Introduction
Context-awareness, data and computational infrastructure requirements
Conceptual framework for cloud-based context-aware services
Components orProcedures | Description (e.g. What?) | Goals/Objectives (e.g. Why?) | Operationalisation (e.g. How?) | Stakeholders (e.g. Who?) | Usefulness |
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Process Models
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Data Processes
| Processes related to datacollection & acquisition,cleansing and filtering,harmonisation and integration | To ensure high quality raw datais collected and transformedinto application specific targetdata model | Apache Solr, AppacheCassandra, (Geo-)SPARQL andRDF query languages, ISO19100 series of standards, OGCPUCK protocol, OpenGISSimple Feature Implementation specs (CORBA, OLE/COM) | Data custodians e.g. cityadministrations, local agenciesincluding security, environment, energy, transport, andeconomic development, officeof national statistics, Eurostat,etc. Business organisations e.g. insurance companies,utility services etc. GeneralPublic e.g. citizens, NGOs | Refinement of data andusability for variety ofapplications to getcross-disciplinaryinformation intelligence |
Service Processes
| Process related to thematicservice discovery, servicechaining and/or workflowcomposition | To discover and connect withrequired utility services | UDDI, (CSW-)ebRIM, OGC OWSstandards - WCS (metadatadiscovery), CSW (discovery),WMS (view), WFS (download),GeoAPI | Service consumers e.g. business organisations, public administrations, general public, etc. Service producers e.g. IT research industry, SMEs, statistical and IT experts etc | Service oriented approachsupports process agility byusing service plug-n-playfeature |
Analytical Processes
| Analysis algorithms, statisticalmodels, reasoning | To identify and use existingand new algorithms (machinelearning, data mining etc) andmodels to analyse applicationspecific data and generaterequired output | Hadoop MapReduce,RapidMiner, R, OGC WPS | Knowledge generation cansupport decision making | |
Security Processes
| Authorisation, Anonymity,Encryption | To ensure that properinformation securitymeasures are applied | ISO/IEC 10181-4:1997 - Security Framework for Open System, GeoXACML | Cyber security providers e.g.SMEs. Beneficiers e.g. generalpublic. | Provides increased privacy andestabilishes trust on the system |
User InteractionProcesses
| Visualisation, Simulation,Interactivity | To facilitate end users byproviding intuitive GUI tointeract with applications | Lynx Browser, OGC OpenLS,OGC Web 3D Service, WMS,OpenGIS SLD, OGC WMTS | Social scientists, e.g. expertsin socio-technical aspects.SMEs e.g. IT developers, etc..End users e.g. general public,etc. | Increases application usabilityand intuitiveness |
Resource managementProcesses
| Resource utilisation,virtualisation, performanceand reliability | To ensure that systemresources are utilised to theirmaximum potential | Public, private and hybridcloud infrastructure e.g. IBMSmart City Control Centre |
IT Administrators
| Results in efficient resourceutilisation that can contributetowards green computing |
Organisational Processes
| Business organisation andinstitutional processes | Aligning theinformation processing with businessprocesses | BPMN, BPEL | Organisations e.g. MetOffice, Disaster managementauthority, Tourismdevelopment, Publictransport authority, Energydistributor, etc. | Ability to adopt organisationalprocesses can result wideradoption |
Data Models
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Data Management
| Standards and management of data and metadata | Structured (SQL/NoSQL based)and non-structured datamanagement, Relational,Object-oriented, Cube, Spatialdata models, Adoption of dataand metadata standards suchas ISO 19000, Dublin Core etc | OpenGIS specification basedMySQL, NuoDB, Oracle, MS SQLServer, PostgreSQL - PostGIS,Apache Cassandra, CouchDB,MongoDB, SimpleDB,DynamoDB | Data modellers andadministrators e.g. IT experts | Ability to store, retrieve, updateand manage data |
Metadata and Datastructure
| Dublin Core, DBLP, OSImetadata standards - 19115,JSON, OGC NetCDF, EOmetadata profile, CityGML,OGC TJS | Data providers andcustodians e.g. cityadministrations, environmentalagencies, office of nationalstatistics, Eurostat, etc. GeneralPublic e.g. citizens. | Increases understanding andpromotes reusability of datamodels | ||
Contextual Models
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Structuring andProfiling
| User profiles and preferences | To structure contextinformation that can bereused for specific users andenvironments | ContextML, OGC Context standard, KML standard, OWL, RDF, OGC Web Map Context Document, Context casting | Social scientists. IT experts. End users e.g. general public, etc. | Personalisation of informationenhances usability |
Context Exchange
| Understandable contextdescription for reusabilitypurposes | To enable exchange contextinformation between variousservices and components | Exchanging context betweenvarious services helps toimprove context-awareinformation processing andprovision | ||
Context Management
| Context entity and relationshipmodel | To manage context data modeland associated actions forspecific circumstances andenvironments | Structured management ofcontext models enhancesreusability and improvesapplication performance | ||
Citizen Participation
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Information provision
| Awareness raising, Informationprovision, communication | To provide contextually related information to citizens and enable them to participate in decision making processes | Web 2.0/3.0, WS-Notification | End users e.g. general public, local business organisations, etc. | Contextual information forbetter decisions |
Data collection
| Crowd sourcing, Citizenscience, Public participationand engagement | OGC SWE, SOS, SensorML,OpenLS, GeoSMS | Supporting participatorysensing and bottom-updemocracy | ||
Behavioural Changemodels
| Behavioural changes ofindividuals or evolvingbusiness processes | To identify changes inbehaviour of users due toenvironmental awareness | Interventions, policies, StudyProtocol | Healthy and environmentfriendly behaviour change andbetter work productivity | |
Application Thematic Models
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Thematic Applications
| Environment, Energy, Mobility,Security, Urban etc | To use collected data forspecific application thematicdomains | Application domain experts e.g. energy, transport,planning, health etc. | Application specific as well ascross-disciplinary integratedknowledge generation forbetter environmental andurban planning | |
Cyber-space Infrastructure
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Hardware and software
| Cloud infrastructure, Sensors,RFIDs, Storage, Processing H/W,IoTs, software frameworks | To apply related hardware andsoftware technologies | OpenStack, Apache Cassandra | IT experts and developers.SMEs e.g. sensors web,wireless ad-hoc networks,cloud infrastructure, serviceprovision etc. | Use of contemporarytechnology for informationmanagement |
Management Aspects
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System Management
| Flow of Info, auditing andpricing, security | To ensure that all componentsare well integrated andsupport flow of informationand an appropriate cost modelis developed | WebMethods, Oracle BPMSuite, OpenText |
IT Administrators
| Enabling sustainable businessmodel |
Service Federation
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System of systems
| Application integration | Applying standards and developing wrappers/adaptors to enable flow of information between multiple applications and systems | Corba, Web Services |
IT experts and developers. SMEs. Research and Academia, Application domain experts
| Enabling inter-cloudinformation and resourceexchange |
Interoperability
| Standards, service wrappers | W3C web standards, OASISRM-ODP, OGC services |
Proposed architecture
Use case and discussion
Proof of the concept
The contextual query
Processing the queries
Prototype stage | Architecture layer |
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User interface | Application service layer |
Crime statistics retrieval | Data acquisition and analysis layer |
Data filtering | Service composition layer |
Simulated cloud infrastructure | Platform integration later |
Experimental setup
Parameter | Value | Justification |
---|---|---|
Computing power | 80 GFLOPS | Approximately equivalent to a |
per machine | Quad-core 2.5 GHz Sandy Bridge | |
CPU | ||
Internet connectivity | 1 Gbps | Arbitrarily chosen value |
between machines | ||
Topology | Master-slave | Represents typical cluster |
architecture | architectures | |
Network latency | 50 ms | Arbitrarily chosen value |