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Load Balancing and Job Migration Techniques in Grid: A Survey of Recent Trends

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Abstract

Grid computing has recently become one of the most important research topics in the field of computing. The Grid computing paradigm has gained popularity due to its capability to offer easier access to geographically distributed resources operating across multiple administrative domains. The grid environment is considered as a combination of dynamic, heterogeneous and shared resources in order to provide faster and reliable access to the Grid resources, the resource overloading must be prevented which can be obtained by proper load balancing and job migration mechanisms. This paper presents an extensive survey of the existing load balancing and job migration techniques proposed so far. A detailed classification has also been included based on different parameters which are depending on the analysis of the existing techniques, a new Load balancing technique, along with Job Migration approach has been proposed and discussed to fulfill the existing research gaps.

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References

  1. Foster, I., Kesselman, C., & Tuecke, S. (2001). The anatomy of the grid: Enabling scalable virtual organization. International Journal of High Performance Computing Applications, 15(3), 200–222.

    Article  Google Scholar 

  2. Berman, F., Fox, G., & Hey, A. J. (2003). Grid computing: Making the global infrastructure a reality. New York: Wiley.

    Book  Google Scholar 

  3. Rathore, N. K., & Chana, I., Dr. (2013). A sender initiate based hierarchical load balancing technique for grid using variable threshold value. In International conference IEEE-ISPC (pp. 1–6), ISBN-978-1-4673-6188-0.

  4. Lu, K., & Zomaya, A. Y. (2007). A hybrid policy for job scheduling and load balancing in heterogeneous computational grids. In Sixth international symposium on parallel and distributed computing (ISPDC’07), IEEE.

  5. Shan, H., Oliker, L., Biswas, R., & Smith, W. (2004). Scheduling in heterogeneous grid environments: The effects of data migration. In Proceedings of the ADCOM2004: International conference advanced computing and communication, Ahmedabad Gujarat, India.

  6. Balasangameshwara, J., & Raju, N. (2012). A hybrid policy for fault tolerant load balancing in grid computing environments. Journal of Network and Computer Applications, 35, 412–422.

    Article  Google Scholar 

  7. Kumar, P., Setiya, R., & Gahlan, P. (2009). Checkpointing algorithms for distributed systems. In TECHNIA—international journal of computing science and communication technologies (vol. 2, no.1), ISSN 0974-3375.

  8. Zhang, Y., Franke, H., Moreira, J. E., & Sivasubramaniam, A. (2000). The impact of migration on parallel job scheduling for distributed systems. In Euro-Par 2000 Parallel Processing, Lecture Notes in Computer Science (Vol. 1900, pp. 242–251).

  9. Nazir, B., Qureshi, K., & Manuel, P. (2009). Adaptive checkpointing strategy to tolerate faults in economy based grid. The Journal of Supercomputing, 50(1), 1–18.

  10. Qureshi, K., & Manuel, P. (2007). Adaptive pre-task scheduling strategy for heterogeneous distributed ray-tracing system. International Journal of Computer and Electrical Engineering, 33, 70–78.

    Article  MATH  Google Scholar 

  11. Mishra, S., Kushwaha, D. S., & Misra, A. K. (2010). An efficient job scheduling technique in trusted clusters for load balancing. In The first international conference on cloud computing, GRIDs, and virtualization: Cloud computing.

  12. Mehta, H. K., Chandwani, M., & Kanungo, P. (2010). A modified delay strategy for dynamic load balancing in cluster and grid environment, IEEE.

  13. Rathore, N. K., & Chana, I. (2014). Variable threshold based hierarchical load balancing technique in grid. In Engineering with computers. Springer, Berlin. ISSN: 0177-0667 (print version) ISSN: 1435-5663 (electronic version). doi:10.1007/s00366-014-0364-z.

  14. Lin, H. C., & Raghavendra, C. S. (1992). A dynamic load-balancing policy with a central job dispatcher (LBC). IEEE Transaction on Software Engineering, 18(2), 148–158.

    Article  Google Scholar 

  15. El-Zoghdy, S. F. (2012). A hierarchical load balancing policy for grid computing environment. International Journal of Computer Network and Information Security, 5, 1–12.

    Article  Google Scholar 

  16. Rathore, N. K., & Chana, I. (2011). A cogitative analysis of load balancing technique with job migration in grid environment. In IEEE proceedings paper (pp 77–82). World Congress on Information and Communication Technology (WICT), Mumbai, ISBN -978-1-4673-0127-5.

  17. Prakash, S., & Vidyarthi, D. P. (2011). Load balancing in computational grid using genetic algorithm. Advances in Computing: 2011, 1(1), 8–17. doi:10.5923/j.ac.20110101.02.

    Article  Google Scholar 

  18. Benmohammed-Mahieddine, K. (1991). An evaluation of load balancing algorithms for distributed systems. Doctor of Philosophy The University of Leeds.

  19. Peng, L., & **ao, W. (2011). A binary-tree based hierarchical load balancing algorithm in structured peer-to-peer systems. Journal of Convergence Information Technology, 6(4), 42–49.

  20. Xu, Z., & Huang, R. (2009). Performance study of load balancing algorithms in distributed web server systems. In CS213 parallel and distributed processing project report, IJCSIS (vol. 6, No. 1).

  21. Zeng, Z., & Veeravalli, B. (2004) Rate-based and queue-based dynamic load balancing algorithms in distributed systems. In: Proceedings of the 10th IEEE international conference on parallel & distributed systems (pp. 349–356).

  22. Lu, K., Subrata, R., & Zomaya, A. Y. (2006). An efficient load balancing algorithm for heterogeneous grid1 systems considering desirability of grid sites. In Proceedings of the 25th IEEE international conference on performance, computing, and communications.

  23. Rathore, N. K., & Chana, I. (2013). Report on hierarchal load balancing technique in grid environment. International Journal of Scientific and Innovative Technology, i-manager’s Journal on Information Technology, 2(4), 21–35. ISSN Print: 2277-5110, ISSN Online: 2277-5250.

  24. Rathore, N. K. (2014). An efficient hierarchical load balancing technique for grid. In 29th M.P. Young Scientist congress (p. 55), Bhopal, MP.

  25. Raj, J. S., & Fiona, R. (2013). Load balancing technique in grid environment: A survey. In ICCCI-2013, India.

  26. Agarwal, A., & Jain, S. (2014). Efficient optimal algorithm of task scheduling in cloud computing environment. International Journal of Computer Trends and Technology (IJCTT), 9(7), 344, ISSN: 2231-280.

  27. Lin, S.-J., Huang, M.-C., Lai, K.-C., & Huang, K.-C. (2008). Design and implementation of job migration policies in P2P grid system. In Asia-Pacific services computing conference IEEE.

  28. Balasangameshwara, J., & Raju, N. (2010). A fault tolerance optimal neighbor load balancing algorithm for grid environment. In International conference on computational intelligence and communication networks.

  29. Deng, Y., & Lau, R. W. H. (2014). Dynamic load balancing in distributed virtual environments using heat diffusion. ACM Transactions on Multimedia Computing, Communications, and Applications, 10(2), Article 16.

  30. Zhang, J. (2010). Flexible distributed computing with volunteered resources. PhD Thesis, University of London.

  31. Rathore, N. K., & Chana, I., Dr. (2014). Job migration mechanism with fault tolerance and QoS scheduling using hash table functionality in social grid computing. Journal of Intelligent & Fuzzy Systems, 26, (6), 21–35. IOS Press publication, SCI indexed, ISSN print 1064-1246, ISSN online 1875-8967, impact factor 2012-.788.

  32. Rathore, N. K., & Chana, I., Dr. (2008). Comparative analysis of checkpointing, PIMR third national IT conference, IT enabled practices and emerging management paradigm book and category is communication technologies and security issues (pp. 32–35), Topic No/Name-46, Prestige Management and Research, Indore, MP, India.

  33. Rathore, N. K., & Chana, I., Dr. (2010). Checkpointing algorithm in Alchemi.NET. Pragyaan: Journal of Information Technology, 8(1), 32–38. IMS Dehradun. ISSN No.: 0974-5513, IEEE, CSI and MPCET, Dehradun.

  34. Rathore, N. K., & Chana, I., Dr. (2010). Checkpointing algorithm in Alchemi.NET. Lambert Academic Publication House (LBA), Germany ISBN-10: 3843361371, ISBN-13: 978-3843361378.

  35. Rathore, N. K., & Chana, I., Dr. (2010). Fault tolerance checkpointing algorithm in Alchemi.NET Middleware. In National conference on education & research (ConFR10), Third CSI National conference of CSI Division V, Bhopal Chapter, IEEE Bombay, and MPCST Bhopal, organized by JUIT, Guna (MP) India.

  36. Chakravorty, S., Mendes, C. L., & Kale, L. V. (2006). Proactive fault tolerance in MPI applications via task migration, high performance computing, Lecture Notes in Computer Science (Vol. 4297). Berlin: Springer.

    Google Scholar 

  37. Gilly, K., Thomas, N., Juiz, C., & Puigjaner, R. (2008). Scalable QoS content-aware load balancing algorithm for a Web Switch based on classical. AINA 2008, 934–941. doi:10.1109/AINA.2008.75.

  38. Chen, P.-C., Lin, C.-I., Huang, S.-W., Chang, J.-B., Shieh, C.-K., Liang, T.-Y. A performance study of virtual machine migration vs thread migration for grid systems. In 22nd International conference on advanced information networking and applications—workshops.

  39. Kalaiselvi, S., & Rajaraman, V. (2000). A survey of check-pointing algorithms for parallel and distributed computers (vol. 25, Part 5, pp. 489–510).

  40. Kulkarni, P., & Sengupta, I. Load balancing with multiple token policy.

  41. Bawa, R. K., & Singh, R. (2012). Comparative analysis of fault tolerance techniques in grid environment. International Journal of Computer Applications, 41(1), 21–25.

  42. Kun-Ming, V. Y., Chou, C.-H., & Wang, Y.-T. (2004). A fuzzy-based dynamic load-balancing algorithm. Journal of Information, Technology and Society, 4(2), 55–63.

  43. Shan, H., & Oliker, L. (2003). Job superscheduler architecture and performance in computational Grid environments. In Proceedings of the ACM/IEEE SC2003 conference.

  44. Ludwig, S. A., & Moallem, A. (2011). Swarm intelligence approaches for grid load balancing. Journal of Grid Computing, 9, 279–301. doi:10.1007/s10723-011-9180-5.

  45. Long, Q., Lin, J., & Sun, Z. (2011). Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations, China simulation modelling practice and theory (pp. 1021–1034). Tongji University, Shanghai Science Direct Elsevier.

  46. Balasangameshwara, J., & Raju, N. (2010). A decentralized recent neighbour load balancing algorithm for computational grid. International Journal of ACM Jordan, 1(3), ISSN 2078-7952.

  47. Rao, Y., Wang, R.-c. (2010). Agent-based load balancing routing for LEO satellite networks. In Computer networks (pp. 3187–3195). Amsterdam: Elsevier.

  48. Khalouli, S., Ghedjati, F., & Hamzaoui, A. (2010). A meta-heuristic approach to solve a JIT scheduling problem in hybrid flowshop. Engineering Applications of Artificial Intelligence, 23(5), 765–771.

  49. dos Santos Coelho, L., & De Andrade Bernert, D. L. (2010). A modified ant colony optimization algorithm based on differential evolution for chaotic synchronization. Amsterdam: Elsevier.

  50. Afshar, M. H. (2010). A parameter free continuous Ant Colony Optimization Algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach. Advances in Engineering Software, 41, 188–195.

    Article  MATH  Google Scholar 

  51. Ali, A.-D., Belal, M. A., & Al-Zoubi, M. B. (2010). Load balancing of distributed systems based on multiple ant colonies optimization. American Journal of Applied Sciences, 7(3), 433–438, Science Publications.

  52. Bai, L., Hu, Y.-L., Lao, S.-Y., & Zhang, W.-M. (2010). Task scheduling with load balancing using multiple Ant Colonies optimization in grid computing. In Sixth international conference on natural computation (ICNC 2010).

  53. Nasir, H. J. A., Ruhana, K., & Ku-Mahamud. (2010). Grid load balancing using ant colony optimization. In Second international conference on computer and network technology, IEEE ICCNT-2010.

  54. Lidya, A., Therasa, S., Sumathi, G., & Antony Dalya, S. (2010). Dynamic adaptation of checkpoints and rescheduling in grid computing. International Journal of Computer Applications (0975–8887), 2(3).

  55. Cosenza, B., Cordasco, G., De Chiara, R., & Scarano, V. (2010). Distributed load balancing for parallel agent-based simulations. http://www.isislab.it/projects/DistrSteer/Dist. Steer: Parallel Distributed Agent-Based Simulations.

  56. Kim, Y. H., Han, S., Lyu, C. H., & Youn, H. Y. (2009). An efficient dynamic load balancing scheme for multi-agent system reflecting agent workload. In International conference on computational science and engineering.

  57. Saeb, M., & Fathy, C. (2003). Performance evaluation of mobile agent-based dynamic load balancing algorithm. In 9th International Conference on Distributed Multimedia Systems, DMS _ Conference, Data Communication Security, Miami: Mobile Agent Paradigm.

  58. Ana Cortes Fite. (2000). A new distributed diffusion algorithm for dynamic load balancing in parallel systems, Barcelona, Spain.

  59. Saruladha, K., & Santhi, G. (2007) Behavior of agent based dynamic load balancing algorithm for heterogeneous P2P systems. In International conference on computational intelligence and multimedia applications. Pondicherry: Pondicherry Engineering College.

  60. Kontogiannis, S., Valsamidis, S., & Karakos, A. (2011). ALBL, ALBL/HSC algorithms: Towards more scalable, more adaptive and fully utilized balancing systems. Journal of Computing, 3(2), ISSN 2151-9617.

  61. De Grande, R. E., & Boukerche, A. (2011). Dynamic balancing of communication and computation load for HLA-based simulations on large-scale distributed systems. Journal of Parallel and Distributed Computing, 71(1), 40–52.

  62. Sharma, D., & Saxena, A. B. (2011). Framework to solve load balancing problem in heterogeneous web servers. International Journal of Computer Science & Engineering Survey, 2(1), 50–63.

  63. Hsiao, H.-C., Liao, H., Chen, S.-T., Huang, K.-C. (2011). Member, IEEE Computer Society, Liao, H., Chen, S.-T., Huang, K.-C. (2011). Load balance with imperfect information in structured peer-to-peer systems. IEEE Transactions on Parallel and Distributed Systems, 22(4), 634–649.

  64. El Kabbany, G. F., Wanas, N. M., Hegazi, N. H., & Shaheen, S. I. (2010). A dynamic load balancing framework for real-time applications in message passing systems. Berlin: Springer.

  65. Suri, P. K., & Singh, M. (2010). An efficient decentralized load balancing algorithm for grid, IEEE.

  66. Lin, W., Shen, W. (2010). Tree-based task scheduling model and dynamic load-balancing algorithm for P2P computing. In 10th IEEE International Conference on Computer and Information Technology (CIT 2010). South China University of Technology, Guangzhou, China.

  67. Abdi, S., & Mohamadi, S. (2010). The impact of data replication on job scheduling performance in hierarchical data grid. In International journal on applications of graph theory in wireless ad hoc networks and sensor networks (GRAPH-HOC) (vol. 2, no. 3).

  68. Nandagopal, M., & Uthariaraj, R. V. (2010). Hierarchical status information exchange scheduling and load balancing for computational grid environments. International Journal of Computer Science and Network Security, 10(2), 177–185.

  69. Nandagopal, M., Gokulnath, K., & Uthariaraj, V. R. (2010). Sender initiated decentralized dynamic load balancing for multi cluster computational grid environment, A2CWiC.

  70. Zheng, G., Bhatelé, A., Meneses, E., & Kalé, L. V. (2011). Periodic hierarchical load balancing for large supercomputers. International Journal of High Performance Computing Applications, 25(4), 371–385.

  71. Wang, B., & Shen, Q.-g. (2010). ID management and allocation algorithm for P2P load balancing, IEEE.

  72. De Grande, R. E., & Boukerche, A. (2010). Dynamic balancing of communication and computation load for HLA- based simulations on large-scale distributed systems. Journal of Parallel and Distributed Computer, 71(1), 40–52.

  73. Qin, X., Jiang, H., Manzanares, A., Ruan, X., Yin, S. (2010). Communication-aware load balancing for parallel applications on clusters. IEEE Transactions on computers, 59(1), 42–52.

  74. Zhang, D. Jiang, C., & Li, S. (2009). A fast adaptive load balancing method for parallel particle-based simulations. Simulation Modelling Practice and Theory, 1032–1042.

  75. Hui, C., **aoyong, L., & Shuling, D. (2009). A dynamic load balancing algorithm for sort-first rendering clusters, IEEE.

  76. Boukerche, A., & De Grande, R. E. (2009). Dynamic load balancing using grid services for HLA-based simulations on large-scale distributed systems. In 13th IEEE/ACM international symposium on distributed simulation and real time applications.

  77. Saravanakumar, E., & Prathima, G. (2010). A novel load balancing algorithm for computational grid. International Journal of Computational Intelligence Techniques, 1(1), 20-26. ISSN: 0976-0466 & E-ISSN: 0976-0474.

  78. Bhatele, A., Kale, L. V., & Kumar, S. (2009). Dynamic topology aware load balancing algorithms for molecular dynamics applications, ICS’09. New York Town Heights, New York, USA: ACM.

  79. Aye, T. T., Hlaing, H. H. (2008). An efficient dynamic load balancing policy in cluster computing system. In GMSARN international conference on sustainable development: Issues and prospects for the GMS 12-14.

  80. Liao, C.-J., & Chung, Y.-C. (1999). Tree-based parallel load-balancing methods for solution-adaptive finite element graphs on distributed memory multicomputers. IEEE Transactions on Parallel and Distributed Systems, 10(4), 360–370.

  81. Qin, X., Jiang, H., Manzanares, A., Ruan, X., & Yin, S. (2009). Dynamic load balancing for I/O-intensive applications on clusters. ACM Transactions on Storage, 5(3), Article 9.

  82. Ali, S., Eslamnour, B., & Shah, Z. (2010). A case for on-machine load balancing. Amsterdam: Elsevier.

    Google Scholar 

  83. Wu, C.-C., & Sun, R.-Y. (2010). An integrated security-aware job scheduling strategy for large-scale computational grids. Future Generation Computer Systems, 26(2), 198–206.

  84. Elsässer, R., & Sauerwald, T. (2010). Discrete load balancing is (almost) as easy as continuous load balancing. PODC Zurich, Switzerland: ACM.

  85. Prasad, P. V., Sivanagaraju, S., & Sreenivasulu, N. (2010). Network reconfiguration for load balancing in radial distribution systems using genetic algorithm. Electric Power Components and Systems, Publication details, including instructions for authors and subscription information.

  86. Miao, W., Li, D., & Zhang, W. (2010). A load-balancing dynamic scheduling algorithm under machine failure conditions. In International conference on intelligent computation technology and automation, IEEE.

  87. Chang, J., Zhou, W., Song, J., & Lin, Z. (2010). Scheduling algorithm of load balancing based on dynamic policies. In Sixth international conference on networking and services.

  88. Zhang, M., & Feng, B. (2008). A novel migration algorithm based-on “States-balancing” in a distributed multimedia services system. International conference on multimedia and ubiquitous engineering, IEEE.

  89. Jo, Y., & Kulkarni, M. (2010). Brief announcement: Locality-aware load balancing for speculatively-parallelized irregular applications (SPAA’10), Purdue University, Thira, Santorini, Greece: ACM. 978-1-4503-0079-7/10/06.

  90. Visalakshi, P., & Sivanandam, S. N. (2009). Dynamic task scheduling with load balancing using hybrid particle swarm optimization. International Journal of Open Problems Computer Mathematics, 2(3); Copyright ICSRS Publication.

  91. Anandharajan, T. R. V., & Bhagyaveni, M. A., Dr. (2011). Co-operative scheduled energy aware load-balancing technique for an efficient computational cloud. International Journal of Computer Science Issues, 8(2), 571–576.

  92. Mehta, H. K., Kanungo, P., & Chandwani, M. (2011). Performance enhancement of scheduling algorithms in clusters and grids using improved dynamic load balancing techniques. WWW 2011—Ph. D. Symposium, March 28–April 1, 2011, Hyderabad, India.

  93. Lee, J., Keleher, P., & Sussman, A. (2010). Decentralized dynamic scheduling across heterogeneous multi-core desktop grids, IEEE-2010.

  94. Qian, Z., Zeng, M., Qi, D., & Xu, K. (2008). A dynamic scheduling algorithm for distributed kahn process networks in a cluster environment. doi:10.1109/PACIIA.2008.190, IEEE.

  95. Moradi, M., Dezfuli, M. A., & Safavi, M. H. (2010). A new time optimizing probabilistic load balancing algorithm in grid computing. IEEE.

  96. Li, Y., Yanga, Y., Mab, M., & Zhou, L. (2009). A hybrid load balancing strategy of sequential tasks for grid computing environments. Future Generation Computer Systems, 25(8), 819–828.

  97. Zaki, M. J., Li, W., & Parthasarathy, S. (1997). Customized dynamic load balancing for a network workstations. Journal of Parallel and Distributed Computing, 43, 156–162.

  98. Mishra, S., Kushwaha, D. S., & Misra, A. K. (2011). Hybrid and reliable load balancing with MOSIX as middleware and its formal verification using process algebra. Future Generation of Computer Science, 27(5), 506–526.

  99. Walters, V., Paul, C. J., & Jiang, H. (2006). An adaptive heterogeneous software DSM. In Proceedings of international conference on parallel processing workshops, ICPPW- 2006.

  100. Siripoonya, V., & Chanchio, K. (2011). Thread-based live checkpointing of virtual machines. In 2011 IEEE international symposium on network computing and applications.

  101. Yang, S. (2012). Online scheduling with migration cost. In IEEE 26th international parallel and distributed processing symposium workshops & PhD forum.

  102. Lee, D. (2010). IP-paging base resource management and task migration in mobile grid environments. International Journal of Grid and Distributed Computing, 3(3), 29–40.

  103. Sayar, Z. A., & Prof. Erdogan, N. Dr. (2012). Network load balancing with strong migration in an agent based grid system using CSP approach. International Journal of Grid Computing & Applications, 3(4), 43–53.

  104. Shah, R., Veeravalli, B., & Misra, M. (2007). On the design of adaptive and decentralized load-balancing algorithms with load estimation for computational grid environments. IEEE Transactions on Parallel and Distributed Systems, 18(12), 1675–1686.

  105. Mishra, S., Kushwaha, D. S., Misra, A. K. (2010). An optimized scheduling algorithm for migrated jobs in trusted distributed systems. In International conference on computer & communication technology.

  106. Cuesta, D., Ayala, J. L., Hidalgo, J. I., Atienza, D., Acquaviva, A., & Macii, E. (2010). Adaptive task migration policies for thermal control in MPSoCs. In IEEE annual symposium on VLSI.

  107. Azfar, A., Morshed, Md. S., Islam, Md. Z., Ullah, A. S. S. M. B., & Pathan, A.-M. K. (2005). A Simplified Process for Grid Job Migration. In International Conference of Computer and Information Technology (ICCIT-2005) (pp. 706–709). Bangladesh: Islamic University of Technology (IUT).

  108. Lee, H., Chung, K., Chin, S., Lee, J., Lee, D., Parka, S., et al. (2005). Aresource management and fault tolerance services in grid computing. Journal of Parallel and Distributed Computing, 65, 1305–1317.

    Article  Google Scholar 

  109. Chen, P.-C., Lin, C.-I., Huang, S.-W., Chang, J.-B., Shieh, C.-K., Liang, T.-Y. A performance study of virtual machine migration vs. thread migration for grid systems. In 22nd international conference on advanced information networking and applications—workshops.

  110. Vadhiyar, S. S., & Dongarra, J. J. (2003). A performance oriented migration framework for the grid. In Cluster Computing and the Grid, 2003. Proceedings. CCGrid 2003 (pp. 130–137). 3rd IEEE/ACM International Symposium on IEEE.

  111. Calzolari, F., & Volpe, S. (2011). “A new job migration algorithm to improve data center efficiency” proceeding on science. In The international symposium on grids and clouds and the open grid forum Academia Sinica, Taipei, Taiwan.

  112. Mehnert-Spahn, J., & Schoettner, M. (2010). Checkpointing and Migration of Communication Channels in Heterogeneous Grid Environments. In Algorithms and Architectures for Parallel Processing, Lecture Notes in Computer Science (Vol. 6081, pp 254–265).

  113. Chung, P. E., Huang, Y., Yajnik, S., Fowler, G., Vo, K.-P., & Wang, Y.-M. (1997). Checkpointing in CosMiC: A user-level process migration environment, IEEE.

  114. Satheesh, A., Kumar, K. V., & Krishnaveni, S. (2008). Generalized load sharing for homogeneous networks of distributed environment. Hindawi Publishing Corporation Journal of Computer Systems, Networks, and Communications, Article ID 294106.

  115. Tadepalli, S. S. (2003). GEMS: A fault tolerant grid job management system, Thesis, Master of Science, Blacksburg, Virginia.

  116. Altameem, T. (2013). Fault tolerance techniques in grid computing systems. International Journal of Computer Science and Information Technologies, 4(6), 858–862.

  117. Patra, P. K., Singh, H., & Singh, G. (2013). Fault tolerance techniques and comparative implementation in cloud computing. International Journal of Computer Applications (0975–8887), 64(14).

  118. Busseuil, R., Almeida, G. M., Varyani, S., Sassatelli, G., & Robert, M. (2010). Exploration of task migration techniques for distributed memory multiprocessor systems on chips. In 18th IEEE/IFIP International Conference on VLSI and Systems-on-Chip (VLSI-SoC’2010), Madrid, Spain: IEEE Computer Society.

  119. Alwada’n, T., Aldabbas, H., Janicke, H., Khdour, T., & Aldabbas, O. (2012). Dynamic policy management in mobile grid environments. International Journal of Computer Networks & Communications, 4(2), 35–51.

  120. El-Zoghdy, S. F. (2012). A capacity-based load balancing and job migration algorithm for heterogeneous computational grids. International Journal of Computer Networks & Communications, 4(1), 113–125.

  121. Ellahi, T. N., Hudzia, B., McDermott, L., & Kechadi, T. Transparent migration of multi-threaded applications on a java based grid, University College Dublin Dublin—Ireland.

  122. Albers, S., & Hellwig, M. (2012). On the value of job migration in online makespan minimization, ar**v:1111.0773v2 [cs.DS].

  123. Zhang, Z., & Cheng, W. (2007). Model and optimization of mobile agent’s migration in grid, IEEE.

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  1. Computer Science and Engineering Department, Jaypee University of Engineering and Technology, AB Road, Guna, MP, India

    Neeraj Rathore

  2. HNo-1056, Mahaveer Nagar-2, Kota, 324005, Rajasthan, India

    Neeraj Rathore

  3. Computer Science and Engineering Department, Thapar University, Patiala, 147004, India

    Inderveer Chana

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Rathore, N., Chana, I. Load Balancing and Job Migration Techniques in Grid: A Survey of Recent Trends. Wireless Pers Commun 79, 2089–2125 (2014). https://doi.org/10.1007/s11277-014-1975-9

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