The representation of spaces, locations and the entities they contain is of great importance to location aware systems and pervasive computing scenarios. There has been an active research community in developing many diverse models of location, resulting in significant progress in the area. Various types of location model have evolved through experiment and experience however there still remains many challenges to be met by the research community. This paper aims to highlight previous trends in location modeling, discuss the research challenges ahead and to outline the initial design of a location model for the Strathclyde Context Infrastructure [?]

Ferguson, Ian

Glassey, Richard

English

The representation of spaces, locations and the entities they contain is of great importance to location aware systems and pervasive computing scenarios. There has been an active research community in developing many diverse models of location, resulting in significant progress in the area. Various types of location model have evolved through experiment and experience however there still remains many challenges to be met by the research community. This paper aims to highlight previous trends in location modeling, discuss the research challenges ahead and to outline the initial design of a location model for the Strathclyde Context Infrastructure [1]

Richard Glassey

Ian Ferguson

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Modeling Location for Pervasive Environments

University of Strathclyde Institutional Repository

Strathprints Institutional RepositoryGlassey, R. and Ferguson, R.I. (2003) Modeling location for pervasive environments. In: 1st UK-UbiNet Workshop, 2003-09-25 - 2003-09-26, London, England.Strathprints is designed to allow users to access the research output of the University of Strathclyde.Copyright c© and Moral Rights for the papers on this site are retained by the individual authorsand/or other copyright owners. You may not engage in further distribution of the material for anyprofitmaking activities or any commercial gain. You may freely distribute both the url (http://strathprints.strath.ac.uk/) and the content of this paper for research or study, educational, ornot-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to Strathprints administrator:mailto:strathprints@strath.ac.ukhttp://strathprints.strath.ac.uk/   Glassey, R. and Ferguson, R. I. (2003) Modeling location for pervasive environments. In: 1st UK-UbiNet Workshop, 25-26 Sep 2003, London, England.   http://eprints.cdlr.strath.ac.uk/1960/      Strathprints is designed to allow users to access the research output of the University of Strathclyde. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in Strathprints to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the url (http://eprints.cdlr.strath.ac.uk) of the Strathprints website.  Any correspondence concerning this service should be sent to The Strathprints Administrator: eprints@cis.strath.ac.uk Modeling Location for Pervasive EnvironmentsRichard Glassey and Ian FergusonThe Pervasive and Global Computing GroupDepartment of Computer and Information SciencesUniversity of StrathclydeGlasgow, ScotlandEmail: {firstname, lastname}@cis.strath.ac.ukAbstract— The representation of spaces, locations and theentities they contain is of great importance to location awaresystems and pervasive computing scenarios. There has been anactive research community in developing many diverse modelsof location, resulting in significant progress in the area. Varioustypes of location model have evolved through experiment andexperience however there still remains many challenges to be metby the research community. This paper aims to highlight previoustrends in location modeling, discuss the research challenges aheadand to outline the initial design of a location model for theStrathclyde Context Infrastructure [?].I. INTRODUCTIONLocation information is a fundamental aspect of pervasivecomputing. The ability to discover an entity’s location withina space and be able to reason about relationships with otherentities sharing this space is very useful. Location modelingrefers to the capture, organization and reasoning of locationinformation. The earliest efforts to develop ubiquitous com-puting environments [?] introduced abstract models of locationfor the environment. Since then the models of location havedeveloped in terms of representation and complexity. Previouswork [?], [?] has identified four types of location model.• Geometric - allows points, areas and volumes to bemodelled, however a point in geometric space has norelationship to what it points to. The resolution of thismodel is as fine as the units of measurement used.• Symbolic - describes location and space in terms of namesand abstractions. Unlike the previous model type, humansand computational devices can understand this model,however they lack the precision of geometric models.• Hybrid - represents a logical step forward in combiningthe advantages of the previous model types in orderto overcome their respective disadvantages. As a con-sequence the hybrid model is more complex, requiringgreater amounts of data.• Semantic - rather than focusing purely on position, thismodel type is concerned with relationships of entities inspace and between the spaces themselves.Despite the progress made so far with respect to modelinglocation many challenges have been identified that must beovercome. The next section highlights some of the pertinentchallenges.II. CHALLENGESThe following list briefly discusses a collection of chal-lenges that have to be overcome in order to progress the utilityof location models.• Managing complexity and scalability: As models increasein complexity the management and integrity of the infor-mation becomes a critical design issue. In addition thedesign of a model should not only take into account thepotentially large number of entities in a single environ-ment, but also factor for multiple environments.• Transient environments and aggregation of sensor data:Designing a model that successfully bridges the differ-ence between administrative, social and home environ-ments is challenging. Focusing the design on a singleenvironment may obscure difficulties when applying it toanother environment type. Many environments will sup-port one or more differing location sensing technologies.Aggregation of this multiple sensor data would dependon an abstract location model not directly connected toor reliant upon a particular sensing technology.• Inference beyond position: Whilst determination of po-sition remains important there is potential for greatercontextual inferences to be made from a model in termsincluding both physical and conceptual connectivity.• Privacy and security: Although previously acknowledgedthere are still many issues surrounding the access controland management of potentially sensitive location infor-mation.• Ontology for location: The decision of how to describespace is not a trivial matter, however a common meansto represent location across various different models maybe useful.• Open and extensible model: The task of providing lo-cation information for the model should not rely solelyon a single source. The ability for other providers tosupply additional information is desirable. In order fora model to evolve along with changes in the environmentit and the sensing technologies employed it must be easilyextensible and adaptive.This list is not exhaustive, but it does reflect the effort stillrequired in designing models. We propose a location modelfor pervasive environments that will overcome shortcomingsof previous models and meet the challenges highlighted.III. DESIGNA. Outline of Strathclyde Context InfrastructureThe Strathclyde Context Infrastructure (SCI) is organizedinto two distinct layers. The upper layer of the infrastructureis a network overlay of partially connected nodes. The lowerlayer of the infrastructure concerns the contents of each node,which consists of entities (People, Software, Places, Devicesand Artifacts) responsible for producing, managing and usingcontextual information, and is referred to as a Range [?]. Thepurpose of the Range is the logical partitioning of space. Ourcontext infrastructure requires a location model for Ranges thatcaptures the geometric, topological and logical spatial relationsthat will allow fine grained control over the interaction ofentities with the real world and the user.B. Location Model DesignIn order to make the model of location as flexible as thenotion of a SCI Range, multiple environment types mustbe considered from the initial design onwards. It is deemedtoo restrictive to design a model with a bias towards asingle environment type. It is believed that modeling transitiveenvironments, whilst difficult, brings us closer to a morerealistic model that would be useful across the many diverseenvironments encountered in everyday scenarios.Extending from the above point is the need to make use ofmultiple sensor technologies (passive IR, RFID tags, GPS andwireless signal strength [?]) found within environments anddeal with uncertainty when faced with imperfect information.This points to the need for the model to employ simpleabstractions that enable an interface between sensor and modelto be developed that hides the complexity.Previous location models have largely relied upon a statichierarchical tree structure as a natural means of how humansreason about space and how buildings are constructed. Thisapproach however limits aspects of reasoning beyond physicalconnectedness and provision of navigation using path costmetrics. Whilst at the basic level location can be viewed ashierarchical it is perhaps more accurate to model location withmultiple parents, eventually representing a graph structure.This flexibility allows for basic navigation tasks like a routefrom A to B, to more logical concepts of navigating adminis-trative group structures instead of just architectural structure.A graph approach is suitable for modeling more than physicalrelationships between entities. For instance a group of roomsmay be physically connected by doors and corridors, but theyalso form a research area within a department which doesnot have physical form. This notion could also support roomsthat are physically separated by floors or buildings, but whichare logically related. A hierarchical model would struggle torepresent this form of concept. Modeling conceptual arrange-ments of location and entities beyond their physical locationis a goal of this model.C. Location QueriesHaving described the need for interaction with multiple lowlevel sensors, consideration must be given to providing highlevel access to the information contained within the model.The form of the query and the resultant reply will be of greatimportance to the variety of contextual services and locationaware applications that may demand location information. Thedesign of the query will be such that it is both open andflexible with due consideration to returning sensible replies.The query should benefit from the graph model, rememberingboth physical and logical connectivity attributes, so that aquery asking, “which members of the research group X arepresently in their offices?” would pose no problem.D. Management of Model InformationIn terms of managing the location information modelled,it’s accessibility, integrity and security, a distributed modelwill be used instead of a centralized solution. This decisionis partly influenced by the nature of Ranges within SCI,distributed across and connected by an overlay network. Whilsta centralized solution may favour performance, it will not besuitable to deal with the scalability issues inherent in pervasivecomputing environments. The management of the model willinclude features of openness and extensibility. It is envisagedthat as more location information becomes available that it canbe integrated easily in order to evolve the model. The abilityto extend the model should encourage the process where thecontent can evolve without the need to develop new modelsto cope with new information. These features however raisethe question of whether an ontology for space needs to bedeveloped and how new information can be mediated forinclusion.IV. SUMMARY AND FUTURE WORKThis paper has sought to provide an brief overview of howlocation models are currently being developed and the futureresearch challenges. The list of challenges is by no meansexhaustive but it does highlight the types of issues locationmodeling must overcome.The next step will be to formalize the design goals of thelocation model for Strathclyde Context Infrastructure into aspecification. Prototypes of this model can then be imple-mented and tested in order to determine their usability andareas of improvement. The evaluation of the model will beinitially the simulation of environments and typical usage, witha view to modeling real world environments and scenarios.REFERENCES[1] R. Glassey, G. Stevenson, M. Richmond, P. Nixon, S. Terzis, F. Wang,and I. Ferguson. Towards a middleware for generalised context manage-ment. In 1st Int. Workshop for Middleware for Pervasive and Ad HocComputing, Middleware 2003 companion, pages 45–52, 2003.[2] B. Schilit and M. Theimer. Disseminating active map information tomobile hosts. IEEE Network, 8(5):22–32, 1994.[3] U. Leonhardt. Supporting Location-Awareness in Open DistributedSystems. PhD thesis, University of London, 1998.[4] M. Beigl, D. Salber, and P. Gray, editors. Workshop on Location Modelingfor Ubiquitous Computing, Ubicomp. LNCS, 2001.[5] J. Hightower and G. Borriello. Location systems for ubiquitous comput-ing. IEEE Computer, 34(8):57–66, August 2001.

Disseminating active map information to mobile hosts.

Location systems for ubiquitous computing.

Supporting Location-Awareness in Open Distributed Systems.

Towards a middleware for generalised context management.

Modeling location for pervasive environments

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Modeling location for pervasive environments

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