent paradigm characterized by a plethora of smart objects connected to the Internet. An inherent characteristic of IoT is the high heterogeneity and the wide distribution of objects, thereby calling for ways to describe in an unambiguous and machine-interpretable way the resources provided by objects, their properties, and the services they offer. In this context, discovery services play a significant role as they allow clients (middleware platforms, end-users, applications) to retrieve available resources based on appropriate search criteria, such as resource type, capabilities, location, and Quality of Context (QoC) parameters. To cope with these concerns, we introduce QoDisco, a QoC-aware discovery service relying on multiple-attribute searches, range queries, and synchronous/asynchronous operations. QoDisco also comprises an ontology-based information model for semantically describing resources, services, and QoC-related information. In this paper, we describe the QoDisco architecture and information model as well as an evaluation of the search procedure in an urban air pollution monitoring scenario.

From Ambient Sensing to IoT-based Context Computing: An Open Framework for End to End QoC Management

Quality of Context (QoC) awareness is recognized as a key point for the success of context-aware computing. At the time where the combination of the Internet of Things, Cloud Computing, and Ambient Intelligence paradigms offer together new opportunities for managing richer context data, the next generation of Distributed Context Managers (DCM) is facing new challenges concerning QoC management. This paper presents our model-driven QoCIM framework. QoCIM is the acronym for Quality of Context Information Model. We show how it can help application developers to manage the whole QoC life-cycle by providing genericity, openness and uniformity. Its usages are illustrated, both at design time and at runtime, in the case of an urban pollution context- and QoC-aware scenario.

The QoCIM Framework: Concepts and Tools for Quality of Context Management

In the last decade, several works proposed their own list of quality of context (QoC) criteria. This chapter relates a comparative study of these successive propositions and shows that no consensus has been reached about the semantic and the comprehensiveness of QoC criteria. Facing this situation, the QoCIM meta-model offers a generic, computable and expressive solution to handle and exploit any QoC criterion within distributed context managers and context-aware applications. For validation purposes, the key modelling features of QoCIM are illustrated as well as the tool chain that provides developers with QoCIM based models editor and code generator. With the tool chain, developers are able to define and use their own QoC criteria within context and quality aware applications.

Towards QoC-aware location-based services

As location-based services on mobile devices are entering more and more everyday life, we are concerned in this paper with finding ways to master the level of quality of location information in order to take relevant decisions. Location being a typical example of context information, we manipulate it using the COSMOS framework that we develop for the management of context data and their associated quality meta-data or quality of context (QoC). We consider several QoC parameters that are important for location and determine how the QoC can help a location aggregator component to identify the current region where a user is located. The mechanisms we propose support a pragmatic approach in which application designers or deployers survey an area to demarcate regions surrounding locations, and application users are localized into these regions and are presented with the quality of the estimate. We report on the experimentation we performed on the campus of our institute collecting information from Wi-Fi, 3G networks and GPS signals, and show the accuracy we obtain at no additional infrastructure cost.