{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T14:39:52Z","timestamp":1774967992557,"version":"3.50.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100009934","name":"E\u00f6tv\u00f6s Lor\u00e1nd University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100009934","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Grid Computing"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Explosive growth in IoT and cloud infrastructures presents significant challenges for data placement across geographically dispersed data centers. Existing placement strategies improve performance but often fall short of substantially reducing transmission latencies and ensuring load balance across these centers. This paper proposes the Optimal Data Placement Method (ODPM) for effective data placement strategies in geographically distributed cloud environments. ODPM has two parts; the first one is an integration of Vogel\u2019s Approximation Method (VAM) and the Modified Distribution (MODI) technique to deal with cost reduction, load balance distribution, and capacity constraints in distributed cloud data centers. The VAM ensures an efficient starting point for solving the data transportation problem, while MODI method works on optimizing the solutions provided by VAM. The second part uses Floyd\u2019s shortest path algorithm to find the shortest distance between IoT devices and cloud storage to minimize data transmission time and cost. The combined approach focuses on three aspects, the data transmission time, computation time, and load balance between cloud data centers. The experimental results demonstrate that ODPM reduces the data transmission time by 12% over current techniques such as Spectral Clustering on Hypergraphs (SpeCH) and data placement using Lagrangian relaxation (DPLR), and an 8% reduction in computation time for optimal paths calculation while 15% enhancement in load balancing. Integrating MODI and Floyd\u2019s algorithm, ODPM constitutes an efficient and realistic approach to big data allocation in contemporary cloud environments.<\/jats:p>","DOI":"10.1007\/s10723-025-09818-1","type":"journal-article","created":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T09:33:57Z","timestamp":1763976837000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Network-Aware Optimization for Efficient Data Placement in Geo-Distributed Cloud Systems"],"prefix":"10.1007","volume":"23","author":[{"given":"Ayad Hasan","family":"Adnan","sequence":"first","affiliation":[]},{"given":"Abbas M. Ali","family":"Al-Muqarm","sequence":"additional","affiliation":[]},{"given":"Ali S.","family":"Abosinnee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,24]]},"reference":[{"key":"9818_CR1","doi-asserted-by":"crossref","unstructured":"Mondal, A.S., Sanyal, M., Barua, H.B., Chattopadhyay, S., Mondal, K.C.: Comparative analysis of object-based big data storage systems on architectures and services: A recent survey. Journal of The Institution of Engineers (India): Series B, 1\u201316 (2024)","DOI":"10.1007\/s40031-023-00983-z"},{"key":"9818_CR2","doi-asserted-by":"crossref","unstructured":"Sabitha, R., Sydulu, S.J., Karthik, S., Kavitha, M.: Distributed file systems for cloud storage design and evolution. In: 2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), pp. 1\u20138. IEEE (2023)","DOI":"10.1109\/ICAEECI58247.2023.10370956"},{"issue":"2","key":"9818_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3572779","volume":"19","author":"J Li","year":"2023","unstructured":"Li, J., Wang, Q., Lee, P.P., Shi, C.: An in-depth comparative analysis of cloud block storage workloads: Findings and implications. ACM Trans. Storage 19(2), 1\u201332 (2023)","journal-title":"ACM Trans. Storage"},{"key":"9818_CR4","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.future.2021.05.026","volume":"124","author":"M Abd Elaziz","year":"2021","unstructured":"Abd Elaziz, M., Abualigah, L., Attiya, I.: Advanced optimization technique for scheduling IoT tasks in cloud-fog computing environments. Futur. Gener. Comput. Syst. 124, 142\u2013154 (2021)","journal-title":"Futur. Gener. Comput. Syst."},{"key":"9818_CR5","doi-asserted-by":"publisher","first-page":"64641","DOI":"10.1109\/ACCESS.2019.2917387","volume":"7","author":"HM Al-Kadhim","year":"2019","unstructured":"Al-Kadhim, H.M., Al-Raweshidy, H.S.: Energy efficient and reliable transport of data in cloud-based IoT. IEEE Access 7, 64641\u201364650 (2019)","journal-title":"IEEE Access"},{"key":"9818_CR6","doi-asserted-by":"crossref","unstructured":"Gromov, Y., Minin, Y., Eliseev, A., Alrammahi, A.A.H., Sari, F.A.: Synthesis of data transmission networks with specified survivability under negative external influences. In: 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA), pp. 630\u2013635. IEEE (2020)","DOI":"10.1109\/SUMMA50634.2020.9280669"},{"issue":"1","key":"9818_CR7","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1109\/JIOT.2014.2306328","volume":"1","author":"A Zanella","year":"2014","unstructured":"Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M.: Internet of Things for smart cities. IEEE Internet Things J. 1(1), 22\u201332 (2014)","journal-title":"IEEE Internet Things J."},{"issue":"1","key":"9818_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11227-024-06629-1","volume":"81","author":"AA Hussain","year":"2025","unstructured":"Hussain, A.A., Dawood, B.A.: A survey on IoT-cloud task in healthcare system. J. Supercomput. 81(1), 1\u201347 (2025)","journal-title":"J. Supercomput."},{"issue":"10","key":"9818_CR9","doi-asserted-by":"publisher","first-page":"2603","DOI":"10.3390\/agronomy13102603","volume":"13","author":"T Alahmad","year":"2023","unstructured":"Alahmad, T., Nem\u00e9nyi, M., Ny\u00e9ki, A.: Applying IoT sensors and big data to improve precision crop production: A review. Agronomy 13(10), 2603 (2023)","journal-title":"Agronomy"},{"key":"9818_CR10","doi-asserted-by":"crossref","unstructured":"Nangia, S., Makkar, S., Hassan, R.: IoT based predictive maintenance in manufacturing sector. In: Proceedings of the International Conference on Innovative Computing & Communications (ICICC) (2020)","DOI":"10.2139\/ssrn.3563559"},{"key":"9818_CR11","doi-asserted-by":"crossref","unstructured":"Shankar, B.P., Singh, U.K., Vijayalakshmi, Viji, C., Rajkumar, N., Stalin, M., Nachiappan, B.: Comparative analysis of dynamic data placement strategy in distributed cloud environment. In: International Conference on Data Engineering and Machine Intelligence, pp. 223\u2013242. Springer (2023)","DOI":"10.1007\/978-981-97-7616-0_16"},{"key":"9818_CR12","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.future.2021.08.014","volume":"127","author":"C Li","year":"2022","unstructured":"Li, C., Cai, Q., Lou, Y.: Optimal data placement strategy considering capacity limitation and load balancing in geographically distributed cloud. Futur. Gener. Comput. Syst. 127, 142\u2013159 (2022)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"9","key":"9818_CR13","doi-asserted-by":"publisher","first-page":"5769","DOI":"10.1007\/s00500-022-07805-2","volume":"27","author":"AA Mohamed","year":"2023","unstructured":"Mohamed, A.A., Abdellatif, A.D., Alburaikan, A., Khalifa, H.A.E.-W., Elaziz, M.A., Abualigah, L., AbdelMouty, A.M.: A novel hybrid arithmetic optimization algorithm and Salp swarm algorithm for data placement in cloud computing. Soft. Comput. 27(9), 5769\u20135780 (2023)","journal-title":"Soft. Comput."},{"issue":"1","key":"9818_CR14","first-page":"146","volume":"13","author":"B Kumar","year":"2020","unstructured":"Kumar, B., Reddy, E.: Modified floyd warshall algorithm for cache management in information centric network. Int. J. Intell. Eng. Syst. 13(1), 146\u2013155 (2020)","journal-title":"Int. J. Intell. Eng. Syst."},{"issue":"4","key":"9818_CR15","first-page":"501","volume":"64","author":"M Shrivastava","year":"2024","unstructured":"Shrivastava, M.: Optimal data placement for scientific workflows in cloud. J. Comput. Inf. Syst. 64(4), 501\u2013517 (2024)","journal-title":"J. Comput. Inf. Syst."},{"key":"9818_CR16","unstructured":"Udenwagu, N., Oni, A., Ezenwoke, A.: Comparative study of different inertia weight strategies in particle swarm optimization based on actual computational time cost. Int. J. Theor. Appl. Mech. 9 (2025)"},{"issue":"5","key":"9818_CR17","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/s10462-024-10756-9","volume":"57","author":"G Zhou","year":"2024","unstructured":"Zhou, G., Tian, W., Buyya, R., Xue, R., Song, L.: Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions. Artif. Intell. Rev. 57(5), 124 (2024)","journal-title":"Artif. Intell. Rev."},{"key":"9818_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jnca.2019.05.012","volume":"142","author":"A Atrey","year":"2019","unstructured":"Atrey, A., Van Seghbroeck, G., Mora, H., De Turck, F., Volckaert, B.: SpeCH: A scalable framework for data placement of data-intensive services in geo-distributed clouds. J. Netw. Comput. Appl. 142, 1\u201314 (2019)","journal-title":"J. Netw. Comput. Appl."},{"key":"9818_CR19","doi-asserted-by":"crossref","unstructured":"Bouhouch, L., Zbakh, M., Tadonki, C.: A big data placement strategy in geographically distributed datacenters. In: 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech), pp. 1\u20139. IEEE (2020)","DOI":"10.1109\/CloudTech49835.2020.9365881"},{"key":"9818_CR20","doi-asserted-by":"publisher","first-page":"107050","DOI":"10.1016\/j.knosys.2021.107050","volume":"224","author":"C Li","year":"2021","unstructured":"Li, C., Liu, J., Li, W., Luo, Y.: Adaptive priority-based data placement and multi-task scheduling in geo-distributed cloud systems. Knowl.-Based Syst. 224, 107050 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"9818_CR21","doi-asserted-by":"crossref","unstructured":"Bouhouch, L., Zbakh, M., Tadonki, C.: A new classification for data placement techniques in cloud computing. In: 2023 IEEE 6th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech), pp. 1\u20139. IEEE (2023)","DOI":"10.1109\/CloudTech58737.2023.10366156"},{"key":"9818_CR22","doi-asserted-by":"publisher","first-page":"111227","DOI":"10.1016\/j.jss.2022.111227","volume":"187","author":"C Li","year":"2022","unstructured":"Li, C., Liu, J., Wang, M., Luo, Y.: Fault-tolerant scheduling and data placement for scientific workflow processing in geo-distributed clouds. J. Syst. Softw. 187, 111227 (2022)","journal-title":"J. Syst. Softw."},{"key":"9818_CR23","doi-asserted-by":"crossref","unstructured":"Wang, P., Qiao, J., Zhao, Y., Ding, Z.: Cost-effective and low-latency data placement in edge environment based on pagerank-inspired regional value. IEEE Transactions on Parallel and Distributed Systems (2024)","DOI":"10.1109\/TPDS.2024.3506625"},{"key":"9818_CR24","doi-asserted-by":"crossref","unstructured":"Mazumdar, S., Seybold, D., Kritikos, K., Verginadis, Y.: A survey on data storage and placement methodologies for cloud-big data ecosystem. J. Big Data 6(1), 1\u201337 (2019)","DOI":"10.1186\/s40537-019-0178-3"},{"issue":"3","key":"9818_CR25","first-page":"27","volume":"1","author":"I Kezia","year":"2024","unstructured":"Kezia, I., Afrizal, M.N., Soreninu, D.S.: Optimizing stepping stone methods and modified distribution (MODI) methods for cost optimization in cement distribution. Harmoni Eng. Int. J. Eng. Sci. Technol. 1(3), 27\u201335 (2024)","journal-title":"Harmoni Eng. Int. J. Eng. Sci. Technol."},{"key":"9818_CR26","doi-asserted-by":"crossref","unstructured":"Hussein, H., Shiker, M.: A modification to Vogel\u2019s approximation method to solve transportation problems. In: Journal of Physics: Conference Series, vol. 1591, p. 012029. IOP Publishing (2020)","DOI":"10.1088\/1742-6596\/1591\/1\/012029"},{"key":"9818_CR27","doi-asserted-by":"crossref","unstructured":"Wang, S., Liu, B., Liu, W., Hu, C., Tang, Y., Yang, J.: Research on the shortest path for crossing desert based on Floyd algorithm. In: 2021 IEEE 3rd International Conference on Frontiers Technology of Information and Computer (ICFTIC), pp. 1\u20134. IEEE (2021)","DOI":"10.1109\/ICFTIC54370.2021.9647205"},{"key":"9818_CR28","unstructured":"Yao, E., Yao, P., Bai, S.: Obstacle-free path planning for autonomous drones using Floyd algorithm (2024). arXiv:2409.13149"}],"container-title":["Journal of Grid Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10723-025-09818-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10723-025-09818-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10723-025-09818-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T07:44:41Z","timestamp":1766475881000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10723-025-09818-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,24]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["9818"],"URL":"https:\/\/doi.org\/10.1007\/s10723-025-09818-1","relation":{},"ISSN":["1570-7873","1572-9184"],"issn-type":[{"value":"1570-7873","type":"print"},{"value":"1572-9184","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,24]]},"assertion":[{"value":"20 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"30"}}