隨著科技不斷的進步，行動裝置不斷推出新機種，讓使用者願意購買去體驗在軟硬體方面的效能，多年過後，就可能累積不同運算能力的行動裝置了。
在此研究中，我們將使用多個異質行動裝置和一個無線寬頻分享器組成一個MapReduce架構，透過這個架構不只可以控制各個裝置，也可以在單機或多機裝置上執行不同的應用程式。MapReduce架構結合使用多Thread做平行運算與負載平衡的方法，與任一裝置相較之下效能有所改善。在實驗中，我們除了在4種不同類型的行動裝置上執行兩個應用程式去統計字數和質數外，也在電腦上執行，並以此當作基準來比較，根據實驗的結果證明可行性和針對異質性行動裝置的MapReduce架構的效率。

With the advance of science and technology, mobile devices continue to introduce new models, so that users are willing to buy to experience in hardware and software performance. After some years, users could accumulate different computing capability of mobile devices. In the thesis, we will use heterogeneous mobile devices and a wireless router to build a MapReduce framework. Through the MapReduce framework, we not only can control each mobile device but also execute different applications in single mobile device or multiple mobile devices. The MapReduce framework can combine a multi-thread parallel computing with a load balance method to improve the performance when compared to any single mobile device. In the experiments, we will run two applications to count word and prime numbers under 4 different types of mobile devices. We will also run the two applications on a PC as a baseline comparison. According to the experimental results, we can demonstrate the feasibility and efficiency of the MapReduce framework for heterogeneous mobile devices.

[1]Jeffrey Dean and Sanjay Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters", Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation, San Francisco, CA, pp. 137-149 (2004)
[2]Fei Teng, Lei Yu, and Frèdèric Magoulès, "SimMapReduce: A simulator for modeling MapReduce framework", Proceedings of International Conference on Multimedia and Ubiquitous Engineering, Loutraki, Greece, pp. 277–282 (2011)
[3]Spiros Papadimitrious and Jimeng Sun, "DisCo: Distributed Co-clustering with Map-Reduce: A case study towards petabyte-scale end-to-end mining", Proceedings of the 8th IEEE International Conference on Data Mining, Pisa, Italy, pp. 512-521 (2008)
[4]Colby Ranger, Ramanan Raghuraman, Arun Penmetsa, Gary Bradski, and Christos Kozyrakis, "Evaluating MapReduce for Multi-core and Multiprocessor systems", Proceedings of the IEEE 13th International Symposium on High Performance Computer Architecture, Phoenix, Arizona, pp. 205-218 (2007)
[5]Marc de Kruijf and Karthikeyan Sankaralingam, "MapReduce for the Cell broadband engine architecture", IBM Journal of Research and Development, Vol. 53, No. 5, pp. 747-758 (2009)
[6]Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govindaraju, and Tuyong Wang, "Mars: A MapReduce Framework on Graphics Processors", Proceedings of the 17th international conference on Parallel architectures and compilation techniques, New York, NY, USA, pp. 260-269 (2008)
[7]David Dearman and Jeffrey S. Pierce, "It’s on my other computer!”: Computing with Multiple Devices", Proceedings of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems, Florence, Italy, pp. 767-776 (2008)
[8]Adam Dou, Vana Kalogeraki, Dimitrios Gunopulos, Taneli Mielikainen, and Ville H. Tuulos, "Misco: A MapReduce Framework for Mobile Systems", Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments, Samos, Greece (2010)
[9]Adam Ji Dou, Vana Kalogeraki, Dimitrios Gunopulos, Taneli Mielikinen, Ville Tuulos, Sean Foley, and Curtis Yu, "Data Clustering on a Network of Mobile Smartphones", Proceedings of the 2011 IEEE/IPSJ International Symposium on Applications and the Internet, Munich, Bavaria, Germany, pp. 118-127 (2011)
[10]Theofilos Kakantousis, Ioannis Boutsis, Vana Kalogeraki, Dimitrios Gunopulos, Giorgos Gasparis and Adam Dou, "Misco: A System for Data Analysis Applications on Networks of Smartphones using MapReduce", Proceedings of the 2012 IEEE 13th International Conference on Mobile Data Management, Bengaluru, India, pp. 356-359 (2012)
[11]Adam J. Dou, Vana Kalogeraki, Dimitrios Gunopulos, Taneli Mielikainen and Ville Tuulos, "Scheduling for Real-Time Mobile MapReduce Systems", Proceedings of the 5th ACM international conference on Distributed event-based system, New York, NY, pp. 247-358 (2011)
[12]Yang Liu, Maozhen Li, Nasullah Khalid Alham, Suhel Hammoud and Mahesh Ponraj, "Load balancing in MapReduce environments for data intensive applications", Proceedings of the Eighth International Conference on Fuzzy Systems and Knowledge Discovery, Shanghai, China, pp. 2675-2678 (2011)
[13]Taj Alam and Zahid Raza, "A Dynamic Load Balancing Strategy with Adaptive Threshold Based Approach", Proceedings of the 2012 2nd IEEE International Conference on Parallel Distributed and Grid Computing, Solan, India, pp. 927-932 (2012)
[14]Zhenhua Guo, Marlon Pierce, Geoffrey Fox, and Mo Zhou, "Automatic Task Re-organization in MapReduce", Proceedings of the 2011 IEEE International Conference on Cluster Computing, Austin, Texas, pp. 335-343 (2011)
[15] Hsin-Yu Shih, Jhih-Jia Huang and Jenq-Shiou Leu, "Dynamic Slot-based Task Scheduling Based on Node Workload in a MapReduce Computation Model", Proceedings of the 2012 International Conference on Anti-Counterfeiting, Security and Identification, Taipei, Taiwan (2012)
[16]Jeremy Singer, George Kovoor, Gavin Brown and Mikel Luján, "Garbage collection auto-tuning for Java mapreduce on multi-cores", Proceedings of the 2011 international symposium on Memory management, San Jose, California, pp. 109-118 (2011)
[17]"Android architecture", [Online], https://source.android.com/tech/security/
[18]"Android Developers", [Online], http://developer.android.com/
[19]"MapReduce Tutorial", [Online], http://hadoop.apache.org/docs/stable/mapred_tutorial.html
[20]"Java SE Technical Documentation", [Online], http://docs.oracle.com/javase/
[21] Hsueh-Yi Chung, Che-Wei Chang ; Hung-Chang Hsiao ; Yu-Chang Chao, "The Load Rebalancing Problem in Distributed File Systems", Proceedings of the 2012 IEEE International Conference on Cluster Computing, Beiling, China, pp. 117-125 (2012)
[22]Peter R. Elespuru, Sagun Shakya, and Shivakant Mishra, "MapReduce System over Heterogeneous Mobile Devices", Proceedings of the 7th IFIP WG 10.2 International Workshop on Software Technologies for Embedded and Ubiquitous Systems, Newport Beach, CA, USA, pp. 168-178 (2009)
[23]Suhel Hammoud, Maozhen Li, Yang Liu, Nasullah Khalid Alham, and Zelong Liu, "MRSim: A Discrete Event based MapReduce Simulator", Proceedings of the 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, pp. 2993-2997 (2010)
[24]Jin-Ming Shih, Chih-Shan Liao and Ruay-Shiung Chang, "Simplifying MapReduce Data Processing", Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing, Melbourne, Australia, pp. 366-370 (2011)
[25]Dadan Zeng, "Design and Implementation of a MapReduce Based Framework for Determinant Computation", Proceedings of the 2011 Fourth International Symposium on Knowledge Acquisition and Modeling, Sanya, China, pp. 443-446 (2011)
[26]Seonggun Kim, Heungsoon Rim and Hwansoo Han, "Distributed execution for resource-constrained mobile consumer devices", Journal of IEEE Transactions on Consumer Electronics, Vol. 55, No .2, pp. 376-384 (2009).
[27]Mustafa Y. Arslan, Indrajeet Singh, Shailendra Singh, Harsha V. Madhyastha, Karthikeyan Sundaresan, Srikanth V. Krishnamurthy, "Computing While Charging: Building a Distributed Computing Infrastructure Using Smartphones", Proceedings of the 8th international conference on Emerging networking experiments and technologies, Nice, France, pp. 193-204 (2012)
[28]"HTC Desire", [Online], http://www.android.com/devices/detail/htc-desire
[29]"HTC Incredible S", [Online], http://www.android.com/devices/detail/htc-incredible-s
[30]"Asus Transformer TF101", [Online], http://www.android.com/devices/detail/asus-eee-pad-transformer
[31]"Nexus 7", [Online], http://www.google.com.tw/nexus/#/7/specs
[32]"Corega CG-WLBARN80", [Online], http://driver.corega.com.tw/driverusers/support/download/files/manual/WLBARN80_T30-UM8418-SC_RevA.pdf