Page 280 - 《软件学报》2026年第1期
P. 280
向清平 等: 分布式数据库高可用研究进展 277
environment and a novel fault tolerance approach. IEEE Access, 2020, 8: 130500–130526. [doi: 10.1109/ACCESS.2020.3009184]
[54] Kumar P, Kumar R. Issues and challenges of load balancing techniques in cloud computing: A survey. ACM Computing Surveys, 2019,
51(6): 120. [doi: 10.1145/3281010]
[55] Shafiq DA, Jhanjhi NZ, Abdullah A. Load balancing techniques in cloud computing environment: A review. Journal of King Saud
University—Computer and Information Sciences, 2022, 34(7): 3910–3933. [doi: 10.1016/j.jksuci.2021.02.007]
[56] Aliyu AN, Souley PB. Performance analysis of a hybrid approach to enhance load balancing in a heterogeneous cloud environment. Int’l
Journal of Advances in Scientific Research and Engineering, 2019, 5(7): 246–257. [doi: 10.31695/IJASRE.2019.33430]
[57] Chen SL, Chen YY, Kuo SH. CLB: A novel load balancing architecture and algorithm for cloud services. Computers & Electrical
Engineering, 2017, 58: 154–160. [doi: 10.1016/j.compeleceng.2016.01.029]
[58] Pasupuleti KK, Klots B, Nagarajan V, Kandukuri A, Agarwal N. High availability framework and query fault tolerance for hybrid
distributed database systems. In: Proc. of the 31st ACM Int’l Conf. on Information & Knowledge Management. Atlanta: ACM, 2022.
3451–3460. [doi: 10.1145/3511808.3557086]
[59] Balkesen C, Kunal N, Giannikis G, Fender P, Sundara S, Schmidt F, Wen J, Agrawal S, Raghavan A, Varadarajan V, Viswanathan A,
Chandrasekaran B, Idicula S, Agarwal N, Sedlar E. RAPID: In-memory analytical query processing engine with extreme performance per
Watt. In: Proc. of the 2018 Int’l Conf. on Management of Data. Houston: ACM, 2018. 1407–1419. [doi: 10.1145/3183713.3190655]
[60] Hormati M, Khendek F, Toeroe M. Towards an evaluation framework for availability solutions in the cloud. In: Proc. of the 2014 IEEE
Int’l Symp. on Software Reliability Engineering Workshops. Naples: IEEE, 2014. 43–46. [doi: 10.1109/ISSREW.2014.50]
[61] Endo PT, Rodrigues M, Gonçalves GE, Kelner J, Sadok DH, Curescu C. High availability in clouds: Systematic review and research
challenges. Journal of Cloud Computing, 2016, 5(1): 16. [doi: 10.1186/s13677-016-0066-8]
[62] Imran A, Gias AU, Rahman R, Seal A, Rahman T, Ishraque F, Sakib K. Cloud-Niagara: A high availability and low overhead fault
tolerance middleware for the cloud. In: Proc. of the 16th Int’l Conf. Computer and Information Technology. Khulna: IEEE, 2014.
271–276. [doi: 10.1109/ICCITechn.2014.6997344]
[63] OpenStack. Open source cloud computing infrastructure—OpenStack. 2024. http://www.openstack.org
[64] Kanso A, Lemieux Y. Achieving high availability at the application level in the cloud. In: Proc. of the 6th IEEE Int’l Conf. on Cloud
Computing. Santa Clara: IEEE, 2013. 778–785. [doi: 10.1109/CLOUD.2013.24]
[65] Heidari P, Hormati M, Toeroe M, Al Ahmad Y, Khendek F. Integrating open SAF high availability solution with open stack. In: Proc. of
the 2015 IEEE World Congress on Services. New York: IEEE, 2015. 229–236. [doi: 10.1109/SERVICES.2015.41]
[66] An K, Shekhar S, Caglar F, Gokhale A, Sastry S. A cloud middleware for assuring performance and high availability of soft real-time
applications. Journal of Systems Architecture, 2014, 60(9): 757–769. [doi: 10.1016/j.sysarc.2014.01.009]
[67] Endo PT, De Almeida Palhares AV, Pereira NN, Goncalves GE, Sadok D, Kelner J, Melander B, Mangs JE. Resource allocation for
distributed cloud: Concepts and research challenges. IEEE Network, 2011, 25(4): 42–46. [doi: 10.1109/mnet.2011.5958007]
[68] Cully B, Lefebvre G, Meyer D, Feeley M, Hutchinson N, Warfield A. Remus: High availability via asynchronous virtual machine
replication. In: Proc. of the 5th USENIX Symp. on Networked Systems Design and Implementation. San Francisco: USENIX
Association, 2008. 161–174.
[69] Sharma YK, Singh AS. High availability of databases for cloud. In: Satapathy SC, Joshi A, Modi N, Pathak N, eds. Proc. of the 2016 Int’l
Conf. on ICT for Sustainable Development. Singapore: Springer, 2016. 501–509. [doi: 10.1007/978-981-10-0135-2_49]
[70] Minhas UF, Rajagopalan S, Cully B, Aboulnaga A, Salem K, Warfield A. RemusDB: Transparent high availability for database systems.
The VLDB Journal, 2013, 22(1): 29–45. [doi: 10.1007/s00778-012-0294-6]
[71] Ren SR, Zhang YQ, Pan LC, Xiao Z. Phantasy: Low-latency virtualization-based fault tolerance via asynchronous prefetching. IEEE
Trans. on Computers, 2019, 68(2): 225–238. [doi: 10.1109/TC.2018.2865943]
[72] Saxena D, Singh AK. A high availability management model based on VM significance ranking and resource estimation for cloud
applications. IEEE Trans. on Services Computing, 2023, 16(3): 1604–1615. [doi: 10.1109/TSC.2022.3206417]
[73] Nikzad A, Khendek F, Toeroe M. OpenSAF and VMware from the perspective of high availability. In: Proc. of the 9th Int’l Conf. on
Network and Service Management. Zurich: IEEE, 2013. 324–331. [doi: 10.1109/CNSM.2013.6727853]
[74] Baker J, Bond C, Corbett JC, Furman JJ, Khorlin A, Larson J, Leon JM, Li YW, Lloyd A, Yushprakh V. Megastore: Providing scalable,
highly available storage for interactive services. In: Proc. of the 5th Biennial Conf. on Innovative Data Systems Research. 2011. 223–234.
[75] DeCandia G, Hastorun D, Jampani M, Kakulapati G, Lakshman A, Pilchin A, Sivasubramanian S, Vosshall P, Vogels W. Dynamo:
Amazon’s highly available key-value store. ACM SIGOPS Operating Systems Review, 2007, 41(6): 205–220. [doi: 10.1145/1323293.
1294281]
[76] Kim T, Wong DLK, Ganger GR, Kaminsky M, Andersen DG. High availability in cheap distributed key value storage. In: Proc. of the

