{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T05:09:34Z","timestamp":1723698574068},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T00:00:00Z","timestamp":1673913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T00:00:00Z","timestamp":1673913600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cloud Comp"],"abstract":"Abstract<\/jats:title>The popularity of cloud and fog services has raised the number of users exponentially. Main advantage of Cloud\/fog infrastructure and services are crucial specially for commercial users from diverse areas. The variety of service requests with different deadlines makes the task of a service broker challenging. The fog and cloud users always lookfor a suitable compromise between cost and quality of service in terms of response time therefore, the cost optimization is vital for the cloud\/fog service providers to capture the market. In this paper an algorithm, Cost Optimization in the cloud\/fog environment based on Task Deadline (COTD) is proposed that optimizes cost without compromising the response time. In this algorithm the task deadline is considered as a constraint and an appropriate data center for task processing is selected. The proposed algorithm is suitable for runtime decision making due to its low complexity. The proposed algorithm is evluated using a well-known simulation tool Cloud Analyst. Our comprehensive testbed simulations show that COTD outperforms the existing schemes, Service Proximity Based Routing and Performance-Optimized Routing. The proposed algorithm successfully minimizes the cost by 35% on average while maintaining the response time.<\/jats:p>","DOI":"10.1186\/s13677-022-00370-x","type":"journal-article","created":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T12:02:37Z","timestamp":1673956957000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Cost optimization in cloud environment based on task deadline"],"prefix":"10.1186","volume":"12","author":[{"given":"Saima Gulzar","family":"Ahmad","sequence":"first","affiliation":[]},{"given":"Tassawar","family":"Iqbal","sequence":"additional","affiliation":[]},{"given":"Ehsan Ullah","family":"Munir","sequence":"additional","affiliation":[]},{"given":"Naeem","family":"Ramzan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,17]]},"reference":[{"key":"370_CR1","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1016\/j.future.2020.02.036","volume":"108","author":"NMC Donnell","year":"2020","unstructured":"Donnell NMC, Howley E, Duggan J (2020) Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing. Futur Genre Comput Syst 108:288\u2013301. https:\/\/doi.org\/10.1016\/j.future.2020.02.036","journal-title":"Futur Genre Comput Syst"},{"key":"370_CR2","doi-asserted-by":"publisher","first-page":"118924","DOI":"10.1109\/ACCESS.2020.3003799","volume":"8","author":"S Chen","year":"2020","unstructured":"Chen S, Huang S, Luo Q, Zhou J (2020) A profit maximization scheme in cloud computing with deadline constraints. IEEE Access 8:118924\u2013118939. https:\/\/doi.org\/10.1109\/ACCESS.2020.3003799","journal-title":"IEEE Access"},{"key":"370_CR3","doi-asserted-by":"publisher","first-page":"72424","DOI":"10.1109\/ACCESS.2020.2987749","volume":"8","author":"S Chen","year":"2020","unstructured":"Chen S, You Z, Ruan X (2020) Privacy and energy co-aware data aggregation computation offloading for fog-assisted IoT networks. IEEE Access 8:72424\u201372434. https:\/\/doi.org\/10.1109\/ACCESS.2020.2987749","journal-title":"IEEE Access"},{"key":"370_CR4","doi-asserted-by":"publisher","unstructured":"Choudhari T, Moh M, Mo TS (2018) Prioritized task scheduling in fog computing. Proc. ACMSE 2018 Conf 2018. https:\/\/doi.org\/10.1145\/3190645.3190699","DOI":"10.1145\/3190645.3190699"},{"key":"370_CR5","unstructured":"\u201cCloud Computing Architecture.\u201d [Online]. Available: http:\/\/www.eurocloud.org.uk\/wp-content\/uploads\/2018\/03\/Cloud-Computing-1.jpg"},{"key":"370_CR6","doi-asserted-by":"publisher","first-page":"94697","DOI":"10.1109\/ACCESS.2020.2995393","volume":"8","author":"HA Alharbi","year":"2020","unstructured":"Alharbi HA, Elgorashi TEH, Elmirghani JMH (2020) Energy efficient virtual machine placement over cloud-fog network architecture. IEEE Access 8:94697\u201394718. https:\/\/doi.org\/10.1109\/ACCESS.2020.2995393","journal-title":"IEEE Access"},{"key":"370_CR7","doi-asserted-by":"publisher","unstructured":"Yousefpour A, Ishigaki G, Jue JP (2017) Fog Computing: Towards Minimizing Delay in the Internet of Things. Proc. - 2017 IEEE 1st Int. Conf. Edge Comput. EDGE 2017:17\u201324. https:\/\/doi.org\/10.1109\/IEEE.EDGE.2017.12","DOI":"10.1109\/IEEE.EDGE.2017.12"},{"key":"370_CR8","doi-asserted-by":"publisher","unstructured":"Scarlet O, Nardelli M, Schulte S, Dustdar S (2017) Towards QoS-Aware Fog Service Placement. Proc. - 2017 IEEE 1st Int. Conf. Fog Edge Comput. ICFEC 2017:89\u201396. https:\/\/doi.org\/10.1109\/ICFEC.2017.12","DOI":"10.1109\/ICFEC.2017.12"},{"issue":"2","key":"370_CR9","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/MIC.2017.38","volume":"21","author":"N Iotti","year":"2017","unstructured":"Iotti N, Picone M, Crane S, Ferrari G (2017) Improving quality of experience in future wireless access networks through fog computing. IEEE Internet Comput 21(2):26\u201333. https:\/\/doi.org\/10.1109\/MIC.2017.38","journal-title":"IEEE Internet Comput"},{"issue":"1","key":"370_CR10","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1007\/s11227-019-03048-5","volume":"76","author":"MA Khan","year":"2020","unstructured":"Khan MA (2020) Optimized hybrid service brokering for multi-cloud architectures. J Supercomput 76(1):666\u2013687. https:\/\/doi.org\/10.1007\/s11227-019-03048-5","journal-title":"J Supercomput"},{"key":"370_CR11","doi-asserted-by":"publisher","unstructured":"Wickremasinghe B, Calheiros RN, Buyya R (2010) CloudAnalyst: a cloudsim-based visual modeller for analysing cloud computing environments and applications. Proc - Int Conf Adv Inf Netw Apple AINA:446\u2013452. https:\/\/doi.org\/10.1109\/AINA.2010.32","DOI":"10.1109\/AINA.2010.32"},{"key":"370_CR12","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/j.procs.2015.04.173","volume":"48","author":"V Tyagi","year":"2015","unstructured":"Tyagi V, Kumar T (2015) ORT broker policy: reduce cost and response time using throttled load balancing algorithm. Procedia Comput. Sci. 48:217\u2013221. https:\/\/doi.org\/10.1016\/j.procs.2015.04.173","journal-title":"Procedia Comput. Sci."},{"issue":"6","key":"370_CR13","first-page":"684","volume":"7","author":"S Ramasubbareddy","year":"2019","unstructured":"Ramasubbareddy S, Adityasaisrinivas T, Govinda K, Manivannan SS, Swetha E (2019) Analysis of load balancing algorithms using cloud analyst. Int J Recent Technol Eng 7(6):684\u2013687","journal-title":"Int J Recent Technol Eng"},{"key":"370_CR14","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.junkie.2016.08.018","volume":"75","author":"RK Naha","year":"2016","unstructured":"Naha RK, Othman M (2016) Cost-aware service brokering and performance sentient load balancing algorithms in the cloud. J Netw Comput Appl 75:47\u201357. https:\/\/doi.org\/10.1016\/j.junkie.2016.08.018","journal-title":"J Netw Comput Appl"},{"key":"370_CR15","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1007\/s10586-017-1559-z","volume":"22","author":"AM Manasrah","year":"2019","unstructured":"Manasrah AM, Aldomi A, Gupta BB (2019) An optimized service broker routing policy based on differential evolution algorithm in fog\/cloud environment. Cluster Comput. 22:1639\u20131653. https:\/\/doi.org\/10.1007\/s10586-017-1559-z","journal-title":"Cluster Comput."},{"key":"370_CR16","doi-asserted-by":"publisher","unstructured":"Kulkami AK, Annappa B (2017) Cost aware service broker algorithm for load balancing Geo-distributed data centers in the cloud. 2017 IEEE Int. Conf. Signal Process. Informatics, Commun Energy Syst SPICES. https:\/\/doi.org\/10.1109\/SPICES.2017.8091337","DOI":"10.1109\/SPICES.2017.8091337"},{"key":"370_CR17","doi-asserted-by":"publisher","unstructured":"Jain R, Sharma N, Sharma T (2018) Enhancement in performance of the service broker algorithm using fuzzy rules. Proc. 2nd Int. Conf. Invent. Syst. Control. ICISC 2018:922\u2013925. https:\/\/doi.org\/10.1109\/ICISC.2018.8398934","DOI":"10.1109\/ICISC.2018.8398934"},{"key":"370_CR18","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1016\/j.procs.2018.05.086","volume":"132","author":"PM Rekha","year":"2018","unstructured":"Rekha PM, Dakshayini M (2018) Dynamic cost-load aware service broker load balancing in virtualization environment. Procedia Comput. Sci. 132:744\u2013751. https:\/\/doi.org\/10.1016\/j.procs.2018.05.086","journal-title":"Procedia Comput. Sci."},{"key":"370_CR19","volume-title":"Efficient service broker policy for intra data center load balancing","author":"R Patel","year":"2019","unstructured":"Patel R, Patel S (2019) Efficient service broker policy for intra data center load balancing, vol 107. Springer, Singapore"},{"key":"370_CR20","doi-asserted-by":"publisher","unstructured":"Al-Tarawneh M, Al-Mousa A (2019) Adaptive user-oriented fuzzy-based service broker for cloud services. J. King Saud Univ. - Comput. Inf. Sci. https:\/\/doi.org\/10.1016\/j.jksuci.2019.11.004","DOI":"10.1016\/j.jksuci.2019.11.004"},{"issue":"2018","key":"370_CR21","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1016\/j.procs.2019.04.139","volume":"151","author":"Z Benlalia","year":"2019","unstructured":"Benlalia Z, Beanie-Hssane A, Abouelmehdi K, Ezati A (2019) A new service broker algorithm optimizing the cost and response time for cloud computing. Procedia Comput Sci 151(2018):992\u2013997. https:\/\/doi.org\/10.1016\/j.procs.2019.04.139","journal-title":"Procedia Comput Sci"},{"key":"370_CR22","doi-asserted-by":"publisher","unstructured":"Nayak SC, Parida S, Tripathy C, Pattnaik PK (2018) An enhanced deadline constraint based task scheduling mechanism for cloud environments. J. King Saud Univ. - Comput. Inf. Sci. https:\/\/doi.org\/10.1016\/j.jksuci.2018.10.009","DOI":"10.1016\/j.jksuci.2018.10.009"},{"issue":"1","key":"370_CR23","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/s10586-019-02928-y","volume":"23","author":"A Jyoti","year":"2020","unstructured":"Jyoti A, Shrimali M (2020) Dynamic provisioning of resources based on load balancing and service broker policy in cloud computing. Cluster Comput 23(1):377\u2013395. https:\/\/doi.org\/10.1007\/s10586-019-02928-y","journal-title":"Cluster Comput"},{"key":"370_CR24","doi-asserted-by":"publisher","first-page":"118135","DOI":"10.1109\/ACCESS.2020.3003825","volume":"8","author":"M Junaid","year":"2020","unstructured":"Junaid M, Sohail A, Ahmed A, Baz A, Khan IA, Alhakami H (2020) A hybrid model for load balancing in cloud using file type formatting. IEEE Access 8:118135\u2013118155. https:\/\/doi.org\/10.1109\/ACCESS.2020.3003825","journal-title":"IEEE Access"},{"issue":"9","key":"370_CR25","doi-asserted-by":"publisher","first-page":"2049","DOI":"10.1007\/s00607-020-00813-w","volume":"102","author":"A Ghasemi","year":"2020","unstructured":"Ghasemi A, Trophy Haghighat A (2020) A multi-objective load balancing algorithm for virtual machine placement in cloud data centers based on machine learning. Computing 102(9):2049\u20132072. https:\/\/doi.org\/10.1007\/s00607-020-00813-w","journal-title":"Computing"},{"key":"370_CR26","doi-asserted-by":"publisher","first-page":"173208","DOI":"10.1109\/access.2020.3024113","volume":"8","author":"M Junaid","year":"2020","unstructured":"Junaid M et al (2020) Modeling an optimized approach for load balancing in cloud. IEEE Access 8:173208\u2013173226. https:\/\/doi.org\/10.1109\/access.2020.3024113","journal-title":"IEEE Access"},{"key":"370_CR27","doi-asserted-by":"publisher","first-page":"113737","DOI":"10.1109\/ACCESS.2020.3003263","volume":"8","author":"MM Shahriar Maswood","year":"2020","unstructured":"Shahriar Maswood MM, Rahman MR, Alharbi AG, Medhi D (2020) A Novel Strategy to Achieve Bandwidth Cost Reduction and Load Balancing in a Cooperative Three-Layer Fog-Cloud Computing Environment. IEEE Access 8:113737\u2013113750. https:\/\/doi.org\/10.1109\/ACCESS.2020.3003263","journal-title":"IEEE Access"},{"key":"370_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/4406809","volume":"2022","author":"P Gupta","year":"2022","unstructured":"Gupta P, Kaikini RR, Saini DK, Rahman S (2022) Cost-aware resource optimization for efficient cloud application in smart cities. Journal of Sensors 2022:1\u201312. https:\/\/doi.org\/10.1155\/2022\/4406809","journal-title":"Journal of Sensors"},{"key":"370_CR29","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s10586-021-03371-8","volume":"25","author":"A Najafizadeh","year":"2022","unstructured":"Najafizadeh A, Salajegheh A, Rahmani AM, Sahafi A (2022) Multi-objective task scheduling in cloud-fog computing using goal programming approach. J Clus Comput 25:141\u2013165","journal-title":"J Clus Comput"},{"key":"370_CR30","volume-title":"Book: Intelligentand fuzzy techniques: smart and innovative solutions","author":"T Bezdan","year":"2021","unstructured":"Bezdan T, Zivkovic M, Bacanin N, Strumberger I, Tuba E, Tuba M (2021) Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm. In: Book: Intelligentand fuzzy techniques: smart and innovative solutions"},{"issue":"1","key":"370_CR31","doi-asserted-by":"publisher","first-page":"32","DOI":"10.26599\/BDMA.2021.9020016","volume":"5","author":"AK Sandhu","year":"2021","unstructured":"Sandhu AK (2021) Big data with cloud computing: discussions and challenges. Big Data Analytics 5(1):32\u201340","journal-title":"Big Data Analytics"},{"issue":"2","key":"370_CR32","doi-asserted-by":"publisher","first-page":"303","DOI":"10.26599\/TST.2021.9010019","volume":"27","author":"H Liu","year":"2021","unstructured":"Liu H, Aljbri AS, Song J, Jiang J, Hua C (2021) Research advances on AI-powered thermal management for data centers. Tsinghua Sci Technol 27(2):303\u2013314","journal-title":"Tsinghua Sci Technol"},{"issue":"2","key":"370_CR33","doi-asserted-by":"publisher","first-page":"181","DOI":"10.23919\/ICN.2020.0014","volume":"1","author":"S Nath","year":"2020","unstructured":"Nath S, Jingxian W (2020) Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems. Intelligent and Converged Networks 1(2):181\u2013198","journal-title":"Intelligent and Converged Networks"},{"issue":"1","key":"370_CR34","doi-asserted-by":"publisher","first-page":"95","DOI":"10.26599\/TST.2019.9010044","volume":"26","author":"W Zhang","year":"2020","unstructured":"Zhang W, Chen X, Jiang J (2020) A multi-objective optimization method of initial virtual machine fault-tolerant placement for star topological data centers of cloud systems. Tsinghua Sci Technol 26(1):95\u2013111","journal-title":"Tsinghua Sci Technol"},{"issue":"1","key":"370_CR35","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1002\/spe.995","volume":"41","author":"RN Calheiros","year":"2011","unstructured":"Calheiros RN, Ranjan R, Beloglazov A, De Rose CAF, Buyya R (2011) CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw - Pract Exp 41(1):23\u201350","journal-title":"Softw - Pract Exp"},{"key":"370_CR36","unstructured":"\u201cFog-Computing-diagram.\u201d [Online]. Available: https:\/\/www.itprc.com\/wp-content\/uploads\/2018\/09\/Fog-Computing-diagram.jpg"},{"key":"370_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/CloudTech.2018.8713338","volume":"2018","author":"H Ben Alla","year":"2018","unstructured":"Ben Alla H, Ben Alla S, Touhafi A, Ezzati A (2018) Deadline and Energy Aware Task Scheduling in Cloud Computing. 4th Int. Conf Cloud Comput Technol Apple Cloudtech 2018:1\u20138. https:\/\/doi.org\/10.1109\/CloudTech.2018.8713338","journal-title":"4th Int. Conf Cloud Comput Technol Apple Cloudtech"}],"container-title":["Journal of Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-022-00370-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13677-022-00370-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-022-00370-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T12:02:44Z","timestamp":1673956964000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofcloudcomputing.springeropen.com\/articles\/10.1186\/s13677-022-00370-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,17]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["370"],"URL":"https:\/\/doi.org\/10.1186\/s13677-022-00370-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-1587359\/v1","asserted-by":"object"}]},"ISSN":["2192-113X"],"issn-type":[{"value":"2192-113X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,17]]},"assertion":[{"value":"23 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 November 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 January 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not Applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"All authors guarantee that research findings have not been previously published and this work is not submitted any whereelse.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"9"}}