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The Journal of Supercomputing

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26-05-2020

A cost saving and load balancing task scheduling model for computational biology in heterogeneous cloud datacenters

Authors: Wenwei Cai, Jiaxian Zhu, Weihua Bai, Weiwei Lin, Naqin Zhou, Keqin Li

Published in: The Journal of Supercomputing | Issue 8/2020

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Abstract

Cloud-based scientific workflow systems can play an important role in the development of cost-effective bioinformatics analysis applications. There are differences in the cost control and performance of many kinds of servers in heterogeneous cloud data centers for bioinformatics workflows running, which can lead to imbalance between operational/maintenance management costs and quality of service of server clusters. A task scheduling model that responds to the peaks and valleys of task sequencing—the number of tasks that arrive in a given unit of time—is related to indicators such as cost saving, load balancing and system performance (average task wait time, average response time and throughput). This study proposes a large-scale cost-saving and load-balancing scheduling model, called HDCBS, for the optimization of system throughput. First, queuing theory is used to model each computing node as an independent queuing system and to obtain the average system wait time and average task response time. Then, using convex optimization theory, a task assignment solution is proposed with a load-balancing mechanism. The validity of the task scheduling model is verified by simulation experiments, and the model performance is further validated through a comparison with other frequently used scheduling methods. The simulation results show that the credibility of HDCBS is greater than 95% in task scheduling.

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Lu C, Ye K, Xu G, Xu C-Z, Bai T (2017) Imbalance in the cloud: an analysis on alibaba cluster trace. In: 2017 IEEE International Conference on Big Data (Big Data), IEEE, pp 2884–2892

Cheng Y, Chai Z, Anwar A (2018) Characterizing co-located datacenter workloads: an alibaba case study. In: Proceedings of the 9th Asia-Pacific Workshop on Systems, APSys 2018, Jeju Island, Republic of Korea, pp 12:1–12:3

Jiang Congfeng, Han Guangjie, Lin Jiangbin, Jia Gangyong, Shi Weisong, Wan Jian (2019) Characteristics of co-allocated online services and batch jobs in internet data centers: a case study from alibaba cloud. IEEE Access 7:22495–22508

Kameda H, Li J, Kim C, Zhang Y (2012) Optimal load balancing in distributed computer systems. Springer, New YorkMATH

Domanal SG, Reddy GRM (2014) Optimal load balancing in cloud computing by efficient utilization of virtual machines. In: Sixth International Conference on Communication Systems and Networks, COMSNETS 2014, Bangalore, India, pp 1–4

Andrews Jeffrey G, Singh Sarabjot, Ye Qiaoyang, Lin Xingqin, Dhillon Harpreet S (2014) An overview of load balancing in hetnets: old myths and open problems. IEEE Wireless Commun 21(2):18–25

Lin Weiwei, Siyao Xu, He Ligang, Li Jin (2017) Multi-resource scheduling and power simulation for cloud computing. Inf Sci 397:168–186

Hondo F, Wercelens P, da Silva WMC, Castro K, Santana I, Walter MET, de Araújo APF, Holanda M, Lifschitz S (2017) Data provenance management for bioinformatics workflows using NOSQL database systems in a cloud computing environment. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, MO, USA, pp 1929–1934

Liu Bo, Madduri Ravi K, Sotomayor Borja, Chard Kyle, Lacinski Lukasz, Dave Utpal J, Li Jianqiang, Liu Chunchen, Foster Ian T (2014) Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses. J Biomed Inf 49:119–133

10.

Abouelhoda Mohamed, Issa Shadi, Ghanem Moustafa (2013) Towards scalable and cost-aware bioinformatics workflow execution in the cloud—recent advances to the tavaxy workflow system. Fundam Inf 128(3):255–280

11.

Emeakaroha Vincent C, Maurer Michael, Stern Patrick, Labaj Pawel P, Brandic Ivona, Kreil David P (2013) Managing and optimizing bioinformatics workflows for data analysis in clouds. J Grid Comput 11(3):407–428

12.

Xie Z, Han L, Baldock RA (2013) Augmented petri net cost model for optimisation of large bioinformatics workflows using cloud. In: Seventh UKSim/AMSS European Modelling Symposium, EMS 2013, Manchester UK, pp 201–205

13.

Bai W-H, Xi J-Q, Zhu J-X, Huang S-W (2015) Performance analysis of heterogeneous data centers in cloud computing using a complex queuing model. In: Mathematical Problems in Engineering 2015

14.

Jin Y, Gao Y, Qian Z, Zhai M, Peng H, Lu S (2016) Workload-aware scheduling across geo-distributed data centers. In: 2016 IEEE Trustcom/BigDataSE/ISPA, Tianjin, China, pp 1455–1462

15.

Chen Shang-Liang, Chen Yun-Yao, Kuo Suang-Hong (2017) CLB: a novel load balancing architecture and algorithm for cloud services. Comput Electr Eng 58:154–160

16.

Tripathi R, Vignesh S, Tamarapalli V, Chronopoulos AT, Siar H (2017) Non-cooperative power and latency aware load balancing in distributed data centers. J Parallel Distrib Comput 107:76–86

17.

Panda Sanjaya K, Jana Prasanta K (2018) Normalization-based task scheduling algorithms for heterogeneous multi-cloud environment. Inf Syst Front 20(2):373–399

18.

Cao Junwei, Hwang Kai, Li Keqin, Zomaya Albert Y (2013) Optimal multiserver configuration for profit maximization in cloud computing. IEEE Trans Parallel Distrib Syst 24(6):1087–1096

19.

Chiang Y-J, Ouyang Y-C (2014) Profit optimization in SLA-aware cloud services with a finite capacity queuing model. In: Mathematical Problems in Engineering 2014

20.

Cao J, Li K, Stojmenovic I (2014) Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. IEEE Trans Comput 63(1):45–58MathSciNetMATH

21.

Yuan H, Bi J, Zhou M (2019) Multi-queue scheduling of heterogeneous tasks with bounded response time in hybrid green IAAS clouds. IEEE Trans Ind Inf 15(10):5404–5412

22.

Gnimpieba EZ, Thavappiragasam M, Chango A, Conn B, Lushbough CM (2015) Sbmldock: Docker driven systems biology tool development and usage. In: International Conference on Computational Methods in Systems Biology. Springer, New York, pp 282–285

23.

Leggett RM, Heavens D, Caccamo M, Clark MD, Davey RP (2016) Nanook: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles. Bioinformatics 32(1):142–144

24.

Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM (2016) Mash: fast genome and metagenome distance estimation using minhash. Genom Biol 17(1):132

25.

Liu Q, Yu Z (2018) The elasticity and plasticity in semi-containerized co-locating cloud workload: a view from alibaba trace. In: Proceedings of the ACM Symposium on Cloud Computing, SoCC 2018, Carlsbad, CA, USA, pp 347–360

26.

Alam M, Shakil KA, Sethi S (2016) Analysis and clustering of workload in Google cluster trace based on resource usage. In 2016 IEEE International Conference on Computational Science and Engineering, CSE 2016, and IEEE International Conference on Embedded and Ubiquitous Computing, EUC 2016, and 15th International Symposium on Distributed Computing and Applications for Business Engineering, DCABES 2016, Paris, France, pp 740–747

27.

Shortle JF, Thompson JM, Gross D, Harris CM (2018) Fundamentals of queueing theory, vol 399. Wiley, HobokenMATH

28.

Boyd Stephen, Vandenberghe Lieven (2004) Convex optimization. Cambridge University Press, CambridgeMATH

29.

Ren Xiaoqi, Ananthanarayanan Ganesh, Wierman Adam, Minlan Yu (2015) Hopper: decentralized speculation-aware cluster scheduling at scale. Comput Commun Rev 45(5):379–392

30.

Margolies Robert, Sridharan Ashwin, Aggarwal Vaneet, Jana Rittwik, Shankaranarayanan N K, Vaishampayan Vinay A, Zussman Gil (2016) Exploiting mobility in proportional fair cellular scheduling: measurements and algorithms. IEEE/ACM Trans Netw 24(1):355–367

31.

Singh Sarabjot, Geraseminko Mikhail, Yeh Shu-ping, Himayat Nageen, Talwar Shilpa (2016) Proportional fair traffic splitting and aggregation in heterogeneous wireless networks. IEEE Commun Lett 20(5):1010–1013

32.

Cai Weihong, Yang Junjie, Yidan Yu, Song Youyi, Zhou Teng, Qin Jing (2020) Pso-elm: a hybrid learning model for short-term traffic flow forecasting. IEEE Access 8:6505–6514

33.

Cai L, Yu Y, Zhang S, Song Y, Xiong Z, Zhou T (2020) A sample-rebalanced outlier-rejected k-nearest neighbour regression model for short-term traffic flow forecasting. IEEE Access 1–11

34.

Cai Lingru, Lei Mingqin, Zhang Shuangyi, Yidan Yu, Zhou Teng, Qin Jing (2020) A noise-immune lstm network for short-term traffic flow forecasting. Chaos 30(3):1–10

35.

Zhou Teng, Jiang Dazhi, Lin Zhizhe, Han Guoqiang, Xuemiao Xu, Qin Jing (2019) Hybrid dual kalman filtering model for short-term traffic flow forecasting. IET Intell Transp Syst 13(6):1023–1032

36.

Bai Weihua, Zhu Jiaxian, Zhang Huibing, Lin Weiwei, Xi Jianqing (2019) A multi-dimensional resource scheduling strategy based on multilateral complementarity. IEEE Access 7:88481–88503

37.

Lin Miao, Xi Jianqing, Bai Weihua, Jiayin Wu (2019) Ant colony algorithm for multi-objective optimization of container-based microservice scheduling in cloud. IEEE Access 7:83088–83100

Title: A cost saving and load balancing task scheduling model for computational biology in heterogeneous cloud datacenters
Authors: Wenwei Cai
Jiaxian Zhu
Weihua Bai
Weiwei Lin
Naqin Zhou
Keqin Li
Publication date: 26-05-2020
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 8/2020
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-020-03305-y

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