CloudAware
A System Software Infrastructure for Mobile Cloud Computing
Projektbeschreibung
Die Nutzung mobiler Geräte hat sich in den letzten Jahren vor allem dahingehend geändert, dass ihre Nutzer heutzutage den vollen Funktionsumfang stationärer Geräte auch unterwegs erwarten. Mobile Geräte sind und werden stationären Geräten gegenüber jedoch immer unterlegen sein, insb. was Rechen- und Speicherleistung, Bandbreite und Energiereserven anbetrifft. Mobiles Cloud Computing versucht diesen Einschränkungen zu begegnen, indem es mobilen Geräten die nahezu unbegrenzten Ressourcen der Cloud bereitstellt.
Das Projekt CloudAware zielt darauf ab, bewährte Konzepte aus dem Bereich der verteilten Systeme auf das mobile Cloud Computing zu übertragen. Eine inhärente Eigenschaft mobiler Nutzungsszenarien ist allerdings ein oft wechselnder Kontext, wodurch die bekannten Konzepte meist nicht direkt übertragen werden können. Ein zentraler Aspekt von CloudAware ist daher die Optimierung der sog. Auslagerungsentscheidung - hierzu wird eine kontextadaptive Anwendungsarchitektur entwickelt, welche in der Lage ist, dem schnell wechselnden Kontext mobiler Geräte gerecht zu werden und dabei die verfügbaren Cloud-Ressourcen möglichst gut ausnutzt.
Kontextadaption bedeutet im Fall von CloudAware die Prognose eines zukünftigen Kontexts, bezogen auf die Verfügbarkeit von zur Auslagerung nutzbaren Cloud-Ressourcen. Zu dieser Prognose werden die zahlreichen Sensordaten mobiler Geräte einen wesentlichen Beitrag leisten. Ein weiteres Ergebnis von CloudAware soll es sein, die Entwickler mobiler Anwendungen in die Lage zu versetzen, von den Vorteilen des mobilen Cloud Computings zu profitieren, ohne sich mit den damit einhergehenden Problemstellungen im Detail beschäftigen zu müssen.
Das Projekt CloudAware zielt darauf ab, bewährte Konzepte aus dem Bereich der verteilten Systeme auf das mobile Cloud Computing zu übertragen. Eine inhärente Eigenschaft mobiler Nutzungsszenarien ist allerdings ein oft wechselnder Kontext, wodurch die bekannten Konzepte meist nicht direkt übertragen werden können. Ein zentraler Aspekt von CloudAware ist daher die Optimierung der sog. Auslagerungsentscheidung - hierzu wird eine kontextadaptive Anwendungsarchitektur entwickelt, welche in der Lage ist, dem schnell wechselnden Kontext mobiler Geräte gerecht zu werden und dabei die verfügbaren Cloud-Ressourcen möglichst gut ausnutzt.
Kontextadaption bedeutet im Fall von CloudAware die Prognose eines zukünftigen Kontexts, bezogen auf die Verfügbarkeit von zur Auslagerung nutzbaren Cloud-Ressourcen. Zu dieser Prognose werden die zahlreichen Sensordaten mobiler Geräte einen wesentlichen Beitrag leisten. Ein weiteres Ergebnis von CloudAware soll es sein, die Entwickler mobiler Anwendungen in die Lage zu versetzen, von den Vorteilen des mobilen Cloud Computings zu profitieren, ohne sich mit den damit einhergehenden Problemstellungen im Detail beschäftigen zu müssen.
Beteiligte Personen
- Mitarbeiter
Publikationen im Projekt
2021 |
In: Journal of Ambient Intelligence and Humanized Computing | |
2018 |
In: Journal of Ambient Intelligence and Humanized Computing | |
In: Transactions on Emerging Telecommunications Technologies | ||
2016 |
In: 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W) | |
In: The 11th International Conference on Future Networks and Communications (FNC 2016) / The 13th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2016) / Affiliated Workshops, August 15-18, 2016, Montreal, Quebec, Canada | ||
2015 |
In: 8th IFIP Wireless and Mobile Networking Conference, WMNC 2015, Munich, Germany, October 5-7, 2015 | |
In: The 10th International Conference on Future Networks and Communications (FNC 2015) / The 12th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2015) / Affiliated Workshops, August 17-20, 2015, Belfort, France | ||
In: IFIP/IEEE International Symposium on Integrated Network Management, IM 2015, Ottawa, ON, Canada, 11-15 May, 2015 |
Dissertationen im Projekt
2017 | Dissertation von Gabriel Orsini
Betreuer: Winfried Lamersdorf |
Studentische Arbeiten im Projekt
2017 | Bachelorarbeit von Yannic Kitzky
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Masterarbeit von Xiao Han
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Masterarbeit von Rena Sharma
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Masterstudie von Cherina Tratzky
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2016 | Bachelorarbeit von Anne-Victoria Meyer
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Bachelorarbeit von Fabian Besner
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Masterarbeit von Sangines Füchtner Jorge Daniel
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Bachelorarbeit von Claas Brüggemann
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Bachelorarbeit von Ersin Yildrim
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Bachelorarbeit von Thorsten Hellmann
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2015 | Bachelorarbeit von Nico Pohl
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Am 8. October 2024 um 11:37 von Prof. Dr. Winfried LamersdorfCALL getCollectionFull('research/lookproject','vsis',56,0)