A Survey of Software Infrastructures and Frameworks for Ubiquitous Computing
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Mobile Information Systems 1 (2005) 41–80 41 IOS Press A survey of software infrastructures and frameworks for ubiquitous computing Christoph Endresa, Andreas Butzb and Asa MacWilliamsc aGerman Research Center for Artificial Intelligence, DFKI GmbH, Germany E-mail: [email protected] bMunich University, Germany E-mail: butz@ifi.lmu.de cTechnical University of Munich, Germany E-mail: [email protected] Abstract. In this survey, we discuss 29 software infrastructures and frameworks which support the construction of distributed interactive systems. They range from small projects with one implemented prototype to large scale research efforts, and they come from the fields of Augmented Reality (AR), Intelligent Environments, and Distributed Mobile Systems. In their own way, they can all be used to implement various aspects of the ubiquitous computing vision as described by Mark Weiser [60]. This survey is meant as a starting point for new projects, in order to choose an existing infrastructure for reuse, or to get an overview before designing a new one. It tries to provide a systematic, relatively broad (and necessarily not very deep) overview, while pointing to relevant literature for in-depth study of the systems discussed. 1. Introduction With the widespread availability of mobile computing devices, such as PDAs and smart phones as well as pervasive networks, such as GSM or WLAN, our attitude towards computing is changing rapidly. Computers have moved from our basements to our desks over the last three decades and they will move on from there into many parts of our daily environments. They will be connected to each other and equipped with extended sensing capabilities, making them reactive to their context of use. Today’s mobile computing devices are only an intermediate stage in this evolution, but the vision of ubiquitous computing [60] has become realistic to the extent that big software companies and popular magazines start to talk about it, often coining their own terms, but basically describing similar ideas. Research has picked up on this topic about a decade earlier and today many groups spend considerable amounts of effort and funding on the investigation of various aspects of ubiquitous computing. Often the first step towards research in this field is choosing or establishing a hardware and/or software infrastructure with which prototype scenarios can be developed and tested. These infrastructures or frameworks usually provide the basis for building ubiquitous computing applications as distributed interactive systems. They provide abstractions for networking, sensors or data, as well as formalisms and models for the specification of such systems. Researchers new to ubiquitous computing will invariably have to catch up with a lot of this previous work in order to find out where others might already have solved aspects of their own research agenda. The purpose of this survey is to provide a starting point for this process and to enable researchers to quickly identify relevant work in their field which can then be studied in more detail. 1574-017X/05/$17.00 2005 – IOS Press and the authors. All rights reserved 42 C. Endres et al. / A survey of software infrastructures and frameworks for ubiquitous computing Fig. 1. A geographic map of the systems discussed in this survey. 2. Terminology and criteria for the survey For the sake of this survey we have decided to subsume the various terms used in this field under three broad areas, which reflect fundamentally different approaches to building ubiquitous computing environments. – Augmented Reality (AR) overlays a virtual layer to the physical environment and thereby makes computing power (mostly visually) appear in the environment although it is physically located elsewhere. This group also includes projects which are concerned with mixed reality. – Intelligent Environments (IE) embed sensors, actuators and/or processors into the environment and thereby achieve behavior which was previously impossible. Parts of the ubiquitous computing power therefore reside in the actual objects of the environment, while others are still located on backend systems. This family also subsumes the terms smart spaces, instrumented rooms, as well as embedded systems. – Distributed Mobile Systems (DMS) provide ubiquitous computing power by coordinating and integrating multiple mobile devices and distributing functionality across them. This family is closest to the original ubiquitous computing scenario and subsumes among others the term context-aware computing. We realize that this separation is a rather strong simplification. The 29 systems discussed in this survey span a wide spectrum, but we hope to provide a useful first classification within this vast landscape. Figure 1 presents a more subtle version of this classification, where borderline cases can be recognized as such and where close proximity also expresses relationships between systems. The placement of a system in the diagram roughly expresses its position between the three groups described above. The criteria we use to describe the systems are split into five major sections. They are: 1. Type and background C. Endres et al. / A survey of software infrastructures and frameworks for ubiquitous computing 43 Group/company: Research group or company from which the system originates. Time/manpower: Time period and manpower spent, as a measure for the effort that went into the system. Development focus: Focus for the development of the system, e.g., research or commercial. Research goals: Research goals for the group and the system, e.g., in terms of major scientific or design goals. Contact: Main contact person for the project, e.g., principal researcher and senior developer. Target environment: Specific application environment targeted by the system. 2. System description A very brief description of the system, partly in our own words, partly in terms used by the system’s authors, where appropriate. Interesting aspects: Aspects, which distinguish this system particularly from others. 3. Underlying technology Language: Programming language, in which the system is implemented or in which applications are written. Network protocol: Protocols used for communication between system components and/or devices. Supported platforms: Hard- or software platforms on which the infrastructure runs. Scalability: Scalability of the infrastructure, e.g., number of users, devices, covered area. Underlying paradigm: Basic programming paradigm or conceptual model of the system. 4. Components Types: Types of system components. Granularity: Granularity at which the system allows to build these components. Description: Component descriptions and interface definitions, as used by compilers and run-time component management systems; e.g., IDL, XML, C++ class hierarchy Instantiation: of components at run time, e.g., command line, application, infrastructure Configuration: of components, e.g., component description, command line, config tool Communication/lookup: Organization of the communication between and lookup of components, e.g., central, decentral or hybrid. 5. General information Accessibility: Public accessibility of the system’s source code, binaries, documentation, existence of discussion groups, etc. Level of abstraction: The level of abstraction at which a programmer has to specify applications. Modules and services: Predefined services or modules which are part of the infrastructure. Suitable for: Things for which the system is particularly well suitable. Key publications: These are often the first comprehensive publications about a system, but sometimes also the most recent and up-to-date papers. They are recommended as starting points for a detailed study of the system. We consciously refrained from giving project URLs, since all these projects can easily be found by typing their names into any contemporary web search engine, while URLs might in some cases already be outdated at the time of publication of this article. In order to provide a rough historical perspective, Fig. 2 gives a chronological time line of the project durations. Open ended lines mean that the projects are still active. The following three main sections of the paper provide a list of these systems under the criteria stated above. The sections are split according to the three families of systems mentioned before, and within each section, systems are ordered alphabetically in order to avoid any apparent judgment of importance or relevance. 44 C. Endres et al. / A survey of software infrastructures and frameworks for ubiquitous computing fluidum dynamite dart context fabric activecampus vrib qosdream nmm cooltown xweb pima dwarf aura arvika gaia metaglue nexus imagetclar artoolkit ubicom tinmith context toolkit sentient computing studierstube beach limbo coterie multiplatform parctab 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Fig. 2. Time line of systems discussed in this survey. 3. Augmented reality systems This section contains infrastructures which are mainly used for implementing AR systems and proto- types. AR TOOLKIT is a publicly available library for marker recognition and camera-based tracking with a large user community. ARVIKA is a large research consortium who developed two infrastructures for their own purposes. DART wraps trackers and other AR functionality into a Macromedia DIRECTOR pro- gramming environment, while COTERIE provided tracker abstractions and distributed graphical objects in aMODULA-3 environment. DWARF provides a collection of reusable