Abstract
This paper proposes two-fold approach that works on minimizing makespan for parallel machines and performs caching operation to reduce the load on data servers during multi-query process. Makespan criterion is an NP-hard problem, which assigns jobs to machines so as to minimize the time by which the last job gets finished. Discrete version of particle swarm optimization (PSO) is implemented to schedule the processing of parallel machines, connected through message passing interface (MPI). Data caching on B-tree is performed on multiple processors for handling subsequent and concurrent queries. The multi-query process addressed here is multiple sequence alignment (MSA), which is one of the most challenging and prominent areas of bioinformatics with high computational cost. State-of-the-art alignment algorithm ClustalW is used for obtaining MSA of highly complex sequence sets. The results show the improvements in process time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Robert, C.: Edgar and serafim batzoglou, multiple sequence alignment. Curr. Opin. Struct. Biol. 16(3), 368–373 (2006)
Xiao Lin L., Yu Peng L., Yu W.: Minimising makespan on a batch processing machine using heuristics improved by an enumeration scheme. Int. J. Prod. Res. 55(1), 176–186 (2017)
Schatz, M.C., Trapnell, C., Delcher, A.L., Varshney, A.: High-throughput sequence alignment using graphics processing units. BMC Bioinform. 8(1), 474 (2007)
Julie, D.T., Desmond, G.H., Toby, J.G.: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994)
Kennedy, J.F., Eberhart. R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948. Piscataway, NJ (1995)
Husseinzadeh, A.K., Karimi, B.: A discrete particle swarm optimization algorithm for scheduling parallel machines. Comput. Ind. Eng. 56, 216–223 (2009)
Notredame, C.: Recent progress in multiple sequence alignment: a survey. Pharmacogenomics 3(1), 131–144 (2002)
Myers, E.W., Miller, W.: Optimal alignments in linear space. Bioinformatics 4(1), 11–17 (1988)
Smith, T.F., Waterman, M.S., Walter, M.F.: Comparative biosequence metrics. J. Mol. Evol. 18(1), 38–46 (1981)
Saitou, N., Nei, M.: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987)
Askitis, N., Zobel, J.: B-tries for disk-based string management. VLDB J. Int. J. Very Larg. Data Bases 18(1), 157–179 (2009)
Catalyurek, U., Ferreira, R., Kurc, T., Saltz, J., Stahlberg, E.: Improving performance of multiple sequence alignment analysis in multi-client environments. In: Proceedings of the 16th International Parallel and Distributed Processing Symposium. Washigton, DC, USA (2001)
Weikum, G., Vossen, G.: Transactional Information Systems. Morgan Kaufmann Publishers (2002)
Gropp, W., Lusk, E., Skjellum, A.: Using MPI: portable parallel programming with the message-passing interface, vol. 1. MIT press (1999)
Adamo, J.-M.: Multi-threaded object-oriented MPI-based message passing interface: the ARCH library, vol. 446. Springer Science & Business Media (2012)
Lalwani, S., Kumar, R., Gupta, N.: A review on particle swarm optimization variants and their applications to multiple sequence alignment. J. Appl. Math. Bioinformatics. 3(2), 87–124 (2013)
Lalwani, S., Kumar, R., Deep, K.: Multi-objective two-level swarm intelligence approach for multiple RNA sequence-structure alignment. Swarm Evolut. Comput. 34, 130–144 (2017)
Bahr, A., Thompson, J.D., Thierry, J.-C., Poch, O.: BAliBASE (benchmark alignment database): enhancements for repeats, transmembrane sequences and circular permutations. Nucleic Acids Res. 29(1), 323–326 (2001)
Acknowledgements
The first author (S.L.) gratefully acknowledges Science & Engineering Research Board, DST, Government of India for the fellowship (PDF/2016/000008). We are thankful to Dr. Krishna Mohan from BISR, Jaipur, India, for his valuable suggestions throughout the work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Lalwani, S., Sharma, H., Verma, A., Deep, K. (2019). Minimization of Makespan for Parallel Machines Using PSO to Enhance Caching of MSA-Based Multi-query Processes. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_15
Download citation
DOI: https://doi.org/10.1007/978-981-13-1595-4_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1594-7
Online ISBN: 978-981-13-1595-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)