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Articles

An efficient weighted partial MaxSAT encoding for scheduling in overloaded real-time systems

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Pages 175-183 | Received 03 Aug 2023, Accepted 16 Dec 2023, Published online: 23 Dec 2023

References

  • Ramasubbareddy S, Sasikala R. RTTSMCE: a response time aware task scheduling in multi-cloudlet environment. Int J Comput Appl. 2021;43(7):691–696.
  • Rambabu D, Govardhan A. Task scheduling and data replication in cloud with improved correlation strategy. Int J Comput Appl. 2023;45:1–12.
  • Geeta K, Kamakshi Prasad V. Multi-objective cloud load-balancing with hybrid optimization. Int J Comput Appl. 2023;45(10):611–625.
  • Kumar M, Sharma SC. Dynamic load balancing algorithm to minimize the makespan time and utilize the resources effectively in cloud environment. Int J Comput Appl. 2020;42(1):108–117.
  • Malik A, Walker C, O'Sullivan M, et al. Satisfiability modulo theory (SMT) formulation for optimal scheduling of task graphs with communication delay. Comput Oper Res. 2018;89:113–126. doi: 10.1016/j.cor.2017.08.012
  • Liao X, Zhang H, Koshimura M, et al. Modeling and solving scheduling in overloaded situations with weighted partial MaxSAT. Math Probl Eng. 2021;2021:1–17.
  • Marchand A, Chetto M. Dynamic scheduling of periodic skippable tasks in an overloaded real-time system. In: 2008 IEEE/ACS international conference on computer systems and applications. IEEE; 2008. p. 456–464.
  • Cheng Z, Zhang H, Tan Y, et al. SMT-based scheduling for overloaded real-time systems. IEICE Trans Inf Syst. 2017;E100.D(5):1055–1066. doi: 10.1587/transinf.2016EDP7374
  • Wang S, Liao X, Wang M, et al. An improved SMT-based scheduling for overloaded real-time systems. Eng Lett. 2020;28(1):112–122.
  • Liao X, Zhang H, Koshimura M, et al. Maximum satisfiability formulation for optimal scheduling in overloaded real-time systems. In: Pacific rim international conference on artificial intelligence. Springer; 2019. p. 618–631.
  • Li C-M, Xu Z, Coll J, et al. Combining clause learning and branch and bound for MaxSAT. In: 27th International conference on principles and practice of constraint programming (CP 2021). Schloss Dagstuhl-Leibniz-Zentrum für Informatik; 2021.
  • Berg J, Järvisalo M, Martins R, et al. MaxSAT evaluation 2023; n. d.
  • Cheng Z, Zhang H, Tan Y, et al. Dpsc: A novel scheduling strategy for overloaded real-time systems. In: 2014 IEEE 17th international conference on computational science and engineering. IEEE; 2014. p. 1017–1023.
  • Cheng Z, Zhang H, Tan Y, et al. Greedy scheduling with feedback control for overloaded real-time systems. In: 2015 IFIP/IEEE international symposium on integrated network management (IM). IEEE; 2015. p. 934–937.
  • Shah A, Kotecha K. Efficient scheduling algorithms for real-time distributed systems. In: 2010 First international conference on parallel, distributed and grid computing (PDGC 2010). IEEE; 2010. p. 44–48.
  • Khalilzad NM, Nolte T, Behnam M. Towards adaptive hierarchical scheduling of overloaded real-time systems. In: 2011 6th IEEE international symposium on industrial and embedded systems. IEEE; 2011. p. 39–42.
  • Ghazy N, Abdelkader A, Zaki MS, et al. A new round robin algorithm for task scheduling in real-time system. Int J Intell Eng Syst. 2022;15(5):691–704.
  • Liu W, Gu Z, Xu J, et al. Satisfiability modulo graph theory for task mapping and scheduling on multiprocessor systems. IEEE Trans Parallel Distrib Syst. 2010;22(8):1382–1389. doi: 10.1109/TPDS.2010.204
  • Ourari S, Briand C, Bouzouiac B. A MIP approach for the minimization of the number of late jobs in single machine scheduling. J Math Model Algorithms. 2009;1:1–15.
  • Hung H-C, Lin BMT, Posner ME, et al. Preemptive parallel-machine scheduling problem of maximizing the number of on-time jobs. J Sched. 2019;22:413–431. doi: 10.1007/s10951-018-0584-y
  • Bofill M, Coll J, Suy J, et al. Solving the multi-mode resource-constrained project scheduling problem with SMT. In: 2016 IEEE 28th international conference on tools with artificial intelligence (ICTAI). IEEE; 2016. p. 239–246.
  • Salamun K, Pavić I, Džapo H, et al. Evolving scheduling heuristics with genetic programming for optimization of quality of service in weakly hard real-time systems. Appl Soft Comput. 2023;137:110141. doi: 10.1016/j.asoc.2023.110141
  • Su P-C, Tan S-Y, Liu ZY, et al. A mixed-heuristic quantum-inspired simplified swarm optimization algorithm for scheduling of real-time tasks in the multiprocessor system. Appl Soft Comput. 2022;131:109807. doi: 10.1016/j.asoc.2022.109807
  • Xu J, Yu H, Fan G, et al. Uncertainty-aware scheduling of real-time workflows under deadline constraints on multi-cloud systems. Concurr Comput Pract Exp. 2023;35(5):e7562. doi: 10.1002/cpe.v35.5

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