Please wait a minute...
Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2014, Vol. 8 Issue (5) : 847-857    https://doi.org/10.1007/s11704-014-3223-6
RESEARCH ARTICLE
A scheduling algorithm with dynamic properties in mobile grid
JongHyuk LEE1(),SungJin CHOI1,JoonMin GIL3,Taeweon SUH4,HeonChang YU5,*()
1. Software R&D Center, Samsung Electronics, Gyeonggi-do 443-742, Republic of Korea
2. Media Solution Center, Samsung Electronics, Gyeonggi-do 443-742, Republic of Korea
3. School of Information Technology Engineering, Catholic University of Daegu, Gyeongsangbuk-do 712-702, Republic of Korea
4. Graduate School of Information Security, Korea University, Seoul 136-701, Republic of Korea
5. Department of Computer Science and Engineering, Korea University, Seoul 136-701, Republic of Korea
 Download: PDF(581 KB)  
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Mobile grid is a branch of grid computing that incorporates mobile devices into the grid infrastructure. It poses new challenges because mobile devices are typically resource-constrained and exhibit unique characteristics such as instability in network connections. New scheduling strategies are imperative in mobile grid to efficiently utilize the devices. This paper presents a scheduling algorithm that considers dynamic properties of mobile devices such as availability, reliability, maintainability, and usage pattern in mobile grid environments. In particular, usage patterns caused by voluntarily or involuntarily losing a connection, such as switching off the device or a network interruption could be important criteria for choosing the best resource to execute a job. The experimental results show that our scheduling algorithm provides superior performance in terms of execution time, as compared to the other methods that do not consider usage pattern. Throughout the experiments, we found it essential to consider usage pattern for improving performance in the mobile grid.

Keywords mobile grid      scheduling      dynamic properties      availability      reliability      maintainability      usage pattern     
Corresponding Author(s): HeonChang YU   
Issue Date: 11 October 2014
 Cite this article:   
JongHyuk LEE,SungJin CHOI,JoonMin GIL, et al. A scheduling algorithm with dynamic properties in mobile grid[J]. Front. Comput. Sci., 2014, 8(5): 847-857.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-014-3223-6
https://academic.hep.com.cn/fcs/EN/Y2014/V8/I5/847
1 Foster I, Kesselman C. The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, 2004
2 Muthuvelu N, Chai I, Chikkannan E, Buyya R. Batch resizing policies and techniques for fine-grain grid tasks: the nuts and bolts. The Journal of Information Processing Systems, 2011, 7(2): 299-320
https://doi.org/10.3745/JIPS.2011.7.2.299
3 Kurdi H, Li M, Al-Raweshidy H. A classification of emerging and traditional grid systems. IEEE Distributed Systems Online, 2008, 9(3). Article No. 0001
https://doi.org/10.1109/MDSO.2008.8
4 Lee J, Song S, Gil J, Chung K, Suh T, Yu H. Balanced scheduling algorithm considering availability in mobile grid. In: Proceedings of the 4th Intern<?Pub Caret?>ational Conferemce on Advances in Grid and Pervasive Computing. 2009, 211-222
https://doi.org/10.1007/978-3-642-01671-4_20
5 Park S M, Ko Y B, Kim J H. Disconnected operation service in mobile grid computing. In: Proceedings of the International Conference on Service Oriented Computing. 2003, 499-513,
6 Balazinska M, Castro P. Characterizing mobility and network usage in a corporate wireless local-area network. In: Proceedings of the 1st International Conference on Mobile Systems, Applications, and Services. 2003, 303-316
https://doi.org/10.1145/1066116.1066127
7 Casanova H, Legrand A, Quinson M. SimGrid: a generic framework for large-scale distributed experiments. In: Proceedings of the 10th IEEE International Conference on Computer Modeling and Simulation. 2008, 126-131
8 Yeo J, Kotz D, Henderson T. A community resource for archiving wireless data at dartmouth. ACM SIGGOMM Computer Communication Review, 2006, 36(2): 21-22
https://doi.org/10.1145/1129582.1129588
9 Rodrigues J M, Zunino A, Campo M. Introducing mobile devices into grid systems: a survey. International Journal ofWeb and Grid Services, 2011, 7(1): 1-40
10 Huang C Q, Zhu Z T, Wu Y H, Xia Z H. Power-aware hi-erarchical scheduling with respect to resource intermittence in wireless grids. In: Proceedings of the 5th International Conference on Machine Learning and Cybernetics. 2006, 693-698
11 Li C, Li L. Collaboration among mobile agents for efficient energy allocation in mobile grid. Information Systems Frontiers, 2012, 14(3): 711-723
https://doi.org/10.1007/s10796-011-9298-9
12 Lee J, Choi S, Suh T, Yu H, Gil J. Group-based scheduling algorithm for fault tolerance in mobile grid. Communications in Computer and Information Science, 2010, 78: 394-403
https://doi.org/10.1007/978-3-642-16444-6_49
13 Farooq U, Khalil W. A generic mobility model for resource prediction in mobile grids. In: Proceedings of the International Symposium on Collaborative Technologies and Systems. 2006, 189-193
https://doi.org/10.1109/CTS.2006.7
14 Ghosh P, Roy N, Das S K. Mobility-aware efficient job scheduling in mobile grids. In: Proceedings of the 7th IEEE International Symposium on Cluster Computing and the Grid. 2007, 701-706
15 Xu Y Q, Yin M. A mobility-aware task scheduling model in mobile grid. Applied Mechanics and Materials, 2013, 336-338: 1786-1791
https://doi.org/10.4028/www.scientific.net/AMM.336-338.1786
16 Jiang Q, Wu X, Yang H. Task scheduling based on genetic algorithm in mobile grid. In: Proceedings of the Computer Science & Service System. 2012, 719-722
17 Litke A, Skoutas D, Tserpes K, Varvarigou T. Efficient task replication and management for adaptive fault tolerance in mobile grid environments. Future Generation Computer Systems, 2007, 23(2): 163-178
https://doi.org/10.1016/j.future.2006.04.014
[1] Jinwei GUO, Peng CAI, Weining QIAN, Aoying ZHOU. Accurate and efficient follower log repair for Raft-replicated database systems[J]. Front. Comput. Sci., 2021, 15(2): 152605-.
[2] Han Yao HUANG, Kyung Tae KIM, Hee Yong YOUN. Determining node duty cycle using Q-learning and linear regression for WSN[J]. Front. Comput. Sci., 2021, 15(1): 151101-.
[3] Zeinab ASKARI, Avid AVOKH. EMSC: a joint multicast routing, scheduling, and call admission control in multi–radio multi–channel WMNs[J]. Front. Comput. Sci., 2020, 14(5): 145503-.
[4] Libing WU, Lei NIE, Samee U. KHAN, Osman KHALID, Dan WU. A V2I communication-based pipeline model for adaptive urban traffic light scheduling[J]. Front. Comput. Sci., 2019, 13(5): 929-942.
[5] Lin WANG, Depei QIAN, Rui WANG, Zhongzhi LUAN, Hailong YANG, Huaxiang ZHANG. A novel index system describing program runtime characteristics for workload consolidation[J]. Front. Comput. Sci., 2019, 13(3): 489-499.
[6] Yihong GAO, Huadong MA. StreamTune: dynamic resource scheduling approach for workload skew in video data center[J]. Front. Comput. Sci., 2018, 12(4): 669-681.
[7] Yu TANG,Hailong SUN,Xu WANG,Xudong LIU. An efficient and highly available framework of data recency enhancement for eventually consistent data stores[J]. Front. Comput. Sci., 2017, 11(1): 88-104.
[8] Mei BAI,Junchang XIN,Guoren WANG,Roger ZIMMERMANN,Xite WANG. Skyline-join query processing in distributed databases[J]. Front. Comput. Sci., 2016, 10(2): 330-352.
[9] Qi WANG,Donghui WANG,Chaohuan HOU. Exploiting write power asymmetry to improve phase change memory system performance[J]. Front. Comput. Sci., 2015, 9(4): 566-575.
[10] Xite WANG,Derong SHEN,Mei BAI,Tiezheng NIE,Yue KOU,Ge YU. SAMES: deadline-constraint scheduling in MapReduce[J]. Front. Comput. Sci., 2015, 9(1): 128-141.
[11] Najme MANSOURI. Network and data location aware approach for simultaneous job scheduling and data replication in large-scale data grid environments[J]. Front. Comput. Sci., 2014, 8(3): 391-408.
[12] Kok-Lim Alvin YAU, Kae Hsiang KWONG, Chong SHEN. Reinforcement learning models for scheduling in wireless networks[J]. Front Comput Sci, 2013, 7(5): 754-766.
[13] Huafeng YU, Yue MA, Thierry GAUTIER, Lo?c BESNARD, Jean-Pierre TALPIN, Paul Le GUERNIC, Yves SOREL. Exploring system architectures in AADL via Polychrony and SynDEx[J]. Front Comput Sci, 2013, 7(5): 627-649.
[14] Kenli LI, Zhao TONG, Dan LIU, Teklay TESFAZGHI, Xiangke LIAO. A PTS-PGATS based approach for data-intensive scheduling in data grids[J]. Front Comput Sci Chin, 2011, 5(4): 513-525.
[15] Zheng LIU, Heng DAI, Farouk ALKADHI, Jufeng DAI, . An effective scheduling scheme for multi-hop multicast in wireless mesh networks[J]. Front. Comput. Sci., 2010, 4(1): 135-142.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed