Skip to main content
SpringerLink
Log in

A scheduling algorithm with dynamic properties in mobile grid

  • Research Article
  • Published:
Frontiers of Computer Science Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Foster I, Kesselman C. The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, 2004

    Google Scholar 

  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

    Article  Google Scholar 

  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

    Google Scholar 

  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 International Conferemce on Advances in Grid and Pervasive Computing. 2009, 211–222

    Chapter  Google Scholar 

  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.

    Google Scholar 

  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

    Chapter  Google Scholar 

  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

    Google Scholar 

  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

    Article  Google Scholar 

  9. Rodrigues J M, Zunino A, Campo M. Introducing mobile devices into grid systems: a survey. International Journal of Web and Grid Services, 2011, 7(1): 1–40

    Article  Google Scholar 

  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

    Google Scholar 

  11. Li C, Li L. Collaboration among mobile agents for efficient energy allocation in mobile grid. Information Systems Frontiers, 2012, 14(3): 711–723

    Article  Google Scholar 

  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

    Article  Google Scholar 

  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

    Chapter  Google Scholar 

  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

    Google Scholar 

  15. Xu Y Q, Yin M. A mobility-aware task scheduling model in mobile grid. Applied Mechanics and Materials, 2013, 336–338: 1786–1791

    Article  Google Scholar 

  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

    Google Scholar 

  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

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Samsung Electronics, Software R&D Center, Gyeonggi-do, 443-742, Republic of Korea

    JongHyuk Lee

  2. Media Solution Center, Samsung Electronics, Gyeonggi-do, 443-742, Republic of Korea

    SungJin Choi

  3. School of Information Technology Engineering, Catholic University of Daegu, Gyeongsangbuk-do, 712-702, Republic of Korea

    JoonMin Gil

  4. Graduate School of Information Security, Korea University, Seoul, 136-701, Republic of Korea

    Taeweon Suh

  5. Department of Computer Science and Engineering, Korea University, Seoul, 136-701, Republic of Korea

    HeonChang Yu

Authors
  1. JongHyuk Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. SungJin Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. JoonMin Gil
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Taeweon Suh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. HeonChang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to HeonChang Yu.

Additional information

JongHyuk Lee received his PhD degree of computer science education from Korea University where he did research in distributed systems. He was previously a research professor at Korea University, and a research scientist at University of Houston. Currently, he is employed as a senior engineer by Samsung Electronics. In the past, he authored and co-authored over publications covering research problems in distributed systems, computer architecture & systems, mobile computing, p2p computing, grid computing, cloud computing, computer security, and computer science education.

SungJin Choi received his PhD degree of computer science from Korea University. He was a post-doctoral researcher in University of Melbourne. He was a research processor in Intelligent HCI Convergence Research Center, Sungkyunkwan University. Currently, he is working at Samsung Electronics. His research interests include mobile agent, peer-to-peer computing, grid computing, cloud computing and distributed systems.

JoonMin Gil received his BS and MS degrees in computer science from Korea University, Korea in 1994 and 1996, respectively. He received his PhD degree in computer science and engineering from Korea University, Korea in 2000. From 2001 to 2002, he was a visiting research associate in the Department of Computer Science at University of Illinois at Chicago, USA. From October 2002 to February 2006, he was a senior research engineer in Supercomputing Center at Korea Institute of Science and Technology Information, Korea. He joined Catholic University of Daegu in March 2006, where he is currently an associate professor in the School of Information Technology Engineering. His recent research interests include cloud computing, grid computing, fault-tolerances, and wireless & sensor networks.

Taeweon Suh is an associate professor in the Graduate School of Information Security, Korea University. Prior to joining academia, he was a systems engineer at Intel Corporation in Hillsboro, Oregon, USA. His research interests include embedded systems, computer architecture, multiprocessor and virtualization. He has a BS degree in electrical engineering from the Korea University, Korea, and anMS degree in electronics engineering from the Seoul National University, Korea, and a PhD degree in computer engineering from the Georgia Institute of Technology, USA. He is a member of ACM and IEEE.

HeonChang Yu received the BS, MS, and PhD degrees in computer science and engineering from Korea University, Seoul, Korea in 1989, 1991, and 1994, respectively. He has been a professor of computer science and engineering with Korea University since 1998. From February 2011 to January 2012, he was a visiting professor of electrical and computer engineering in Virginia Technology. Since 2011, he has been the director of Korea Information Processing Society, Korea. Prof. Yu was the vice president of the Korean Association of Computer Education and an editor of the Korean Institute of Information Scientists and Engineers. He was awarded the Okawa Foundation Research Grant of Japan in 2008. His research interests include cloud computing, grid computing, distributed computing, and fault-tolerant systems.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, J., Choi, S., Gil, J. et al. A scheduling algorithm with dynamic properties in mobile grid. Front. Comput. Sci. 8, 847–857 (2014). https://doi.org/10.1007/s11704-014-3223-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11704-014-3223-6

Keywords

Search

Navigation