{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T18:35:35Z","timestamp":1790447735802,"version":"4.1.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T00:00:00Z","timestamp":1650412800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T00:00:00Z","timestamp":1650412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100018777","name":"Nile University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100018777","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mobile Netw Appl"],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Mobile edge computing (MEC) is a promising technology that has the potential to meet the latency requirements of next-generation mobile networks. Since MEC servers have limited resources, an orchestrator utilizes a scheduling algorithm to decide where and when each task should execute so that the quality of service (QoS) of each task is achieved. The scheduling algorithm should use the least possible resources required to meet the service demands. In this paper, we develop a two-level cooperative scheduling algorithm with a centralized orchestrator layer. The first scheduling level is used to schedule tasks locally on MEC servers. In contrast, the second level resides at the orchestrator and assigns tasks to a neighboring base station or the cloud. The tasks serve in accordance with their priority, which is determined by the latency and required throughput. We also present a resource optimization algorithm for determining resource distribution in the system in order to ensure satisfactory service availability at the minimum cost. The resource optimization algorithm contains two variations that can be employed depending on the traffic model. One variant is used when the traffic is uniformly distributed, and the other is used when the traffic load is unbalanced among base stations. Numerical results show that the cooperative model of task scheduling outperforms the non-cooperative model. Furthermore, the results show that the suggested scheduling algorithm performs better than other well-known scheduling algorithms, such as shortest job first scheduling and earliest deadline first scheduling.<\/jats:p>","DOI":"10.1007\/s11036-022-01974-y","type":"journal-article","created":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T19:02:59Z","timestamp":1650481379000},"page":"1444-1460","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["An Optimized Collaborative Scheduling Algorithm for Prioritized Tasks with Shared Resources in Mobile-Edge and Cloud Computing Systems"],"prefix":"10.1007","volume":"27","author":[{"given":"Amira A.","family":"Amer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ihab E.","family":"Talkhan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reem","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0109-5545","authenticated-orcid":false,"given":"Tawfik","family":"Ismail","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,4,20]]},"reference":[{"key":"1974_CR1","doi-asserted-by":"publisher","unstructured":"Gao H, Qin X, Barroso RJD, Hussain W, Xu Y, Yin Y (2020) Collaborative learning-based industrial iot api recommendation for software-defined devices: The implicit knowledge discovery perspective. IEEE Transactions on Emerging Topics in Computational Intelligence, 1\u201311. https:\/\/doi.org\/10.1109\/TETCI.2020.3023155","DOI":"10.1109\/TETCI.2020.3023155"},{"key":"1974_CR2","doi-asserted-by":"publisher","unstructured":"Li R, Zhou Z, Chen X, Ling Q (2019) Resource price-aware offloading for edge-cloud collaboration: A two-timescale online control approach. IEEE Transactions on Cloud Computing, 1\u20131. https:\/\/doi.org\/10.1109\/TCC.2019.2937928","DOI":"10.1109\/TCC.2019.2937928"},{"key":"1974_CR3","doi-asserted-by":"crossref","unstructured":"Gao H, Zhang Y, Miao H, Barroso RJD, Yang X (2021) Sdtioa: Modeling the timed privacy requirements of iot service composition: A user interaction perspective for automatic transformation from bpel to timed automata. Mobile Networks and Applications, 1\u201326","DOI":"10.1007\/s11036-021-01846-x"},{"key":"1974_CR4","doi-asserted-by":"crossref","unstructured":"Lakhan A, Ahmad M, Bilal M, Jolfaei A, Mehmood RM (2021) Mobility aware blockchain enabled offloading and scheduling in vehicular fog cloud computing. IEEE Transactions on Intelligent Transportation Systems","DOI":"10.1109\/TITS.2021.3056461"},{"issue":"3","key":"1974_CR5","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.1109\/COMST.2017.2682318","volume":"19","author":"P Mach","year":"2017","unstructured":"Mach P, Becvar Z (2017) Mobile edge computing: A survey on architecture and computation offloading. IEEE Commun Surv Tutorials 19(3):1628\u20131656","journal-title":"IEEE Commun Surv Tutorials"},{"issue":"2","key":"1974_CR6","doi-asserted-by":"publisher","first-page":"1040","DOI":"10.1109\/TNSM.2020.2977843","volume":"17","author":"H Sun","year":"2020","unstructured":"Sun H, Yu H, Fan G (2020) Contract-based resource sharing for time effective task scheduling in fog-cloud environment. IEEE Trans Netw Serv Manag 17(2):1040\u20131053. https:\/\/doi.org\/10.1109\/TNSM.2020.2977843","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"1974_CR7","unstructured":"FG-NET2030 (2020) Network 2030 architecture framework. Technical specification, ITU-T"},{"key":"1974_CR8","doi-asserted-by":"publisher","unstructured":"Lin T, Qiu J, Fu L (2021) Online learning and resource allocation for user experience improvement in mobile edge clouds. In: ICC 2021 - IEEE international conference on communications. https:\/\/doi.org\/10.1109\/ICC42927.2021.9500905, pp 1\u20136","DOI":"10.1109\/ICC42927.2021.9500905"},{"key":"1974_CR9","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.jpdc.2018.03.004","volume":"132","author":"R Mahmud","year":"2019","unstructured":"Mahmud R, Srirama SN, Ramamohanarao K, Buyya R (2019) Quality of experience (qoe)-aware placement of applications in fog computing environments. J Parallel Distrib Comput 132:190\u2013203","journal-title":"J Parallel Distrib Comput"},{"key":"1974_CR10","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.jss.2019.04.050","volume":"154","author":"S Tuli","year":"2019","unstructured":"Tuli S, Mahmud R, Tuli S, Buyya R (2019) Fogbus: A blockchain-based lightweight framework for edge and fog computing. J Syst Softw 154:22\u201336","journal-title":"J Syst Softw"},{"issue":"2","key":"1974_CR11","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s11761-019-00260-2","volume":"13","author":"O Fadahunsi","year":"2019","unstructured":"Fadahunsi O, Maheswaran M (2019) Locality sensitive request distribution for fog and cloud servers. Serv Oriented Comput Appl 13(2):127\u2013140","journal-title":"Serv Oriented Comput Appl"},{"issue":"10","key":"1974_CR12","doi-asserted-by":"publisher","first-page":"2333","DOI":"10.1109\/JSAC.2018.2869954","volume":"36","author":"T Ouyang","year":"2018","unstructured":"Ouyang T, Zhou Z, Chen X (2018) Follow me at the edge: Mobility-aware dynamic service placement for mobile edge computing. IEEE J Sel Areas Commun 36(10):2333\u20132345","journal-title":"IEEE J Sel Areas Commun"},{"issue":"4","key":"1974_CR13","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1007\/s11761-017-0219-8","volume":"11","author":"O Skarlat","year":"2017","unstructured":"Skarlat O, Nardelli M, Schulte S, Borkowski M, Leitner P (2017) Optimized IoT service placement in the fog. Serv Oriented Comput Appl 11(4):427\u2013443","journal-title":"Serv Oriented Comput Appl"},{"key":"1974_CR14","doi-asserted-by":"crossref","unstructured":"Wang J, Zhao L, Liu J, Kato N (2019) Smart resource allocation for mobile edge computing: A deep reinforcement learning approach. IEEE Transactions on Emerging Topics in Computing","DOI":"10.1109\/GCWkshps45667.2019.9024603"},{"issue":"2","key":"1974_CR15","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1109\/TVT.2019.2962542","volume":"69","author":"X Chen","year":"2020","unstructured":"Chen X, Cai Y, Li L, Zhao M, Champagne B, Hanzo L (2020) Energy-efficient resource allocation for latency-sensitive mobile edge computing. IEEE Trans Veh Technol 69(2):2246\u20132262. https:\/\/doi.org\/10.1109\/TVT.2019.2962542","journal-title":"IEEE Trans Veh Technol"},{"issue":"4","key":"1974_CR16","doi-asserted-by":"publisher","first-page":"2633","DOI":"10.1109\/JIOT.2017.2786343","volume":"5","author":"J Zhang","year":"2018","unstructured":"Zhang J, Hu X, Ning Z, Ngai EC, Zhou L, Wei J, Cheng J, Hu B (2018) Energy-latency tradeoff for energy-aware offloading in mobile edge computing networks. IEEE Internet Things J 5 (4):2633\u20132645. https:\/\/doi.org\/10.1109\/JIOT.2017.2786343","journal-title":"IEEE Internet Things J"},{"issue":"4","key":"1974_CR17","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1109\/TPDS.2016.2604814","volume":"28","author":"S Wang","year":"2016","unstructured":"Wang S, Urgaonkar R, He T, Chan K, Zafer M, Leung KK (2016) Dynamic service placement for mobile micro-clouds with predicted future costs. IEEE Trans Parallel Distrib Syst 28(4):1002\u20131016","journal-title":"IEEE Trans Parallel Distrib Syst"},{"issue":"3","key":"1974_CR18","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1109\/TPDS.2021.3099731","volume":"33","author":"T Bahreini","year":"2022","unstructured":"Bahreini T, Badri H, Grosu D (2022) Mechanisms for resource allocation and pricing in mobile edge computing systems. IEEE Trans Parallel Distrib Syst 33(3):667\u2013682. https:\/\/doi.org\/10.1109\/TPDS.2021.3099731","journal-title":"IEEE Trans Parallel Distrib Syst"},{"issue":"2","key":"1974_CR19","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1109\/TGCN.2021.3067374","volume":"5","author":"Y Huang","year":"2021","unstructured":"Huang Y, Xu H, Gao H, Ma X, Hussain W (2021) Ssur: An approach to optimizing virtual machine allocation strategy based on user requirements for cloud data center. IEEE Trans Green Commun Netw 5(2):670\u2013681. https:\/\/doi.org\/10.1109\/TGCN.2021.3067374","journal-title":"IEEE Trans Green Commun Netw"},{"issue":"11","key":"1974_CR20","doi-asserted-by":"publisher","first-page":"5141","DOI":"10.1109\/TWC.2019.2933417","volume":"18","author":"N Zhao","year":"2019","unstructured":"Zhao N, Liang Y, Niyato D, Pei Y, Wu M, Jiang Y (2019) Deep reinforcement learning for user association and resource allocation in heterogeneous cellular networks. IEEE Trans Wirel Commun 18 (11):5141\u20135152. https:\/\/doi.org\/10.1109\/TWC.2019.2933417","journal-title":"IEEE Trans Wirel Commun"},{"key":"1974_CR21","doi-asserted-by":"crossref","unstructured":"Lin L, Li P, Xiong J, Lin M (2018) Distributed and application-aware task scheduling in edge-clouds. In: 2018 14th international conference on mobile ad-hoc and sensor networks (MSN). IEEE, pp 165\u2013170","DOI":"10.1109\/MSN.2018.000-1"},{"issue":"3","key":"1974_CR22","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1007\/s10723-019-09481-3","volume":"17","author":"L Chunlin","year":"2019","unstructured":"Chunlin L, Jianhang T, Youlong L (2019) Hybrid cloud adaptive scheduling strategy for heterogeneous workloads. J Grid Comput 17(3):419\u2013446","journal-title":"J Grid Comput"},{"key":"1974_CR23","doi-asserted-by":"publisher","unstructured":"Xiang Z, Deng S, Jiang F, Gao H, Tehari J, Yin J (2020) Computing power allocation and traffic scheduling for edge service provisioning. In: 2020 IEEE international conference on Web services (ICWS). https:\/\/doi.org\/10.1109\/ICWS49710.2020.00058, pp 394\u2013403","DOI":"10.1109\/ICWS49710.2020.00058"},{"key":"1974_CR24","doi-asserted-by":"publisher","unstructured":"Ma X, Zhou A, Zhang S, Li Q, Liu AX, Wang S (2021) Dynamic task scheduling in cloud-assisted mobile edge computing. IEEE Transactions on Mobile Computing, 1\u20131. https:\/\/doi.org\/10.1109\/TMC.2021.3115262","DOI":"10.1109\/TMC.2021.3115262"},{"issue":"7","key":"1974_CR25","doi-asserted-by":"publisher","first-page":"5773","DOI":"10.1109\/JIOT.2019.2946426","volume":"7","author":"M Adhikari","year":"2019","unstructured":"Adhikari M, Mukherjee M, Srirama SN (2019) Dpto: A deadline and priority-aware task offloading in fog computing framework leveraging multilevel feedback queueing. IEEE Internet Things J 7(7):5773\u20135782","journal-title":"IEEE Internet Things J"},{"issue":"11","key":"1974_CR26","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/MCOM.2017.1700363","volume":"55","author":"W Bao","year":"2017","unstructured":"Bao W, Yuan D, Yang Z, Wang S, Li W, Zhou BB, Zomaya AY (2017) Follow me fog: Toward seamless handover timing schemes in a fog computing environment. IEEE Commun Mag 55(11):72\u201378. https:\/\/doi.org\/10.1109\/MCOM.2017.1700363","journal-title":"IEEE Commun Mag"},{"issue":"4","key":"1974_CR27","doi-asserted-by":"publisher","first-page":"6862","DOI":"10.1109\/JIOT.2019.2912155","volume":"6","author":"A Zhu","year":"2019","unstructured":"Zhu A, Guo S, Liu B, Ma M, Yao J, Su X (2019) Adaptive multiservice heterogeneous network selection scheme in mobile edge computing. IEEE Internet Things J 6 (4):6862\u20136875. https:\/\/doi.org\/10.1109\/JIOT.2019.2912155","journal-title":"IEEE Internet Things J"},{"issue":"4","key":"1974_CR28","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.1109\/TCCN.2020.3027681","volume":"6","author":"Y Yin","year":"2020","unstructured":"Yin Y, Cao Z, Xu Y, Gao H, Li R, Mai Z (2020) Qos prediction for service recommendation with features learning in mobile edge computing environment. IEEE Trans Cogn Commun Netw 6 (4):1136\u20131145. https:\/\/doi.org\/10.1109\/TCCN.2020.3027681","journal-title":"IEEE Trans Cogn Commun Netw"},{"key":"1974_CR29","doi-asserted-by":"publisher","unstructured":"Ma X, Xu H, Gao H, Bian M (2021) Real-time multiple work-flow scheduling in cloud environments. IEEE Transactions on Network and Service Management, 1\u20131. https:\/\/doi.org\/10.1109\/TNSM.2021.3125395","DOI":"10.1109\/TNSM.2021.3125395"},{"key":"1974_CR30","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1109\/ACCESS.2019.2959119","volume":"8","author":"X Wang","year":"2020","unstructured":"Wang X, Ji Y, Zhang J, Bai L, Zhang M (2020) Joint optimization of latency and deployment cost over tdm-pon based mec-enabled cloud radio access networks. IEEE Access 8:681\u2013696. https:\/\/doi.org\/10.1109\/ACCESS.2019.2959119","journal-title":"IEEE Access"},{"key":"1974_CR31","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Perth A (ed) Proc. IEEE international conference on neural networks, pp 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"1974_CR32","doi-asserted-by":"publisher","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN\u201995 - International conference on neural networks. https:\/\/doi.org\/10.1109\/ICNN.1995.488968, vol 4, pp 1942\u201319484","DOI":"10.1109\/ICNN.1995.488968"},{"key":"1974_CR33","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1007\/978-3-319-93073-2_6","volume-title":"Particle swarm optimization","author":"B Chopard","year":"2018","unstructured":"Chopard B, Tomassini M (2018) Particle swarm optimization. Springer, Cham, pp 97\u2013102. https:\/\/doi.org\/10.1007\/978-3-319-93073-2_6"},{"issue":"2","key":"1974_CR34","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1007\/s00500-016-2474-6","volume":"22","author":"D Wang","year":"2018","unstructured":"Wang D, Tan D, Liu L (2018) Particle swarm optimization algorithm: An overview. Soft Comput 22(2):387\u2013408","journal-title":"Soft Comput"},{"key":"1974_CR35","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.protcy.2012.05.048","volume":"4","author":"A Sahu","year":"2012","unstructured":"Sahu A, Panigrahi SK, Pattnaik S (2012) Fast convergence particle swarm optimization for functions optimization. Procedia Technol 4:319\u2013324","journal-title":"Procedia Technol"},{"key":"1974_CR36","doi-asserted-by":"publisher","unstructured":"Zhang W-J, Xie X-F, Bi D-C (2004) Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space. In: Proceedings of the 2004 congress on evolutionary computation (IEEE Cat. No.04TH8753). https:\/\/doi.org\/10.1109\/CEC.2004.1331185, vol 2, pp 2307\u201323112","DOI":"10.1109\/CEC.2004.1331185"},{"key":"1974_CR37","unstructured":"(2020) 3GPP: System architecture for the 5G System (5GS). Technical Specification (TS) 23.501, 3rd Generation Partnership Project (3GPP). Version 16.6.0. https:\/\/www.etsi.org\/deliver\/etsi_ts\/123500_123599\/123501\/16.06.0060\/ts_123501v160600p.pdf"},{"key":"1974_CR38","unstructured":"(2021) 3GPp: Service requirements for the 5G system. Technical Specification (TS) 22.261, 3rd Generation Partnership Project (3GPP). Version 18.1.1"},{"key":"1974_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/ett.4233","volume":"e4233","author":"HHM Mahmoud","year":"2021","unstructured":"Mahmoud HHM, Amer A, Ismail T (2021) 6g: A comprehensive survey on technologies, applications, challenges, and research problems. Trans Emerging Telecommun Technol e4233:1\u201314. https:\/\/doi.org\/10.1002\/ett.4233","journal-title":"Trans Emerging Telecommun Technol"},{"key":"1974_CR40","unstructured":"(2015) Common Public Radio Interface: Interface Specification v7.0. http:\/\/www.cpri.info\/downloads\/CPRI_v_7_02015-10-09.pdf"},{"issue":"1","key":"1974_CR41","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1145\/321738.321743","volume":"20","author":"CL Liu","year":"1973","unstructured":"Liu CL, Layland JW (1973) Scheduling algorithms for multiprogramming in a hard-real-time environment. J ACM (JACM) 20(1):46\u201361","journal-title":"J ACM (JACM)"},{"key":"1974_CR42","doi-asserted-by":"publisher","unstructured":"Shah SNM, Mahmood AKB, Oxley A (2009) Hybrid scheduling and dual queue scheduling. In: 2009 2nd IEEE international conference on computer science and information technology. https:\/\/doi.org\/10.1109\/ICCSIT.2009.5234480, pp 539\u2013543","DOI":"10.1109\/ICCSIT.2009.5234480"}],"container-title":["Mobile Networks and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-022-01974-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11036-022-01974-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-022-01974-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T19:37:36Z","timestamp":1664307456000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11036-022-01974-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,20]]},"references-count":42,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["1974"],"URL":"https:\/\/doi.org\/10.1007\/s11036-022-01974-y","relation":{},"ISSN":["1383-469X","1572-8153"],"issn-type":[{"value":"1383-469X","type":"print"},{"value":"1572-8153","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,20]]},"assertion":[{"value":"13 December 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"We are enclosing herewith a manuscript entitled \u201cAn Optimized Collaborative Scheduling Algorithm for Prioritized Tasks with Shared Resources in Mobile-Edge and Cloud Computing Systems\u201d for publication in Mobile Networks and Applications Journal.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"With the submission of this manuscript I would like to undertake that:","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 All authors of this research paper have directly participated in the planning, execution, or analysis of this study;","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 All authors of this paper have read and approved the final version submitted;","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 The contents of this manuscript have not been copyrighted or published previously;","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 The contents of this manuscript are not now under consideration for publication elsewhere;","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 The contents of this manuscript will not be copyrighted, submitted, or published elsewhere, while acceptance by the Journal is under consideration;","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"\u2219 There are no directly related manuscripts or abstracts, published or unpublished, by any authors of this paper.","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Manuscript title: An Optimized Collaborative Scheduling Algorithm for Prioritized Tasks with Shared Resources in Mobile-Edge and Cloud Computing Systems. The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honor-aria; educational grants; participation in speakers\u2019 bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.","order":9,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}