Abstract
Network latency is often high on mobile devices due to wireless access, e. g., via 3G cellular networks. To better use the ubiquitously available 3G network connections, we propose a pipelining task concept on a single encrypted channel between a mobile device and a cloud resource. This does not only increases wireless bandwidth occupation, it also makes wireless communication more predictable by assuring a high throughput even for small messages. Constantly high throughput allows for a better data transfer time estimation and can thus lead to a more adequate cloud resource selection to assist the mobile application. In an experimental evaluation using streaming image processing, we investigate the performance and applicability of our approach and compare it to the widely used HTTP.
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References
Guan, L., Ke, X., Song, M., Song, J.: A Survey of Research on Mobile Cloud Computing. In: Proc. of the 10th Int. Conf. on Computer and Information Science (ICIS), pp. 387–392. IEEE (2011)
Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A Survey of Mobile Cloud Computing: Architecture, Applications, and Approaches. Wireless Communications and Mobile Computing (2011)
Chen, D., Tsai, S., Hsu, C., Singh, J., Girod, B.: Mobile Augmented Reality for Books on a Shelf. In: Proc. of the Int. Conf. on Multimedia and Expo. (ICME), pp. 1–6. IEEE (2011)
Girod, B., Chandrasekhar, V., Chen, D., Cheung, N., Grzeszczuk, R., Reznik, Y., Takacs, G., Tsai, S., Vedantham, R.: Mobile Visual Search. IEEE Signal Processing Magazine 28(4), 61–76 (2011)
Chen, D., Tsai, S., Vedantham, R., Grzeszczuk, R., Girod, B.: Streaming Mobile Augmented Reality on Mobile Phones. In: Proc. of the Int. Symp. on Mixed and Augmented Reality (ISMAR), pp. 181–182. IEEE (2009)
Cidon, A., London, T., Katti, S., Kozyrakis, C., Rosenblum, M.: MARS: Adaptive Remote Execution for Multi-Threaded Mobile Devices. In: Proc. of the Workshop on Networking, Systems, and Applications on Mobile Handhelds, pp. 1–6. ACM (2011)
Cuervo, E., Balasubramanian, A., Cho, D., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: Maui: Making Smartphones Last Longer with Code Offload. In: Proc. of the Int. Conf. on Mobile Systems, Applications, and Services, pp. 49–62. ACM (2010)
Kaspar, D., Evensen, K., Engelstad, P., Hansen, A.: Using HTTP Pipelining to Improve Progressive Download over Multiple Heterogeneous Interfaces. In: Proc. of the Int. Conf. on Communications, pp. 1–5. IEEE (2010)
Nixon, M., Aguado, A.: Feature Extraction & Image Processing. Academic Press. Academic (2008)
Hsu, R.L., Abdel-Mottaleb, M., Jain, A.K.: Face Detection in Color Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5), 696–706 (2002)
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Ferber, M., Rauber, T. (2012). Mobile Cloud Computing in 3G Cellular Networks Using Pipelined Tasks. In: De Paoli, F., Pimentel, E., Zavattaro, G. (eds) Service-Oriented and Cloud Computing. ESOCC 2012. Lecture Notes in Computer Science, vol 7592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33427-6_14
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DOI: https://doi.org/10.1007/978-3-642-33427-6_14
Publisher Name: Springer, Berlin, Heidelberg
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