Efficient discrete firefly algorithm for Ctrie based caching of multiple sequence alignment on optimally scheduled parallel machines

• Published in: CAAI Transactions on Intelligence Technology Vol. 4; no. 2; pp. 92 - 100
• Main Authors: Lalwani, Soniya, Sharma, Harish, Verma, Abhay, Kumar, Rajesh
• Format: Journal Article
• Language: English
• Published: Beijing The Institution of Engineering and Technology 01.06.2019; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Alignment; BAliBASE 4 dataset; bioinformatics; Bonferroni posthoc analysis; C1160 Combinatorial mathematics; C1180 Optimisation techniques; C6120 File organisation; C6150J Operating systems; C6170 Expert systems and other AI software and techniques; C7250R Information retrieval techniques; C7330 Biology and medical computing; cache storage; Caching; complex heterogeneous sequences; computational complexity; Ctrie based caching; DFFA; efficient discrete firefly algorithm; Heuristic methods; makespan minimisation; minimisation; MSA; multiclient problem; multiple queries; multiple sequence alignment; MUSCLE dataset; one-way ANOVA; optimally scheduled parallel machines; Optimization; pairwise alignment; parallel connected machines; parallel machines; particle swarm optimisation; Performance enhancement; query processing; Research Article; scheduling; search problems; Sequences; statistical significance testing; statistical testing; Swarm intelligence; swarm-intelligence based implementation; two-level strategy; particle swarm optimisation; complex heterogeneous sequences; cache storage; BAliBASE 4 dataset; parallel machines; query processing; scheduling; MSA; one-way ANOVA; swarm-intelligence based implementation; multiclient problem; MUSCLE dataset; statistical testing; search problems; statistical significance testing; DFFA; pairwise alignment; optimally scheduled parallel machines; multiple sequence alignment; Bonferroni posthoc analysis; two-level strategy; makespan minimisation; parallel connected machines; bioinformatics; Ctrie based caching; efficient discrete firefly algorithm; minimisation; multiple queries; swarm intelligence; computational complexity
• ISSN: 2468-2322; 2468-6557; 2468-2322
• DOI: 10.1049/trit.2018.1040

This study introduces a two-level strategy for efficient execution of multiple sequence alignment (MSA) of complex heterogeneous sequences. The two levels of the proposed technique are comprised of: designing the discrete firefly algorithm (DFFA) for the formation and implementation of makespan minimisation on parallel machines, followed by performing Ctrie-based caching for pairwise alignment to reduce the load on the data servers for handling multiple queries. The proposed strategy addresses a multi-client problem that aims to acquire the full advantage of the computational power of parallel connected machines. Further, it is shown that the inclusion of Ctrie as caching mechanism successively improves the performance of the system with accretion in several sequences. Performance of proposed DFFA is also compared with discrete versions of four swarm intelligence based algorithms at the criteria of makespan minimisation and the rate of convergence on two kinds of complex and diverse datasets. The work is unique in this sense: it is the first swarm-intelligence-based implementation for the addressed problem; it is so far the first approach for Ctrie based caching of the MSA on the scheduled parallel machines; hybridisation of DFFA with Ctrie for caching the MSA results is also a novel implementation.