Abstract
Cloud computing is largely adopted by the current computing industry. Not only users can benefit from cloud scalability, but also businesses are more and more attracted by its flexibility. In addition, the number of offered cloud services (e.g., SaaS, BPaaS, mobile services, etc.) is continuously growing. This raises a question about how to effectively arrange and place them in the cloud, in order to offer high-performance services. Indeed, companies’ and providers’ benefits are strongly related to the optimal placement and management of cloud services, together with their related data. This produces various challenges, including the heterogeneity and dynamicity of hosting cloud zones, the cloud/service -specific placement constraints, etc. Recent cloud service placement approaches have dealt with these issues through different techniques, and by fixing various criteria to optimize. Moreover, researchers have considered other specificities, like the cloud environment type, the deployment model and the placement mode. This paper provides a comprehensive survey on service placement schemes in the cloud. We also identify the current challenges for different cloud service models and environments, and we provide our future directions.
Similar content being viewed by others
Data Availability
The authors declare that there was no dataset exploited to conduct this survey.
References
Toosi, A.N., Calheiros, R.N., Buyya, R.: Interconnected cloud computing environments: Challenges, taxonomy, and survey. ACM Comput. Surv. (CSUR) 47(1), 1–47 (2014)
Guzek, M., Bouvry, P., Talbi, E.-G.: A survey of evolutionary computation for resource management of processing in cloud computing. IEEE Comput. Intell. Mag. 10(2), 53–67 (2015)
Yusoh, Z.I.M., Tang, M.: A penalty-based genetic algorithm for the composite saas placement problem in the cloud. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp 1–8. IEEE (2010)
Petcu, D., Stankovski, V.: Towards cloud-enabled business process management based on patterns, rules and multiple models. In: 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications (ISPA), pp 454–459. IEEE (2012)
Yusoh, Z.I.M., Tang, M.: A cooperative coevolutionary algorithm for the composite saas placement problem in the cloud. In: International Conference on Neural Information Processing, pp 618–625. Springer (2010)
Kang, Y., Zheng, Z., Lyu, M.R.: A latency-aware co-deployment mechanism for cloud-based services. In: 2012 IEEE 5th International Conference on Cloud Computing (CLOUD), pp 630–637. IEEE (2012)
Tortonesi, M., Foschini, L.: Business-driven service placement for highly dynamic and distributed cloud systems. IEEE Trans. Cloud Comput.
Huang, K.-C., Lu, Y.-C., Tsai, M.-H., Wu, Y.-J., Chang, H.-Y.: Performance-efficient service deployment and scheduling methods for composite cloud services. In: Proceedings of the 9th International Conference on Utility and Cloud Computing, pp 240–244. ACM (2016)
Goettelmann, E., Dahman, K., Gâteau, B., Godart, C.: A formal broker framework for secure and cost-effective business process deployment on multiple clouds. In: Forum at the Conference on Advanced Information Systems Engineering (CAiSE), pp 3–19. Springer (2014)
Accorsi, R.: Business process as a service: Chances for remote auditing. In: 2011 IEEE 35th Annual Computer Software and Applications Conference Workshops (COMPSACW), pp 398–403. IEEE (2011)
Nacer, A.A., Goettelmann, E., Youcef, S., Tari, A., Godart, C.: Obfuscating a business process by splitting its logic with fake fragments for securing a multi-cloud deployment. In: 2016 IEEE World Congress on Services (SERVICES), pp 18–25. IEEE (2016)
Rekik, M., Boukadi, K., Assy, N., Gaaloul, W., Ben-Abdallah, H.: A linear program for optimal configurable business processes deployment into cloud federation. In: 2016 IEEE International Conference on Services Computing (SCC), pp 34–41. IEEE (2016)
Foschini, L., Tortonesi, M.: Adaptive and business-driven service placement in federated cloud computing environments. In: 2013 IFIP/IEEE International Symposium On Integrated Network Management (IM 2013), pp 1245–1251. IEEE (2013)
Liu, H., Charif, Y., Jung, G., Quiroz, A., Goetz, F., Sharma, N.: Towards simplifying and automating business process lifecycle management in hybrid clouds. In: 2012 IEEE 19th International Conference on Web Services (ICWS), pp 592–599. IEEE (2012)
Goettelmann, E., Fdhila, W., Godart, C.: Partitioning and cloud deployment of composite web services under security constraints. In: 2013 IEEE International Conference on Cloud Engineering (IC2E), pp 193–200. IEEE (2013)
Wang, S., Urgaonkar, R., He, T., Chan, K., Zafer, M., Leung, K.K.: Dynamic service placement for mobile micro-clouds with predicted future costs. IEEE Trans. Parallel Distrib. Syst. 28(4), 1002–1016 (2017)
Ouyang, T., Zhou, Z., Chen, X.: Follow me at the edge: Mobility-aware dynamic service placement for mobile edge computing. IEEE J. Sel. Areas Commun. 36(10), 2333–2345 (2018)
Wang, Y., Zhao, C., Yang, S., Ren, X., Wang, L., Zhao, P., Yang, X.: Mpcsm: Microservice placement for edge-cloud collaborative smart manufacturing. IEEE Trans Ind Inf
Mahmud, R., Srirama, S.N., Ramamohanarao, K., Buyya, R.: Profit-aware application placement for integrated fog–cloud computing environments. IEEE J. Sel. Areas Commun. 135, 177–190 (2020)
Bowen, Y., Shaochun, W.: An adaptive simulated annealing genetic algorithm for the data placement problem in saas. In: 2012 International Conference on Industrial Control and Electronics Engineering (ICICEE), pp 1037–1043. IEEE (2012)
Liu, Z., Hu, Z., Jonepun, L.K.: Research on composite saas placement problem based on ant colony optimization algorithm with performance matching degree strategy. JDIM 12(4), 225–234 (2014)
Mezni, H., Kouki, J.: A multi-swarm based approach with cooperative learning strategy for composite saas placement. In: Proceedings of the Symposium on Applied Computing, pp 399–404. ACM (2017)
Rekik, M., Boukadi, K., Assy, N., Gaaloul, W., Ben-Abdallah, H.: Optimal deployment of configurable business processes in cloud federations. IEEE Trans. Netw. Serv. Manag. 15(4), 1692–1705 (2018)
Wen, Z., Cala, J., Watson, P., Romanovsky, A.: Cost effective, reliable and secure workflow deployment over federated clouds. IEEE Trans. Serv. Comput.
Ramadoss, R., Elango, N., Satheesh, A., Hsu, C. -H.: Pspo: a framework for cost-effective service placement optimisation during enterprise modernisation on hybrid clouds. Int. J. Web Grid Serv. 14(2), 170–199 (2018)
Charrada, F.B., Tebourski, N., Tata, S., Moalla, S.: Approximate placement of service-based applications in hybrid clouds. In: 2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp 161–166. IEEE (2012)
Agarwal, S., Dunagan, J., Jain, N., Saroiu, S., Wolman, A., Bhogan, H.: Volley: Automated data placement for geo- distributed cloud services. In: NSDI, vol. 10, p 28 (2010)
Charrada, F.B., Tata, S.: An efficient algorithm for the bursting of service-based applications in hybrid clouds. IEEE Trans. Serv. Comput. 9(3), 357–367 (2016)
Selimi, M., Cerdà-Alabern, L., Freitag, F., Veiga, L., Sathiaseelan, A., Crowcroft, J.: A lightweight service placement approach for community network micro-clouds. J. Grid Comput., 1–21 (2018)
Zong, B., Raghavendra, R., Srivatsa, M., Yan, X., K. Singh, A., Lee, K.-W.: Cloud service placement via subgraph matching. In: 2014 IEEE 30th International Conference on Data Engineering (ICDE), pp 832–843. IEEE (2014)
Souza, V., Masip-Bruin, X., Marín-Tordera, E., Sànchez-López, S., Garcia, J., Ren, G. -J., Jukan, A., Ferrer, A.J.: Towards a proper service placement in combined fog-to-cloud (f2c) architectures. Futur. Gener. Comput. Syst. 87, 1–15 (2018)
Kwok, T., Mohindra, A.: Resource calculations with constraints, and placement of tenants and instances for multi-tenant saas applications. In: International Conference on Service-Oriented Computing, pp 633–648. Springer (2008)
Goettelmann, E., Dahman, K., Gateau, B., Dubois, E., Godart, C.: A security risk assessment model for business process deployment in the cloud. In: 2014 IEEE International Conference on Services Computing (SCC), pp 307–314. IEEE (2014)
Tang, M., Yusoh, Z.: A parallel cooperative co-evolutionary genetic algorithm for the composite saas placement problem in cloud computing. In: Parallel Problem Solving from Nature-PPSN XII, pp 225–234 (2012)
Cerroni, W., Foschini, L., Grabarnik, G.Y., Shwartz, L., Tortonesi, M.: Service placement for hybrid clouds environments based on realistic network measurements. In: 2018 14th International Conference on Network and Service Management (CNSM), pp 184–190. IEEE (2018)
Ochei, L.C., Petrovski, A., Bass, J.M.: Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. J. Cloud Comput. 8(1), 1 (2019)
Unuvar, M., Tosi, S., Doganata, Y.N., Steinder, M.G., Tantawi, A.N.: Selecting optimum cloud availability zones by learning user satisfaction levels. IEEE Trans. Serv. Comput. 8(2), 199–211 (2015)
Yang, L., Cao, J., Liang, G., Han, X.: Cost aware service placement and load dispatching in mobile cloud systems. IEEE Trans. Comput. 65(5), 1440–1452 (2016)
Hedhli, A., Mezni, H.: A dfa-based approach for the deployment of bpaas fragments in the cloud. Concurr. Comput. Pract. Exper. ,e5075
Tordsson, J., Montero, R.S., Moreno-Vozmediano, R., Llorente, I.M.: Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers. Futur. Gener. Comput. Syst. 28(2), 358–367 (2012)
Aldawsari, B., Baker, T., England, D.: Towards a holistic multi-cloud brokerage system: Taxonomy, survey, and future directions. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), pp 1467–1472. IEEE (2015)
Espling, D., Larsson, L., Li, W., Tordsson, J., Elmroth, E.: Modeling and placement of cloud services with internal structure. IEEE Trans. Cloud Comput. 4(4), 429–439 (2016)
Zhang, Q., Zhu, Q., Zhani, M.F., Boutaba, R., Hellerstein, J.L.: Dynamic service placement in geographically distributed clouds. IEEE J. Sel. Areas Commun. 31(12), 762–772 (2013)
Huang, K.-C., Shen, B.-J.: Service deployment strategies for efficient execution of composite saas applications on cloud platform. J. Syst. Softw. 107, 127–141 (2015)
Gomes, R., Lima, J., Costa, F., da Rocha, R., Georgantas, N.: A model-based approach for the pragmatic deployment of service choreographies. In: European Conference on Service-Oriented and Cloud Computing, pp 153–165. Springer (2015)
Mahdhi, T., Mezni, H.: A prediction-based vm consolidation approach in iaas cloud data centers. J. Syst. Softw. 146, 263–285 (2018)
Lucas-Simarro, J.L., Moreno-Vozmediano, R., Montero, R.S., Llorente, I.M.: Scheduling strategies for optimal service deployment across multiple clouds. Futur. Gener. Comput. Syst. 29(6), 1431–1441 (2013)
Sellami, M., Mezni, H., Hacid, M.S., Gammoudi, M.M.: Clustering-based data placement in cloud computing: a predictive approach. Clust. Comput., 1–37 (2021)
Shao, Y., Li, C., Tang, H.: A data replica placement strategy for iot workflows in collaborative edge and cloud environments. Comput. Netw. 148, 46–59 (2019)
Renart, E.G., Veith, A.D.S., Balouek-Thomert, D., de Assuncao, M.D., Lefèvre, L., Parashar, M.: Distributed operator placement for iot data analytics across edge and cloud resources. In: CCGrid 2019 - 19th Annual IEEE/ACM International Symposium in Cluster, Cloud and Grid Computing (2019)
Wang, S., Xu, J., Zhang, N., Liu, Y.: A survey on service migration in mobile edge computing. IEEE Access 6, 23511–23528 (2018)
Ghobaei-Arani, M., Souri, A., Rahmanian, A.A.: Resource management approaches in fog computing: a comprehensive review. J. Grid Comput., 1–42 (2019)
Salaht, F.A., Desprez, F., Lebre, A.: An overview of service placement problem in fog and edge computing. ACM Comput. Surv. (CSUR) 53(3), 1–35 (2020)
Masdari, M., Nabavi, S.S., Ahmadi, V.: An overview of virtual machine placement schemes in cloud computing. J. Netw. Comput. Appl., 106–127 (2016)
Kaur, A., Gupta, P., Singh, M., Nayyar, A.: Data placement in era of cloud computing: a survey, taxonomy and open research issues. Scalable Comput. Pract. Exper. 20(2), 377–398 (2019)
Rejiba, Z., Masip-Bruin, X., Marín-Tordera, E.: A survey on mobility-induced service migration in the fog, edge, and related computing paradigms. ACM Comput. Surv. (CSUR) 52(5), 1–33 (2019)
Raghavendra, M.S., Chawla, P., Rana, A.: A survey of optimization algorithms for fog computing service placement. In: 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), pp 259–262. IEEE (2020)
Wittenburg, G., Schiller, J.: A survey of current directions in service placement in mobile ad-hoc networks. In: 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom), pp 548–553. IEEE (2008)
Ali, S., Mitschele-Thiel, A., Diab, A., Rasheed, A.: A survey of services placement mechanisms for future mobile communication networks. In: Proceedings of the 8th International Conference on Frontiers of Information Technology, pp 1–5 (2010)
Lai, C.-M., Yeh, W.-C., Huang, Y.-C.: Entropic simplified swarm optimization for the task assignment problem. Appl. Soft Comput. 58, 115–127 (2017)
Ni, Z.W., Pan, X.F., Wu, Z.J.: An ant colony optimization for the composite saas placement problem in the cloud. In: Applied Mechanics and Materials, vol. 130, pp 3062–3067. Trans Tech Publ (2012)
Mouradian, C., Kianpisheh, S., Abu-Lebdeh, M., Ebrahimnezhad, F., Jahromi, N.T., Glitho, R.H.: Application component placement in nfv-based hybrid cloud/fog systems with mobile fog nodes. IEEE J. Sel. Areas Commun. 37(5), 1130–1143 (2019)
Hajji, M.A., Mezni, H.: A composite particle swarm optimization approach for the composite saas placement in cloud environment. Soft. Comput., 1–21 (2017)
Tantawi, A.N.: Quantitative placement of services in hierarchical clouds. In: International Conference on Quantitative Evaluation of Systems, pp 195–210. Springer (2015)
Petcu, D.: Multi-cloud: expectations and current approaches. In: Proceedings of the 2013 international workshop on Multi-cloud applications and federated clouds, pp 1–6. ACM (2013)
Dastjerdi, A.V., Garg, S.K., Rana, O.F., Buyya, R.: Cloudpick: a framework for qos-aware and ontology-based service deployment across clouds. Softw. Pract. Exper. 45(2), 197–231 (2015)
Tärneberg, W., Mehta, A., Wadbro, E., Tordsson, J., Eker, J., Kihl, M., Elmroth, E.: Dynamic application placement in the mobile cloud network. Futur. Gener. Comput. Syst. 70, 163–177 (2017)
Skarlat, O., Karagiannis, V., Rausch, T., Bachmann, K., Schulte, S.: A framework for optimization, service placement, and runtime operation in the fog. In: 2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC), pp 164–173. IEEE (2018)
Lera, I., Guerrero, C., Juiz, C.: Availability-aware service placement policy in fog computing based on graph partitions. IEEE Internet Things J.
Guerrero, C., Lera, I., Juiz, C.: A lightweight decentralized service placement policy for performance optimization in fog computing. J. Ambient. Intell. Humaniz. Comput., 1–18 (2018)
Cappanera, P., Paganelli, F., Paradiso, F.: Vnf placement for service chaining in a distributed cloud environment with multiple stakeholders. Comput. Commun. 133, 24–40 (2019)
Altmann, J., Kashef, M.M.: Cost model based service placement in federated hybrid clouds. Futur. Gener. Comput. Syst. 41, 79–90 (2014)
Javadi, B., Abawajy, J., Buyya, R.: Failure-aware resource provisioning for hybrid cloud infrastructure. J. Parallel Distrib. Comput. 72(10), 1318–1331 (2012)
Chang, H., Hari, A., Mukherjee, S., Lakshman, T.: Bringing the cloud to the edge. In: 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp 346–351. IEEE (2014)
Yuan, X., Sun, M., Lou, W.: A dynamic deep-learning-based virtual edge node placement scheme for edge cloud systems in mobile environment. IEEE Trans. Cloud Comput.
Brik, B., Frangoudis, P.A., Ksentini, A.: Service-oriented mec applications placement in a federated edge cloud architecture. In: ICC 2020-2020 IEEE International Conference on Communications (ICC), pp 1–6. IEEE (2020)
Moubayed, A., Shami, A., Heidari, P., Larabi, A., Brunner, R.: Cost-optimal v2x service placement in distributed cloud/edge environment. In: 2020 16th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)(50308), pp 1–6. IEEE (2020)
Tsipis, A., Komianos, V., Oikonomou, K., Stavrakakis, I.: Elastic distributed rendering service placement in capacitated cloud/fog gaming systems. In: 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA), pp 1–8. IEEE (2020)
Mudam, R., Bhartia, S., Chattopadhyay, S., Bhattacharya, A.: Mobility-aware service placement for vehicular users in edge-cloud environment. In: International Conference on Service-Oriented Computing, pp 248–265. Springer (2020)
Perez, D.A.L., Rothenberg, C.E., Santos, M., Gomes, P.H.: Ani: Abstracted network inventory for streamlined service placement in distributed clouds. IEEE (2020)
Farhadi, V., Mehmeti, F., He, T., La Porta, T., Khamfroush, H., Wang, S., Chan, K.S.: Service placement and request scheduling for data-intensive applications in edge clouds. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp 1279–1287. IEEE (2019)
Fang, J., Ma, A.: Iot application modules placement and dynamic task processing in edge-cloud computing. IEEE Internet Things J. (2020)
Hassan, H.O., Azizi, S., Shojafar, M.: Priority, network and energy-aware placement of iot-based application services in fog-cloud environments. IET Commun. 14(13), 2117–2129 (2020)
Li, B., Li, J., Huai, J., Wo, T., Li, Q., Zhong, L.: Enacloud: An energy-saving application live placement approach for cloud computing environments. In: IEEE International Conference on Cloud Computing, 2009. CLOUD’09, pp 17–24. IEEE (2009)
Hou, S.-L., Zhao, S., Cheng, B., Cheng, Y.-Y., Chen, J.-L.: Fragmentation and optimal deployment for iot-aware business process. In: 2016 IEEE International Conference on Services Computing (SCC), pp 657–664. IEEE (2016)
Na, T., Park, P., Ryu, H., Kim, T., Kim, J., Park, J.: Optimal service placement using pseudo service chaining mechanism for cloud-based multimedia services. Multimed. Tools Appl., 1–19 (2020)
Hasselmeyer, P., Qu, C., Schubert, L., Koller, B., Wieder, P.: Towards autonomous brokered sla negotiation. In: Exploiting the Knowledge Economy-Issues, Applications, Case Studies, vol. 3, pp 44–51 (2006)
Sailer, A., Head, M.R., Kochut, A., Shaikh, H.: Graph-based cloud service placement. In: 2010 IEEE International Conference on Services Computing (SCC), pp 89–96. IEEE (2010)
Mezni, H., Sellami, M., Kouki, J.: Security-aware saas placement using swarm intelligence. J. Softw. Evol. Process, e1932 (2018)
Mezni, H., Aridhi, S., Hadjali, A.: The uncertain cloud: State of the art and research challenges. Int. J. Approx. Reason. 103, 139–151 (2018)
Ghobaei-Arani, M., Rahmanian, A.A., Souri, A., Rahmani, A.M.: A moth-flame optimization algorithm for web service composition in cloud computing: simulation and verification. Softw. Pract. Exper. 48(10), 1865–1892 (2018)
Ghobaei-Arani, M., Souri, A.: Lp-wsc: a linear programming approach for web service composition in geographically distributed cloud environments. J. Supercomput. 75(5), 2603–2628 (2019)
Ghobaei-Arani, M., Rahmanian, A.A., Aslanpour, M.S., Dashti, S.E.: Csa-wsc: cuckoo search algorithm for web service composition in cloud environments. Soft. Comput. 22(24), 8353–8378 (2018)
Grivas, S.G., Kumar, T.U., Wache, H.: Cloud broker: Bringing intelligence into the cloud. In: 2010 IEEE 3rd International Conference on Cloud Computing (CLOUD), pp 544–545. IEEE (2010)
Mezni, H., Sellami, M., Aridhi, S., Ben Charrada, F.: Towards big services: A synergy between service computing and parallel programming. Computing, 1–1 (2021)
Xu, X., Sheng, Q.Z., Zhang, L.-J., Fan, Y., Dustdar, S.: From big data to big service. Computer 48(7), 80–83 (2015)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hedhli, A., Mezni, H. A Survey of Service Placement in Cloud Environments. J Grid Computing 19, 23 (2021). https://doi.org/10.1007/s10723-021-09565-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10723-021-09565-z