Abstract
At present, the mobile market accounts for the largest portion in IT industry, and its proportion is increasing rapidly. With the rapid increase, mobile services are also becoming bigger and more complex. Therefore, with the development of network technology such as 5G, there exist on-going research on mobile services that follows client-server models capable of overcoming the limitations of computational performance and storage in mobile devices.
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References
SBD, Connected Car Global Forecast 2015 (2015)
H. Shimada, A. Yamaguchi, H. Takada, K. Sato, Implementation and Evaluation of Local Dynamic Map in Safety Driving Systems. J. Transp. Technol. 5 (2015)
CARASSO (Online), https://aws.amazon.com/solutions/case-studies/bmw
Compass4D (Online), http://www.compass4d.eu
Drivenet (Online), http://drivenet.pilotlab.co
SAFESPOT (Online), www.safespot-eu.org
Blue Link (Online), http://bluelink.hyundai.com
iDrive (Online), http://www.bmw.com/com/en/insights/technology/technology_guide/articles/idrive.html
Uconnect (Online), http://www.driveuconnect.com
Android Auto (Online), https://www.android.com/auto
CarPlay (Online), http://www.apple.com/ios/carplay
Dragon Drive (Online), http://www.nuance.com/for-business/mobile-solutions/dragon-drive/index.htm
Sirius (Online), http://sirius.clarity-lab.org/
S. Kumar, S. Gollakota, D. Katabi, A cloud-assisted design for autonomous driving, in Proceedings of MCC’12
A. Ashok, P. Steenkiste, F. Bai, Enabling vehicular applications using cloud services through adaptive computation offloading, in Proceedings of MCS’12
Pivotal (Online), https://pivotal.io
Blind Motion (Online), https://blindmotion.github.io/2015/04/11/ml-in-navigation
K. Kumar, Y.H. Lu, Cloud computing for mobile users: can offloading computation save energy? Computer 43(4) (2010)
E. Lagerspetz, S. Tarkoma, Mobile search and the cloud: the benefits of offloading, in Proceedings of PERCOM Workship (2011)
S. Kosta, A. Aucinas, P. Hui, R. Mortier, X. Zhang, ThinkAir: dynamic resource allocation and parallel execution in the cloud for mobile code offloading, in Proceedings of INFOCOM’12
A. Saarinen, M. Siekkinen, Y. Xiao, J.K. Nurminen, M. Kemppainen, P. Hui, SmartDiet: offloading popular apps to save energy, in Proceedings of SIGCOMM’12
S. Simanta, G.A. Lewis, E. Morris, K. Ha, M. Satyanarayanan, A reference architecture for mobile code offload in hostile environments, in Proceedings of WICSA’12
M.V. Barbera, S. Kosta, A. Mei, J. Stefa, To offload or not to offload? The bandwidth and energy costs of mobile cloud computing, in Proceedings of INFOCOM’13
Y. Nimmagadda, K. Kumar, Y.H. Lu, C.S.G. Lee, Real-time moving object recognition and tracking using computation offloading, in Proceedings of IROS’10
M.Y. Ra, A. Sheth, L. Mummert, P. Pillai, D. Wetherall, R. Govindan, Odessa: enabling interactive perception applications on mobile devices, in Proceedings of MobiSys’11
Y. Zhang, H. Liu, L. Jiao, X. Fu, To offload or not to offload: an efficient code partition algorithm for mobile cloud computing, in Proceedings of ClOUDNET’12
H. Flores, S. Srirama, Adaptive code offloading for mobile cloud applications: exploiting fuzzy sets and evidence-based learning, in Proceedings of MCS’13
F. Xia, F. Ding, J. Li, X. Kong, L.T. Yang, J. Ma, Phone2Cloud: Exploiting computation offloading for energy saving on smartphones in mobile cloud computing. Inf. Syst. Front. 16(1) (2014)
P. Cooper, U. Dolinsky, A.F. Donaldson, A. Richards, C. Riley, G. Russell, Offload—automating code migration to heterogeneous multicore systems, in Proceedings of HiPEAC’10
H.Y. Chen, Y.H. Lin, C.M. Cheng, COCA: computation offload to clouds using AOP, in Proceedings of CCGrid’12
M.S. Gordon, D.A. Jamshidi, S. Mahlke, Z. M. Mao, X. Chen, COMET: Code Offload by Migrating Execution Transparently, in Proceedings of OSDI’12
D. Huang, P. Wang, D. Niyato, A dynamic offloading algorithm for mobile computing. IEEE Trans. Wireless Commun. 11(6) (2012)
E. Cuervo, A. Balasubramanian, D.K. Cho, A. Wolman, S. Saroiu, R. Chandra, P. Bahl, MAUI: making smartphones last longer with code offload, in Proceedings of MobiSys’10
B.G. Chun, S. Ihm, P. Maniatis, M. Naik, A. Patti, Clonecloud: elastic execution between mobile device and cloud, in Proceedings of EuroSys’11
D. Kovachev, T. Yu, R. Klamma, Adaptive computation offloading from mobile devices into the cloud, in Proceedings of ISPA’12
Y. Zhang, G. Huang, X. Liu, W. Zhang, H. Mei, S. Yang, Refactoring android java code for on-demand computation offloading, in Proceedings of OOPSLA’12
H. Wu, Q. Wang, K. Wolter, Tradeoff between performance improvement and energy saving in mobile cloud offloading systems, in Proceedings of ICC’13
C. Shi, K. Habak, P. Pandurangan, M. Ammar, M. Naik, E. Zegura, COSMOS: computation offloading as a service for mobile devices, in Proceedings of MobiHoc’14
B. Zhou et al., A context sensitive offloading scheme for mobile cloud computing service, in Proceedings of CLOUD’15
H. Kim, J. Han, S.-H. Kim, J. Choi, D. Yoon, M. Jeon, E. Yang, N. Pham, S. Woo, D. Kim, C.-H. Youn, IsV2C: an integrated road traffic-network-cloud simulator for V2C connected car services, submitted to SCC’17
OpenStreetMap (Online), http://www.openstreetmap.org/
SUMO (Online), http://www.sumo.dlr.de/
ns-3 (Online), http://www.nsnam.org/
Lena (Online), http://networks.cttc.es/mobile-networks/software-tools/lena/
Amazon EC2 (Online), htttp://aws.amazon.com/ec2
Google Compute Engine (Online), http://cloud.google.com
Microsoft Azure (Online), http://azure.microsoft.com
J. Hamilton, Cost of power in large-scale data centers, Keynote, at ACM SIGMETRICS 2009 (Online), http://perspectives.mvdirona.com/2008/11/cost-of-power-in-large-scale-data-centers
Universal Mobile Telecommunications System (UMTS); Packet Data Convergence Protocol (PDCP) specification, Technical Specification, ETSI TS 125 323 V5.0.0 (2002)
X. Zhang, Z. Hu, X. Du, Probabilistic inverse simulation and its application in vehicle accident reconstruction. J. Mech. Des. 135(12) (2013)
T. Flessa, E. McGookin, D. Thomson, Numerical stability of inverse simulation algorithms applied to planetary rover navigation, in Proceedings of MED’16
Y. Liu, J. Jiang, Inverse dynamics of vehicle minimum time manoeuvre for collision avoidance problem. Int. J. Vehicle Saf. 9(2) (2016)
S.I. You, J.Y.J. Chow, S.G. Ritchie, Inverse vehicle routing for activity-based urban freight forecast modeling and city logistics. Transp. A Transport Sci. 12(7) (2016)
L. Zha, D. Lord, Y. Zou, The Poisson inverse Gaussian (PIG) generalized linear regression model for analyzing motor vehicle crash data. J. Transp. Saf. Secur. 8(1) (2016)
OpenStack (Online), http://www.openstack.org/
Naver MAPS API (Online), http://navermaps.github.io/maps.js/
Cisco, Cisco visual networking index: forecast and methodology (2015) (Online), http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/complete-white-paper-c11-481360.html
C. Jennings, A. Narayanan, D. Burnett, A. Bergkvist, WebRTC 1.0: Real-time communication between browsers, W3C, W3C Ed. Draft. Aug, no. May, 2014
M. Baugher, D. McGrew, M. Naslund, E. Carrara, and K. Norrman, The Secure Real-time Transport Protocol (SRTP). Internet Soc. RFC 3711 1, 1–56 (2004)
F. Wang, J. Liu, M. Chen, CALMS: Cloud-assisted live media streaming for globalized demands with time/region diversities, in Proceedings of INFOCOM’12
A. Amirante, T. Castaldi, L. Miniero, S.P. Romano, Janus: a general purpose WebRTC gateway, in Proceedings of the Conference on Principles, Systems and Applications of IP Telecommunications, (2014), pp. 7:1–7:8
W.-J. Kim, H. Jang, G.-B. Choi, I.-S. Hwang, C.-H. Youn, A WebRTC based live streaming service platform with dynamic resource provisioning in cloud, in Proceedings of TENCON’16
Docker (Online), https://www.docker.com
RabbitMQ (Online), https://www.rabbitmq.com
Docker-Swarm (Online), https://www.docker.com/products/docker-swarm
cAdvisor (Online), https://github.com/google/cadvisor
influxDB (Online), https://influxdata.com/
E. Diaconescu, The use of NARX neural networks to predict chaotic time series. WSEAS Trans. Comput. Res. 3(3), 182–191 (2008)
S. Dutta, T. Taleb, A. Ksentini, QoE-aware elasticity support in cloud-native 5G systems, in Proceedings of ICC’16
Amazon EC2, https://aws.amazon.com/ko/directconnect
R. Wang, M. Xue, K. Chen, Z. Li, T. Dong, Y. Sun, BMA: Bandwidth allocation management for distributed systems under cloud gaming, in ICCSN (2015)
X. Qi, Q. Yang, D. Nguyen, G. Zhou, G. Peng, LBVC: towards low-bandwidth video chat on smartphones, in MMSys (2015)
H. Madhyastha, T. Anderson, A. Krishnamurthy, N. Spring, A. Venkataramani, A structural approach to latency prediction, in SIGCOMM (2006)
Y. Wu, B. Li, L. Zhang, Z. Li, F.C.M. Lau, Scaling social media applications into geo-distributed clouds. IEEE/ACM Trans. Networking 23(3) (2015)
H. Kim, J. Han, S.-H. Kim, J. Choi, D. Yoon, M. Jeon, E. Yang, N. Pham, S. Woo, D. Kim, C.-H. Youn, IsV2C: an integrated road traffic-network-cloud simulator for V2C connected car services, in submitted to SCC’17
H. Shimada, A. Yamaguchi, H. Takada, Implementation and evaluation of local dynamic map in safety driving systems. J. Transp. Technol. 5, 102–112 (2015). (April)
J. Hauswald, L. Tang, J. Mars, M.A. Laurenzano, Y. Zhang, C. Li, A. Rovinski, A. Khurana, R.G.G. Dreslinski, T. Mudge, V. Petrucci, Sirius: an open end-to-end voice and vision personal assistant and its implications for future warehouse scale computers, in Proceedings of ASPLOS’15
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Youn, CH., Chen, M., Dazzi, P. (2017). A Cloud Broker System for Connected Car Services with an Integrated Simulation Framework. In: Cloud Broker and Cloudlet for Workflow Scheduling. KAIST Research Series. Springer, Singapore. https://doi.org/10.1007/978-981-10-5071-8_4
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DOI: https://doi.org/10.1007/978-981-10-5071-8_4
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