Meego Italian Day 2011 – Prof. Paolo Bellavista

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Meego Italian Day 2011 – Prof. Paolo Bellavista - Mobile & Context-aware Computing: Panoramica, Scenari Applicativi e Sfide Tecnologiche

L’intervento cercherà di fare intuire, con esempi pratici e concreti, perchè le infrastrutture di supporto a servizi mobili e le applicazioni mobili stesse non possono più prescindere da forme avanzate di gestione del contesto a livello middleware. La gestione del contesto sta emergendo come cruciale non solo per la personalizzazione adattiva dei servizi mobili ma anche per vincere le sfide tecnologiche correlate alla necessità di scalabilità in scenari di deployment di ampie dimensioni. Saranno mostrate rapidamente esemplificazioni in ambito monitoraggio urbano tramite reti veicolari di sensori e condivisione opportunistica di risorse sotto-utilizzate.

Prof. Paolo Bellavista è professore associato di sistemi distribuiti e mobili presso la Facoltà di Ingegneria dell’Università di Bologna. I suoi principali ambiti di ricerca sono il supporto middleware a sistemi e servizi mobili, i servizi context-aware, lo streaming multimediale verso smart phone su reti wired-wireless eterogenee, le reti wireless di sensori anche veicolari, l’integrazione dinamica di sistemi mobili con infrastrutture, anche cloud. E’ inoltre membro dell’Editorial Board di IEEE Communications, IEEE Transactions on Computers, IEEE Transactions on Network and Service Management., IEEE Transactions on Services Computing, Elsevier Pervasive and Mobile Computing Journal, and Springer Journal of Network and Systems Management.

http://www.meegoit.com/2011

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Meego Italian Day 2011 – Prof. Paolo Bellavista

  1. 1. Mobile & Context-aware Computing: Panoramica,Scenari Applicativi e Sfide Tecnologiche 18 Marzo 2011 – I Facoltà di Ingegneria Università degli Studi di Bologna MeeGo Italian Day Paolo Bellavista paolo.bellavista@deis.unibo.it http://lia.deis.unibo.it/Staff/PaoloBellavista/
  2. 2. AgendaDefinizione di mobile computing, contextawareness e middlewarePerché mobile computing non è per nulla commodityma grandissima opportunità aperta di ricercae businessEsempio di middleware per distribuzionecontesto in ambienti a larga scalaEsempio di middleware per condivisioneopportunistica di risorseIdea provocatoria: “future pervasive systemsas social sharing spaces”? MeeGo – Bologna - 18.03.2011 2/23
  3. 3. Mobile Computing (1)Mobile computing richiede approccio a livelli multipli e con competenze multiple: Dispositivi embedded (problematiche miniaturizzazione, consumo ridotto di energia, …) Comunicazioni wireless (IEEE 802.11a/b/g/s, Bluetooth, WiMAX, comunicazioni veicolari, …) Piattaforme di supporto software (Android, iPhoneSDK, SymbianOS, …) Gestione energia a livello piattaforma software Gestione interfacce wireless multiple e handover a livello piattaforma software Gestione contesto … MeeGo – Bologna - 18.03.2011 3/23
  4. 4. Mobile Computing (2)…Gestione cross-layer requisiti applicativi e allocazionerisorseSupporto a servizi infrastructure-basedSupporto a servizi peer-to-peerSupporto a servizi mobili opportunisticiSupporto a servizi mobili social-awareE design, implementazione, deployment emanagement runtime di tutte queste categorie diservizi! MeeGo – Bologna - 18.03.2011 4/23
  5. 5. ContestoGartner, November 2009, “Context-aware Computing will bea $12 Billion Market by 2012”Contesto (time, location, time and personalinteressi personali, caratteristiche location interestsdevice/risorse/servizi, gruppi, deviceaffinità sociali, storia sessioni characteristics user contextprecedenti, previsioni susessioni future, …) service administrative domainsUsato per personalizzarefruizione del servizio(adattamento) edisciplinare accessoa risorse/servizi(visibilità personalizzata) network domains personalized service view MeeGo – Bologna - 18.03.2011 5/23
  6. 6. NON è una COMMODITY!Mobile computing richiede approccio a livelli multipli e con competenze multiple: Dispositivi embedded (problematiche miniaturizzazione, consumo ridotto di energia, …) Comunicazioni wireless (IEEE 802.11a/b/g/s, Bluetooth, WiMAX, comunicazioni veicolari, …) Piattaforme di supporto software (Android, iPhoneSDK, SymbianOS, …) Gestione energia a livello piattaforma software Gestione interfacce wireless multiple e handover a livello piattaforma software Gestione contesto … MIDDLEWARE MeeGo – Bologna - 18.03.2011 6/23
  7. 7. NON è una COMMODITY!…Gestione cross-layer requisiti applicativi e allocazionerisorseSupporto a servizi infrastructure-basedSupporto a servizi peer-to-peerSupporto a servizi mobili opportunisticiSupporto a servizi mobili social-awareE design, implementazione, deployment emanagement runtime di tutte queste categorie diservizi! MIDDLEWARE + APPS MeeGo – Bologna - 18.03.2011 7/23
  8. 8. Middleware e Applicazioni MobiliSolo per citare alcuni esempi possibili: Distribuzione di streaming multimediale dinamicamente adattato verso terminali mobili differenziati Always Best Connected e Always Best Served Sensori, smart environment e conseguente adattamento dinamico per servizi context-aware Monitoraggio urbano collaborativo (traffico, inquinamento, uso di veicoli/utenti intrinsecamente mobili, …) – vedi MobEyes Gestione sessione e continuità, anche per servizi multimediali, in infrastrutture eterogenee integrate conformi a IMS – vedi IHMAS Replicazione e applicazioni delay tolerant Resource sharing e comportamenti sociali … MeeGo – Bologna - 18.03.2011 8/23
  9. 9. Context-Aware Applications in Mobile and Large-Scale Scenarios BLUETOOTHWLAN GPRS MeeGo – Bologna - 18.03.2011 9/23
  10. 10. Need for Context Data Distribution Infrastructures (CDDI)Context data distribution is a complex task that posesseveral challenging requirements: Heterogeneity of the computing environment: devices (smartphones,Personal Digital Assistants, netbooks, …) and communication technologies(WiFi, Bluetooth, cellular 3G) and types (infrastructure and ad-hoc) Device mobility and density: ever-increasing number of mobile devices,already producing huge amounts of context data (environmental sensing,social computing, …) Data delivery with guaranteed quality levels: depending on specificservice (disaster recovery and emergency scenario, entertainment, …)We need novel Context Data Distribution Infrastructures(CDDIs) to transparently address and take over context datadistribution aspects (integration aspects, data distributiondifferentiation, scalability, …) MeeGo – Bologna - 18.03.2011 10/23
  11. 11. CDDI for Large-Scale Mobile Networks: SALES Design Guidelines1. Middleware-level approach Middleware-based approaches to hide implementation complexity Application-level solutions to have full visibility of underlying execution platforms and hardware resources2. Heterogeneous wireless communications Heterogeneous wireless standards to increase both system coverage and total available bandwidth3. Heterogeneous wireless modes Wireless infrastructures to ensure context data persistency Wireless ad-hoc communications to reduce the distribution load MeeGo – Bologna - 18.03.2011 11/23
  12. 12. CDDI for Large-Scale Mobile Networks: SALES Design Guidelines4. Constrained data distribution scopes Distribute context data only to interested nodes (logical-locality principle) Distribute location-dependent context data only to the devices contained in the local physical place (physical-locality principle) PAN data scope LAN data scope5. Context data distribution adaptation at run-time CDDI has to adapt to fit available resources (minimum intrusion principle) Introduce differentiated quality levels to drive and constraint possible run-time reconfigurations of the CDDI MeeGo – Bologna - 18.03.2011 12/23
  13. 13. SALES Architecture Legend: CN – Central Node CUN – Coordinator User Node CN BN – Base Node SUN – Simple User Node BN1 BN3 BN2 CUN21 CUN11 CUN31 CUN32 SUN211 SUN311 SUN322 SUN111 SUN321 SUN112Three-level tree-like architecture ensures effective and integrated usage of wireless infrastructure and ad- hoc communication modes minimizes tree depth to reduce management overheadNodes at the same level form a collaborative network in which context data are distributed in a peer-to-peer (P2P) manner MeeGo – Bologna - 18.03.2011 13/23
  14. 14. MANET vs. Spontaneous NetworkingMANET homogeneous wireless technology usually targeted to a specific application with given constrains (e.g., energy, throughput...) many nodes with high mobility degreeSpontaneous networking very heterogeneous node capabilities general-purpose environment medium node mobility MeeGo – Bologna - 18.03.2011 14/23
  15. 15. Spontaneous NetworkingImpromptu interconnection of mobile and fixed nodes users willing to share content and resourcesMaximize interconnected nodes and available services heterogeneous wireless technologies both infrastructure and ad-hoc connectivity multiple connectivity opportunities MeeGo – Bologna - 18.03.2011 15/23
  16. 16. Spontaneous NetworkingNode cooperation to UMTS Base Station IEEE 802.11 Access Point provide single-hop connectivity D IEEE 802.11 manage multi-hop connectivity A IBSS C support peer-to-peer services Bluetooth E Piconet B G F interface providing IEEE 802.11 Bluetooth ad hoc connectivity IBSS PiconetPeer-to-peer File Sharing single-hop link service advertising: NodeA provides lesson notes service discovery: NodeF looks for nodes that share files service invocation: NodeF browses and downloads notes stored on NodeANodeA and NodeF reside in different layer-3 networks MeeGo – Bologna - 18.03.2011 16/23
  17. 17. RAMP MiddlewareApplication-layer management layer-3 routing unsuitable for spontaneous networks operating system independency + routing flexibilityLocal management decisions nodes have partial topology awareness dynamic path reconfigurationReactive and mission-oriented approach resource/path discovery only when required eventually cached information invalidated very soonStateless communication per-packet information delivery and path creationCross-layer management applications may influence routing mechanism behaviorManagement of multiple connectivity opportunities RAMP evaluates end-to-end paths in a dynamic, context-aware, and lightweight way MeeGo – Bologna - 18.03.2011 17/23
  18. 18. File Sharing ApplicationNo split: bufferSize greater than file size transmission time increases linearlySplit: bufferSize lower than file size transmission time greatly lowers RAMP introduces little overheadBest buffer size minimum transmission time while limiting read/write depends on path length and packet size sub-optimal default value: 50KB int bestBufferSize(int packetSize, int pathLength); MeeGo – Bologna - 18.03.2011 18/23
  19. 19. Reliability to Path Disruptions routing reroutingAbrupt path disruption would interruptpacket deliveryThe intermediary node aware of path t0 A X L Bdisruption looks for an alternative path,while temporarily storing incomingpackets t1 A X L BThen it reroutes incoming and storedpackets and advices the multimediastream sender: no packet lossFinally, the multimedia stream senderstarts exploiting the novel pathThe final user only perceives a partialquality degradation and only for a 17000 from stream start (ms) Packet arrival timelimited time interval 16500The overhead on the intermediary node 16000is rather limited in terms of both 15500additional communication and memory 15000usage 14500 -20 -17 -14 -11 -8 -5 -2 1 4 7 10 13 16 19 Packet number (0 = last packet before path disruption) MeeGo – Bologna - 18.03.2011 19/23
  20. 20. Reliability for Delay Tolerant ApplicationsCritical message delivery in case of(temporary) path unavailability, e.g., disasterrecovery scenario sparse nodes in a wide geographical area without cellular coverage routing storingNode movements could create a path or anintermediary node could move towards thedestination node area t0 A X L BIntermediary nodes cooperate temporarilystoring the message and periodically lookingfor the destination NMessage discarding based on a temporaldeadline t1 A X L B message validity gradually decreases while time passesSuitable in case of small-size messages, notimposing too much overhead on intermediarynodes MeeGo – Bologna - 18.03.2011 20/23
  21. 21. Internet Connectivity Sharing CBorder Nodes (BNs) provides Internetconnectivity via RAMP Internet BN1 X BN2 InternetNode C discovers available services on 120 1BNs and alternatively exploits them to throughput weight 0.9surf Google Maps (very intensive HTTP 100 0.8interactions) via a standard Web browser 0.7 Throughput (KB/s) 80 0.6 Weight 60 0.5 0.4Starting BN1 and BN2 bandwidth is 40 0.3 0.2125KB/s and 25KB/s respectively (inverted 20 0.1 BN1after 100s) 0 5 25 45 65 85 105 125 145 165 185 0Node C notices BN1 provides a higher Time (s)throughput and thus exploits it more 120 1 throughput weight 0.9frequently than BN2 100 0.8 Throughput (KB/s) 0.7After 100s the bandwidth allocation is 80 0.6 Weightinverted: node C notes throughput 60 0.5 0.4modification and thus starts exploiting 40 0.3BN2 more than BN1 20 0.2 0.1 0 5 25 45 65 85 105 125 145 165 185 0 BN2 Time (s) MeeGo – Bologna - 18.03.2011 21/23
  22. 22. Pervasive Systems + Urban Environments + Social Sharing Not only urban space pervasive personal space social space systems go wide-scale (urbanenvironments), but also strong push towards COLLABO- RATION Courtesy:MetroSense, A. Campbell Social sharing of sensed information Social sharing of available resources MeeGo – Bologna - 18.03.2011 22/23
  23. 23. Social Applications: a Push toward Resource Sharing?The success of social apps could help in pushing users’ communities toward better exploitation of available resources (is this “green” computing?) via effective and dynamic sharing of info+services from pervasive systems MeeGo – Bologna - 18.03.2011 23/24
  24. 24. Questions? (and advertising ☺) Grazie per l’attenzione! E la parola adesso a relatori più specifici…Contatti: Paolo Bellavista (paolo.bellavista@unibo.it) Mobile Middleware Research Group http://lia.deis.unibo.it/Staff/PaoloBellavista/ … e arrivederci all’interno del corso di Sistemi Mobili M (prima attivazione AA 2010/2011) MeeGo – Bologna - 18.03.2011

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