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Mobile Computing, Applications, and Services : 7th International Conference, MobiCASE 2015, Berlin, Germany, November 12-13, 2015, Revised Selected Papers.
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing AG,
2016.
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| Colección: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Intro; Preface; Organization; Contents; Intelligent Caching; Network Data Buffering for Availability Improvement of Mobile Web Applications; Abstract; 1 Background; 2 Issues and Existing Technology; 3 Data Synchronization with VMA; 3.1 Overview; 3.2 DataCache; 3.3 DataShrink; 4 Results; 5 Conclusion, Discussion, and Future Work; References; Upgrading Wireless Home Routers for Enabling Large-Scale Deployment of Cloudlets; 1 Introduction; 2 Related Work; 3 Concept for Router-Based Cloudlets; 3.1 Device (Router); 3.2 Infrastructure; 3.3 Community; 4 Experimental Setup; 4.1 Hardware.
- 4.2 Measurement Methodology5 Benchmark Results; 6 Discussion and Future Work; 6.1 Router's Performance; 6.2 Offloading Strategy; 6.3 Discovery, Handover, and Failure Handling; 7 Conclusion; References; Activity Recognition and Crowdsourcing; Adaptive Activity and Context Recognition Using Multimodal Sensors in Smart Devices; 1 Introduction; 2 Related Work; 3 Sensing System; 3.1 Hardware; 3.2 Architecture; 3.3 Metrics Collected by SWIPE; 3.4 Energy Saving Strategy; 4 Building a Data Set; 4.1 Scenario; 4.2 Example; 4.3 Activity and Context Classes; 5 Activity and Context Recognition Using SVM.
- 5.1 Parameters5.2 Feature Set; 5.3 Recognition Using Metrics Individually; 5.4 Recognition Using a Combination of Multiple Metrics; 5.5 Application Example; 6 Comparing Participants; 7 Conclusion; References; Characterization of User's Behavior Variations for Design of Replayable Mobile Workloads; 1 Introduction; 2 Related Work; 3 Experimental Setup; 4 Analysis of User Workloads; 4.1 Intra-App; 4.2 Inter-App; 4.3 Utilization Values; 5 Automated Test Run Generation; 5.1 Automated Generation of Test Runs; 5.2 Comparison with User Workloads; 6 Analysis with Test Runs.
- 6.1 Resource Characterization for Scenarios6.2 Memory Bandwidth and User Interaction; 6.3 Impact on Power and Optimization; 6.4 Changes in Devices and Platforms; 7 Conclusion; References; Worker Selection for Reliably Crowdsourcing Location-Dependent Tasks; 1 Introduction; 2 Related Work; 3 Our Approaches; 3.1 Definition of Accuracy Metric; 3.2 Formal Problem Statement; 3.3 Our Algorithms; 4 Performance Evaluation; 4.1 Simulation Setup; 4.2 Experimental Results; 5 Conclusions; References; Mobile Frameworks; AppSachet: Distributed App Delivery from the Edge Cloud; 1 Introduction.
- 2 Internet Traffic Due to App Delivery2.1 Data Collection Methodology; 2.2 Observations; 3 App Sachet System Design; 3.1 AppSachet Cache; 3.2 AppSachet Server; 3.3 AppSachet Sync; 3.4 AppSachet Client; 4 AppSachet Cache Policy Design; 4.1 Popularity-Aware Caching: p-LRU; 4.2 Cost-Aware Caching: c-LRU; 5 AppSachet Implementation; 6 Evaluation; 6.1 Experimental Testbed; 6.2 Cacheability of App Traffic; 6.3 p-LRU and c-LRU Cache Performance; 6.4 Storage Requirements on eBox; 6.5 Cost Benefit Analysis of Deploying eBox Based AppSachets; 7 Discussion and Future Work; 8 Related Work; 9 Conclusions.