International Journal of Advanced Technology and Engineering Exploration (IJATEE) ISSN (Print): 2394-5443 ISSN (Online): 2394-7454 Volume - 11 Issue - 116 July - 2024

  1. Google Scholar
A systematic review on recent methods of scheduling and load balancing for containers in distributed environments

Neelima Gogineni and Saravanan Madderi Sivalingam

Abstract

The concept of containers is widely used in cloud computing environments due to perceived benefits linked to packaging and deploying software efficiently. Due to the unprecedented usage of containers, it became indispensable to manage them efficiently. In other words, container scheduling and load-balancing strategies have assumed significance in distributed environments. In this paper, a systematic review is presented that covers ninety-five peer-reviewed research articles from 2012 to 2023, providing a comprehensive understanding of the current state of research in this field. This review synthesizes new insights and knowledge, shedding light on the challenges in container load balancing, various existing methods of container placement, container orchestration, scheduling, load balancing, cluster management, dynamic resource allocation, and micro-services. This paper also investigates load balancing for containers in fog or edge computing environments connected to cloud computing. The study thus synthesizes new knowledge on diversified aspects of containers and their load balancing in cloud environments, paving the way for further investigation and the realization of more optimal container scheduling and load-balancing approaches.

Keyword

Containerization, Scheduling, Load balancing, Cloud computing, Container placement, Container orchestration.

Cite this article

Gogineni N, Sivalingam SM.A systematic review on recent methods of scheduling and load balancing for containers in distributed environments. International Journal of Advanced Technology and Engineering Exploration. 2024;11(116):1030-1048. DOI:10.19101/IJATEE.2023.10102431

Refference

[1]Singh N, Hamid Y, Juneja S, Srivastava G, Dhiman G, Gadekallu TR, et al. Load balancing and service discovery using docker swarm for microservice based big data applications. Journal of Cloud Computing. 2023; 12(1):4.

[2]Wan X, Guan X, Wang T, Bai G, Choi BY. Application deployment using microservice and docker containers: framework and optimization. Journal of Network and Computer Applications. 2018; 119:97-109.

[3]Fazio M, Celesti A, Ranjan R, Liu C, Chen L, Villari M. Open issues in scheduling microservices in the cloud. IEEE Cloud Computing. 2016; 3(5):81-8.

[4]Acharya J, Suthar AC. Container scheduling algorithm in docker based cloud. Webology. 2022; 19(2):627-37.

[5]Watada J, Roy A, Kadikar R, Pham H, Xu B. Emerging trends, techniques and open issues of containerization: a review. IEEE Access. 2019; 7:152443-72.

[6]Rabiu S, Yong CH, Mohamad SM. A cloud-based container microservices: a review on load-balancing and auto-scaling issues. International Journal of Data Science. 2022; 3(2):80-92.

[7]Piraghaj SF, Dastjerdi AV, Calheiros RN, Buyya R. Efficient virtual machine sizing for hosting containers as a service (services 2015). In world congress on services 2015 (pp. 31-8). IEEE.

[8]No JK, Gedung PB, Indonesia M. Utilization docker swarms in a container technology system to problem solving load balance. Journal of Theoretical and Applied Information Technology. 2022; 100(18):5201-8.

[9]Sureshkumar M, Rajesh P. Optimizing the docker container usage based on load scheduling. In 2nd international conference on computing and communications technologies (ICCCT) 2017 (pp. 165-8). IEEE.

[10]Azab A. Enabling docker containers for high-performance and many-task computing. In IEEE international conference on cloud engineering (IC2E) 2017(pp. 279-85). IEEE.

[11]Li L, Chen J, Yan W. A particle swarm optimization-based container scheduling algorithm of docker platform. In proceedings of the 4th international conference on communication and information processing 2018 (pp. 12-7).

[12]Kaewkasi C, Chuenmuneewong K. Improvement of container scheduling for docker using ant colony optimization. In 9th international conference on knowledge and smart technology (KST) 2017 (pp. 254-9). IEEE.

[13]Qian J, Wang Y, Wang X, Zhang P, Wang X. Load balancing scheduling mechanism for openstack and docker integration. Journal of Cloud Computing. 2023; 12(1):67.

[14]Li Q, Fang Y. Multi-algorithm collaboration scheduling strategy for docker container. In international conference on computer systems, electronics and control (ICCSEC) 2017 (pp. 1367-71). IEEE.

[15]Ahmad I, Alfailakawi MG, Almutawa A, Alsalman L. Container scheduling techniques: a survey and assessment. Journal of King Saud University-Computer and Information Sciences. 2022; 34(7):3934-47.

[16]Guo Y, Yao W. A container scheduling strategy based on neighborhood division in micro service. In NOMS IEEE/IFIP network operations and management symposium 2018 (pp. 1-6). IEEE.

[17]Aruna K, Pradeep G. Ant colony optimization-based light weight container (ACO-LWC) algorithm for efficient load balancing. Intelligent Automation & Soft Computing. 2022; 34(1):201-19.

[18]Liu B, Li P, Lin W, Shu N, Li Y, Chang V. A new container scheduling algorithm based on multi-objective optimization. Soft Computing. 2018; 22:7741-52.

[19]Patra MK, Patel D, Sahoo B, Turuk AK. A randomized algorithm for load balancing in containerized cloud. In 10th international conference on cloud computing, data science & engineering (confluence) 2020(pp. 410-4). IEEE.

[20]Cérin C, Menouer T, Saad W, Abdallah WB. A new docker swarm scheduling strategy. In 7th international symposium on cloud and service computing (SC2) 2017 (pp. 112-7). IEEE.

[21]Zhang D, Yan BH, Feng Z, Zhang C, Wang YX. Container oriented job scheduling using linear programming model. In international conference on information management (ICIM) 2017 (pp. 174-80). IEEE.

[22]Marathe N, Gandhi A, Shah JM. Docker swarm and Kubernetes in cloud computing environment. In 3rd international conference on trends in electronics and informatics (ICOEI) 2019 (pp. 179-84). IEEE.

[23]Bernstein D. Containers and cloud: from LXC to docker to Kubernetes. IEEE Cloud Computing. 2014; 1(3):81-4.

[24]Zhang R, Zhong AM, Dong B, Tian F, Li R. Container-VM-PM architecture: a novel architecture for docker container placement. In cloud computing-CLOUD: 11th international conference, held as part of the services conference federation, SCF 2018, Seattle, WA, USA, Proceedings 2018 (pp. 128-40). Springer International Publishing.

[25]Zhiyong C, Xiaolan X. Overview of container cloud task scheduling. In proceedings of the 2020 artificial intelligence and complex systems conference 2020 (pp. 50-5). ACM.

[26]Adhikari M, Srirama SN. Multi-objective accelerated particle swarm optimization with a container-based scheduling for internet-of-things in cloud environment. Journal of Network and Computer Applications. 2019; 137:35-61.

[27]Menouer T. KCSS: Kubernetes container scheduling strategy. The Journal of Supercomputing. 2021; 77(5):4267-93.

[28]Yang S, Wang X, An L, Zhang G. Yun: a high-performance container management service based on OpenStack. In fourth international conference on data science in cyberspace (DSC) 2019 (pp. 202-9). IEEE.

[29]Smimite O, Afdel K. Hybrid solution for container placement and load balancing based on ACO and bin packing. International Journal of Advanced Computer Science and Applications. 2020; 11(11).

[30]Mattia GP, Beraldi R. P2PFaaS: a framework for FaaS peer-to-peer scheduling and load balancing in fog and edge computing. SoftwareX. 2023; 21:101290.

[31]Li Y, Xia Y. Auto-scaling web applications in hybrid cloud based on docker. In 5th international conference on computer science and network technology (ICCSNT) 2016 (pp. 75-9). IEEE.

[32]Patra MK, Misra S, Sahoo B, Turuk AK. GWO-based simulated annealing approach for load balancing in cloud for hosting container as a service. Applied Sciences. 2022; 12(21):11115.

[33]Lin J, Cui D, Peng Z, Li Q, He J, Guo M. Virtualized resource scheduling in cloud computing environments: an review. In conference on telecommunications, optics and computer science (TOCS) 2020 (pp. 303-8). IEEE.

[34]Yang S, Wang X, Wang X, An L, Zhang G. High-performance docker integration scheme based on OpenStack. World Wide Web. 2020; 23(4):2593-632.

[35]Kim WY, Lee JS, Huh EN. Study on proactive auto scaling for instance through the prediction of network traffic on the container environment. In proceedings of the 11th international conference on ubiquitous information management and communication 2017 (pp. 1-8). ACM.

[36]Talukder A, Abedin SF, Munir MS, Hong CS. Dual threshold load balancing in SDN environment using process migration. In international conference on information networking (ICOIN) 2018 (pp. 791-6). IEEE.

[37]Elmagzoub MA, Syed D, Shaikh A, Islam N, Alghamdi A, Rizwan S. A survey of swarm intelligence based load balancing techniques in cloud computing environment. Electronics. 2021; 10(21):1-46.

[38]Song X, Ma Y, Teng D. A load balancing scheme using federate migration based on virtual machines for cloud simulations. Mathematical Problems in Engineering. 2015; 2015(1):506432.

[39]Afzal S, Kavitha G. Load balancing in cloud computing–a hierarchical taxonomical classification. Journal of Cloud Computing. 2019; 8(1):1-24.

[40]Naik KD, Sahoo RR, Kuana SK. A bio inspired approach for load balancing in container as a service cloud computing model. International Research Journal on Advanced Science Hub. 2023; 5(5):426-33.

[41]Polikarpova N, Tschannen J, Furia CA. A fully verified container library. In international symposium on formal methods 2015 (pp. 414-34). Cham: Springer International Publishing.

[42]Lee YJ, Park GY, Song HK, Youn HY. A load balancing scheme for distributed simulation based on multi-agent system. In 36th annual computer software and applications conference workshops 2012 (pp. 613-8). IEEE.

[43]Tao Y, Wang X, Xu X, Chen Y. Dynamic resource allocation algorithm for container-based service computing. In 13th international symposium on autonomous decentralized system (ISADS) 2017 (pp. 61-7). IEEE.

[44]Zhiyong C, Xiaolan X. An improved container cloud resource scheduling strategy. In proceedings of the 4th international conference on intelligent information processing 2019 (pp. 383-7).

[45]Li P, Song J, Xu H, Dong L, Zhou Y. Resource scheduling optimisation algorithm for containerised microservice architecture in cloud computing. International Journal of High Performance Systems Architecture. 2018; 8(1-2):51-8.

[46]Mao Y, Oak J, Pompili A, Beer D, Han T, Hu P. Draps: dynamic and resource-aware placement scheme for docker containers in a heterogeneous cluster. In 36th international performance computing and communications conference (IPCCC) 2017 (pp. 1-8). IEEE.

[47]Tihfon GM, Kim J, Kim KJ. A new virtualized environment for application deployment based on docker and AWS. In information science and applications (ICISA) 2016 (pp. 1339-49). Springer Singapore.

[48]Long X, Liu B, Jiang F, Zhang Q, Zhi X. FPGA virtualization deployment based on docker container technology. In 5th international conference on mechanical, control and computer engineering (ICMCCE) 2020 (pp. 473-6). IEEE.

[49]Imdoukh M, Ahmad I, Alfailakawi MG. Machine learning-based auto-scaling for containerized applications. Neural Computing and Applications. 2020; 32(13):9745-60.

[50]Mondesire SC, Angelopoulou A, Sirigampola S, Goldiez B. Combining virtualization and containerization to support interactive games and simulations on the cloud. Simulation Modelling Practice and Theory. 2019; 93:233-44.

[51]El KS, El MI, Salah K, Hanini M. Dynamic scalability model for containerized cloud services. Arabian Journal for Science and Engineering. 2020; 45(12):10693-708.

[52]Celesti A, Mulfari D, Galletta A, Fazio M, Carnevale L, Villari M. A study on container virtualization for guarantee quality of service in cloud-of-things. Future Generation Computer Systems. 2019; 99:356-64.

[53]Xiaojing XI, Govardhan SS. A service mesh-based load balancing and task scheduling system for deep learning applications. In 20th international symposium on cluster, cloud and internet computing (CCGRID) 2020 (pp. 843-9). IEEE.

[54]Thongthavorn W, Rattanatamrong P. Multi-container application migration with load balanced and adaptive parallel TCP. In international conference on high performance computing & simulation (HPCS) 2019 (pp. 55-62). IEEE.

[55]Vaishali KR, Rammohan SR, Natrayan L, Usha D, Niveditha VR. Guided container selection for data streaming through neural learning in cloud. International Journal of System Assurance Engineering and Management. 2021:1-7.

[56]Hofer F, Sehr MA, Iannopollo A, Ugalde I, Sangiovanni-vincentelli A, Russo B. Industrial control via application containers: migrating from bare-metal to IAAS. In international conference on cloud computing technology and science (CloudCom), Sydney, NSW, Australia, 2019 (pp. 62-9). IEEE.

[57]Ma H, Wang L, Tak BC, Wang L, Tang C. Auto-tuning performance of MPI parallel programs using resource management in container-based virtual cloud. In 9th international conference on cloud computing (CLOUD) 2016 (pp. 545-52). IEEE.

[58]Kanchanadevi P, Kumar VA, Kumar GA. Optimal resource allocation and load balancing for a container as a service in a cloud computing. Journal of Critical Reviews. 2020; 7(4):900-2.

[59]Souza A, Wen Z, Cacho N, Romanovsky A, James P, Ranjan R. Using osmotic services composition for dynamic load balancing of smart city applications. In 11th conference on service-oriented computing and applications (SOCA) 2018 (pp. 145-52). IEEE.

[60]Baburao D, Pavankumar T, Prabhu CS. Load balancing in the fog nodes using particle swarm optimization-based enhanced dynamic resource allocation method. Applied Nanoscience. 2023; 13(2):1045-54.

[61]Pérez DPR, García-galán S, Muñoz-expósito JE, Marchewka A, Ruiz-reyes N. Smart containers schedulers for microservices provision in cloud-fog-IoT networks. Challenges and Opportunities. Sensors. 2020; 20(6):1-21.

[62]Li X, Jiang Y, Ding Y, Wei D, Ma X, Li W. Application research of docker based on mesos application container cluster. In international conference on computer vision, image and deep learning (CVIDL) 2020 (pp. 476-9). IEEE.

[63]Choudhury S, Maheshwari S, Seskar I, Raychaudhuri D. Shareon: shared resource dynamic container migration framework for real-time support in mobile edge clouds. IEEE Access. 2022; 10:66045-60.

[64]Baburao D, Pavankumar T, Prabhu CS. Survey on service migration, load optimization and load balancing in fog computing environment. In 5th international conference for convergence in technology (I2CT) 2019 (pp. 1-5). IEEE.

[65]Singh A, Aujla GS, Bali RS. Container-based load balancing for energy efficiency in software-defined edge computing environment. Sustainable Computing: Informatics and Systems. 2021; 30:100463.

[66]Ma Z, Shao S, Guo S, Wang Z, Qi F, Xiong A. Container migration mechanism for load balancing in edge network under power internet of things. IEEE Access. 2020; 8:118405-16.

[67]Li K, Chang C, Yun K, Zhang J. Research on container migration mechanism of power edge computing on load balancing. In 6th international conference on cloud computing and big data analytics (ICCCBDA) 2021 (pp. 386-90). IEEE.

[68]Singh J, Singh P, Amhoud EM, Hedabou M. Energy-efficient and secure load balancing technique for SDN-enabled fog computing. Sustainability. 2022; 14(19):1-22.

[69]Alqahtani F, Amoon M, Nasr AA. Reliable scheduling and load balancing for requests in cloud-fog computing. Peer-to-Peer Networking and Applications. 2021; 14(4):1905-16.

[70]Dlamini T, Vilakati S. LSTM‐based traffic load balancing and resource allocation for an edge system. Wireless Communications and Mobile Computing. 2020;2020(1):8825396.

[71]Chen CH, Liu CT. A 3.5-tier container-based edge computing architecture. Computers & Electrical Engineering. 2021; 93:107227.

[72]Khan A. Key characteristics of a container orchestration platform to enable a modern application. IEEE Cloud Computing. 2017; 4(5):42-8.

[73]Hussein MK, Mousa MH, Alqarni MA. A placement architecture for a container as a service (CaaS) in a cloud environment. Journal of Cloud Computing. 2019; 8:1-5.

[74]Zhong Z, Buyya R. A cost-efficient container orchestration strategy in Kubernetes-based cloud computing infrastructures with heterogeneous resources. ACM Transactions on Internet Technology (TOIT). 2020; 20(2):1-24.

[75]Littley M, Anwar A, Fayyaz H, Fayyaz Z, Tarasov V, Rupprecht L, et al. Bolt: towards a scalable docker registry via hyperconvergence. In 12th international conference on cloud computing (CLOUD) 2019 (pp. 358-66). IEEE.

[76]Louati T, Abbes H, Cérin C, Jemni M. Lxcloud-cr: towards linux containers distributed hash table based checkpoint-restart. Journal of Parallel and Distributed Computing. 2018; 111:187-205.

[77]Louati T, Abbes H, Cérin C. LXCloudFT: towards high availability, fault tolerant cloud system based Linux containers. Journal of Parallel and Distributed Computing. 2018; 122:51-69.

[78]Martin JP, Kandasamy A, Chandrasekaran K. Exploring the support for high performance applications in the container runtime environment. Human-centric Computing and Information Sciences. 2018; 8:1-5.

[79]Wan F, Wu X, Zhang Q. Chain-oriented load balancing in microservice system. In world conference on computing and communication technologies (WCCCT) 2020 (pp. 10-4). IEEE.

[80]Kaur K, Guillemin F, Sailhan F. Container placement and migration strategies for cloud, fog, and edge data centers: a survey. International Journal of Network Management. 2022; 32(6):e2212.

[81]Muthakshi S, Mahesh K. Container selection processing implementing extensive neural learning in cloud services. Materials Today: Proceedings. 2023; 80:1868-71.

[82]Queiroz R, Cruz T, Mendes J, Sousa P, Simões P. Container-based virtualization for real-time industrial systems-a systematic review. ACM Computing Surveys. 2023; 56(3):1-38.

[83]Rizvi H, Rahman HU. Load balancing on cloud computing. International Journal of Creative Research Thoughts. 2023; 11(4):927-31.

[84]Gamal M, Rizk R, Mahdi H, Elhady B. Bio-inspired load balancing algorithm in cloud computing. In proceedings of the international conference on advanced intelligent systems and informatics 2018 (pp. 579-89). Springer International Publishing.

[85]Peinl R, Holzschuher F, Pfitzer F. Docker cluster management for the cloud-survey results and own solution. Journal of Grid Computing. 2016; 14(2):265-82.

[86]Tihfon GM, Park S, Kim J, Kim YM. An efficient multi-task PaaS cloud infrastructure based on docker and AWS ECS for application deployment. Cluster Computing. 2016; 19:1585-97.

[87]Pahl C, Lee B. Containers and clusters for edge cloud architectures-a technology review. In 3rd international conference on future internet of things and cloud 2015 (pp. 379-86). IEEE.

[88]Zheng G, Fu Y, Wu T. Research on docker cluster scheduling based on self-define kubernetes scheduler. In journal of physics: conference series 2021 (pp. 1-6). IOP Publishing.

[89]Hu Y, De LC, Zhao Z. Multi-objective container deployment on heterogeneous clusters. In 19th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGRID) 2019 (pp. 592-9). IEEE.

[90]Nguyen N, Kim T. Toward highly scalable load balancing in kubernetes clusters. IEEE Communications Magazine. 2020; 58(7):78-83.

[91]Wang L, Guo S, Zhang P, Yue H, Li Y, Wang C, et al. An efficient load prediction‐driven scheduling strategy model in container cloud. International Journal of Intelligent Systems. 2023; 2023(1):5959223.

[92]Hanafy WA, Mohamed AE, Salem SA. Novel selection policies for container-based cloud deployment models. In 13th international computer engineering conference (ICENCO) 2017 (pp. 237-42). IEEE.

[93]De AMC, Solis P. An algorithm based on response time and traffic demands to scale containers on a cloud computing system. In 15th international symposium on network computing and applications (NCA) 2016 (pp. 343-50). IEEE.

[94]Manu AR, Patel JK, Akhtar S, Agrawal VK, Murthy KB. Docker container security via heuristics-based multilateral security-conceptual and pragmatic study. In international conference on circuit, power and computing technologies (ICCPCT) 2016 (pp. 1-14). IEEE.

[95]Aksakalli IK, Celik T, Can AB, Tekinerdogan B. Systematic approach for generation of feasible deployment alternatives for microservices. IEEE Access. 2021; 9:29505-29.

[96]Rajasekar P, Palanichamy Y. Scheduling multiple scientific workflows using containers on IaaS cloud. Journal of Ambient Intelligence and Humanized Computing. 2021; 12:7621-36.

[97]Jiang C, Wu P. A fine‐grained horizontal scaling method for container‐based cloud. Scientific Programming. 2021; 2021(1):6397786.

[98]Casalicchio E, Iannucci S. The state‐of‐the‐art in container technologies: application, orchestration and security. Concurrency and Computation: Practice and Experience. 2020; 32(17):e5668.

[99]Kuramoto K, Furuichi M, Kakuda K. Efficient load-balancing scheme for multi-agent simulation systems. Computer Modeling in Engineering & Sciences. 2015; 106(3):169-86.