Computer Science ›› 2021, Vol. 48 ›› Issue (1): 26-33.doi: 10.11896/jsjkx.200900211

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

Survey on Service Resource Availability Forecast Based on Queuing Theory

ZHNAG Kai-qi, TU Zhi-ying, CHU Dian-hui, LI Chun-shan   

  1. School of Computer Science and Technology,Harbin Institute of Technology,Weihai,Weihai,Shandong 264209,China
  • Received:2020-09-29 Revised:2020-11-07 Online:2021-01-15 Published:2021-01-15
  • About author:ZHANG Kai-qi,born in 1995,Ph.D student.Her main research interests include service recommendation and so on.
    TU Zhi-ying,born in 1983,Ph.D,associate professor,is a member of China Computer Federation.His main research interests include service computing and knowledge engineering.
  • Supported by:
    National Key Research and Development Projects (2018YFB1702900),National Natural Science Foundation of China(61772159,61802089,61832004) and Shandong Province Nature Science Foundation(ZR2017MF02661802089).

Abstract: Queuing theory solves various complex queuing problems in many fields.This paper first introduces the general model representation and common models of queuing theory.Secondly,it briefly summarizes the various problems solved by queuing theory,and focuses on the literatures on service availability prediction of queuing theory in recent years,including its application in different fields,such as daily life,cloud computing,and network resources.To find the relationship between service and user needs,it classifies and summarizes the purpose of predicting service availability,including predicting resources,reasonably planning and allocating resources,meeting user needs,reducing user waiting time,and improving system reliability,etc.Through the summary of such documents,it finds the existing problems,and puts forward improvement methods and suggestions.Finally,the application of service resource availability predictions based on queuing theory in recommendation is forecasted,and the future research directions and challenges are briefly explained.

Key words: Cloud computing, Network resources, Queuing theory, Resource availability, Service resources

CLC Number: 

  • TP311.5
[1] XU X,SHENG Q Z,ZHANG L J,et al.From Big Data to Big Service[J].Computer,2015,48(7):80-83.
[2] DORDA M,TEICHMANN D,GRAF V.Optimisation of service capacity based on queueing theory[J].MM Science Journal,2019(3):2975-2981.
[3] GORUNESCU F,MCCLEAN S I,MILLARD P H.A queueing model for bed-occupancy management and planning of hospitals[J].Journal of the Operational Research Society,2002,53(1):19-24.
[4] LI X,BEULLENS P,JONES D,et al.Optimal bed allocation in hospitals[M].Berlin:Springer Berlin Heidelberg,2009.
[5] TIRDAD A,GRASSMANN W K,TAVAKOLI J.Optimal policies of M(t)/M/c/c queues with two different levels of servers[J].European Journal of Operational Research,2016,249(3):1124-1130.
[6] CHAN J,ZHANG L.Case mix index weighted multi-objective optimization of inpatient bed allocation in general hospital[J].Journal of Combinatorial Optimization,2019,37(1):1-19.
[7] KRPAN L,ROBERT M,MILKOVIĆM.A model of the dimensioning of the number of service places at parking lot entrances by using the queuing theory[J].Tehnicki vjesnik-Technical Gazette,2017,24(1):231-238.
[8] KATSINIS C,CONSTANT A.Effect of queue selection andservice time distributions in multiple resource allocation[J].Computer Systems Science & Engineering,1994,9(3):184-194.
[9] JONATHA A,PAOLO C,EDOARDO A.On the consolidation of data-centers with performance constraints[M].Berlin:Springer Berlin Heidelberg,2009.
[10] ZHOU X,CAI Y,CHOW E.An integrated approach with feedback control for robust web QoS design[J].Computer Communications,2006,29(16):3158-3169.
[11] ELSHERIF A A,MOHAMED A.Joint routing and resource allocation for delay minimization in cognitive radio based mesh networks[J].IEEE Transactions on Wireless Communications,2014,13(1):186-197.
[12] KHOMONENKO A D,GINDIN S I,MODHER K M.A cloud computing model using multi-channel queuing system with coo-ling[C]//XIX IEEE International Conference on Soft Compu-ting & Measurements.IEEE,2016:103-106.
[13] YAN Z X,LIU W,XU D.Study of cloud service queuing model based on imbedding markov chain perspective[J].Cluster Computing,2018,21(1):837-844.
[14] SALAH K,SHELTAMI T R.Performance modeling of cloudapps using message queueing as a service (MaaS)[C]//Confe-rence on Innovations in Clouds.IEEE,2017:65-71.
[15] LI L,XUE,LIN Y L.A two-stage stochastic model for cloud computing simulation of resource efficiency cost analysis[C]//IEEE International Conference on Computer and Communications (ICCC).IEEE,2017:2267-2274.
[16] HICHA B A,SAID B A,ABDALLAH E.A novel architecture with dynamic queues based on fuzzy logic and particle swarm optimization algorithm for task scheduling in cloud computing[M]//Advances in Ubiquitous Networking 2.Springer Singapore,2017.
[17] BARABASI,ALBERTl L.The origin of bursts and heavy tails in human dynamics[J].Nature,2005,435(7039):207.
[18] BOYDON C.Assessment of an alternative payment scheme for manual gasoline stations using queuing theory[C]//IEEE International Conference on Industrial Engineering and Applications (ICIEA).IEEE,2019:299-305.
[19] BJATTACHARJEE P,RAY P K.Simulation modelling andanalysis of appointment system performance for multiple classes of patients in a hospital:A case study[J].Operations Research for Health Care,2015,8:71-84.
[20] VARNE J,BEAN N,MACKAY M.The self-regulating nature of occupancy in ICUs:stochastic homoeostasis[J].Health Care Management Science,2019,22(4):615-634.
[21] LU R,LIN X,ZHU H,et al.SPARK:A new VANET-based smart parking scheme for large parking lots[C]//IEEE Infocom.IEEE,2009:1413-1421.
[22] LAM W H K,LI Z C,HUANG H J,et al.Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities[J].Transportation Research Part B,2006,40(5):368-395.
[23] BROWN L,GANS N,MANDELBAUM A,et al.Statisticalanalysis of a telephone call center:A queueing-science perspective[J].Publications of the American Statistical Association,2005,100(469):36-50.
[24] MOVAGHAR A.On queueing with customer impatience untilthe beginning of service[J].Queueing System,1998,29(2):337-350.
[25] BARRER D Y.Queuing with impatient customers and ordered service[J].Operations Research,1957,5(5):650-656.
[26] DEFRAEYE M,VAN N I.Staffing and scheduling under nonstationary demand for service:A literature review[J].Omega,2016,58:4-25.
[27] SINGHAL K,SINGHAL J,KUMAR S.The value of the customer's waiting time for general queues[J].Decision Sciences,2018,50(3):567-581.
[28] DIVYA P,SEEMA H.Navigation based-intelligent parking manegement system using queuing theory and IOT[C]//2018 Second International Conference on Green Computing and Internet of Things.IEEE,2018:159-165.
[29] BO L,YI J P,HAO W,et al.MADM-based smart parking guidance algorithm[J].Plos One,2017,12(12):1-30.
[30] FUENTES A,HEASLIP K,DANTONIO A,et al.Evaluation of vehicle parking queueing in a national park:case study of the laurance S[J].Rockefeller Preserve in Grand Teton National Park.Transportation Research Record,2017,2654(1):1-10.
[31] PEL A J,CJANIOTAKIS E.Stochastic user equilibrium traffic assignment with equilibrated parking search routes[J].Transportation Research,2017,101(Jul.):123-139.
[32] HO C Y,YEONG G S,JEONG D Y.LoRa network based parking dispatching system:queuing theory and Q-learning approach journal of digital contents society[J].Journal of Digital Contents Society,2017,18(7):1443-1450.
[33] CHANG Y L,CHEN Z C,SUN C,et al.Urban parking flow assignment model based on G/G/c/FCFS queuing theory[J].Journal of Transportation Systems Engineering & Information Technology,2019,19(5):205-211.
[34] JOSEPH W.Queuing theory and modeling emergency depart-ment resource utilization[J].Emergency Medicine Clinics of North America,2020,38(3):563-572.
[35] WU K,ZHU X,ZHANG R,et al.Hospital Bed Planning in a Single Department Based on Monte Carlo Simulation and Queuing Theory[C]//IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).IEEE,2020:644-648.
[36] CAYIRLI T,VERAL E.Outpatient scheduling in health care:A review of literature[J].Production & Operations Management,2009,12(4):519-549.
[37] GUPTA D,DENTA B.Appointment scheduling in health care:challenges and opportunities[J].IIE Transactions,2008,40(9):800-819.
[38] LI J,DONG M,ZHAO W.Admissions optimisation and premature discharge decisions in intensive care units[J].International Journal of Production Research,2015,53(23/24):7329-7342.
[39] GOLDWASSER R S,LOBO M S,ARRUDA E F,et al.Difficulties in access and estimates of public beds in intensive care units in the state of Rio de Janeiro[J].Revista De Saude Publica,2016,50(19):1-9.
[40] YADUVABSHI D,SHARMA A,MORE P V.Application ofqueuing theory to optimize waiting-time in hospital operations[J].Operations and Supply Chain Management An International Journal,2019,12(3):165-174.
[41] DIJK N M V,KORTBEEK N.Erlang loss bounds for OT-ICU systems[J].queueing systems,2009,63(1-4):253-280.
[42] GREE N,LINDA V.How many hospital beds?[J].Inquiry,2002,39(4):400-412.
[43] ACOSTA O,RUIZ P,RUEDA J,et al.Solving the negative impact of congestion in the postanesthesia care unit:a cost of opportunity analysis[J].Journal of Surgical Research,2017,210:86-91.
[44] MALLOR F,FERMIN J,AZCARATE C,et al.Control problems and management policies in health systems:application to intensive care units[J].Flexible Services & Manufacturing Journal,2016,28(1/2):62-89.
[45] ANDERSEN A R,NIELSEN B F,REINHARDDT L B.Optimization of hospital ward resources with patient relocation using markov chain modeling[J].European Journal of Operational Research,2017,260(3):1152-1163.
[46] LI X Y,LIU Y,KANG R,et al.Service reliability modeling and evaluation of active-active cloud data center based on the IT infrastructure[J].Microelectronics Reliability,2017,75:271-282.
[47] BALLA H,CHEN G S,JING W P.Cloud Biometric Authentication:An Integrated Reliability and Security Method Using the Reinforcement Learning Algorithm and Queue Theory[J].Journal of Universal Computer Science,2018,24(4):372-391.
[48] YANG Z X,LIU W,XU D.Study of cloud service queuing mo-del based on imbedding Markov chain perspective[J].Cluster Computing,2018,21(1):837-844.
[49] BALLA,HUSAMELDDIN A,CHEN G S,et al.Reliability Enhancement in Cloud Computing via Optimized Job Scheduling Implementing Reinforcement Learning Algorithm and Queuing Theory[C]//2018 1st International Conference on Data Intelligence and Security (ICDIS).2018:127-130.
[50] AKBARI E,CUNG F,PATEL H,et al.Incorporation of weighted linear prediction technique and M/M/1 queuing theory for improving energy efficiency of cloud computing datacenters[C]//2016 IEEE Long Island Systems,Applications and Technology Conference.IEEE,2016:1-5.
[51] QU C,CALHEIROS R N,BUYYA R.Auto-scaling web applications in clouds:A taxonomy and survey[J].ACM Computing Surveys,2016,51(4):1-33.
[52] SONG B,HASSANA M,ALAMRI A.A two-stage approach for task and resource management in multimedia cloud environment[J].Computing,2016,98(1/2):119-145.
[53] KAI Q X,PERROS H.SLA-based resource allocation in cluster computing systems[C]//2008 IEEE International Symposium on Parallel and Distributed Processing.IEEE,2008:1-12.
[54] GAWALI M B,SHINDE S K.Implementation of IDEA,BATS,ARIMA and queuing model for task scheduling in cloud computing[C]//Fifth International Conference on Eco-friendly Computing & Communication Systems.IEEE,2016:7-12.
[55] FENG G,GARG S,BUYYA R,et al.Revenue maximizationusing adaptive resource provisioning in cloud computing environments[C]//IEEE International Conference on Grid Computing.ACM,2012:192-200.
[56] TING Q H,LI J C,ZI Y D.Queuing-Oriented job optimizingscheduling in cloud mapreduce[C]// International Conference on P2P,Parallel,Grid,Cloud and Internet Computing.Springer International Publishing,2017:435-446.
[57] SHI J,DONG F,ZHANG J,et al.Resource provisioning optimization for service hosting on cloud platform[C]//IEEE 20th International Conference on Computer Supported Cooperative Work in Design.IEEE,2016:340-345.
[58] VAKILINIA,SHAHIN,CHERIET,et al.Preemptive cloud resource allocation modeling of processing jobs[J].Journal of Supercomputing,2018,74(5):2116-2150.
[59] KONORSKI J.Coordination of distributed user-defined resource sharing supportedby an intelligent communication network[C]//Private Switching Systems and Networks.IET,1992:138-143.
[60] SOOMANAT K,VATANAWOOD W.Formalism of stochastic queueing network using stochastic petri nets[C]//2018 19th IEEE/ACIS International Conference on Software Engineering,Artificial Intelligence,Networking and Parallel/Distributed Computing (SNPD).IEEE,2018:347-351.
[61] GONG L,SUN X H,WATSON E F.Performance modeling and prediction of nondedicated network computing[J].IEEE Transactions on Computers,2002,51(9):1041-1055.
[62] SUGANYA R,JAYASHREE L S.Fuzzy rough set inspired rate adaptation and resource allocation using hidden markov model (FRSIRA-HMM) in mobile ad hoc networks[J].Cluster Computing,2019,22(S4):9875-9888.
[63] VANDY B,JOEL G,EMMANUEL J.On the Distribution of Sequential Jobs in Random Brokering for Heterogeneous Computational Grids[J].IEEE Press,2006,17(2):113-124.
[64] SIMHON E,STAROBINSKI D.On the impact of information disclosure on advance reservations:A game-theoretic view[J].European Journal of Operational Research,2018,267(3):1075-1088.
[65] NING N G,HONG J.A resource reservation algorithm with muti-parameters[C]//2011 Sixth Annual Chinagrid Confe-rence.2011:211-214.
[66] NGUYEN D N,ERYK D,MARWAN K.Harvesting short-lived white spaces via opportunistic traffic offloading between mobile service providers[J].IEEE Transactions on Cognitive Communications & Networking,2018,4(3):635-647.
[67] MANN C R,BALDWIN R O,KHAROUFED J P,et al.Aqueueing approach to optimal resource replication in wireless sensor networks[J].Performance Evaluation,2008,65(10):689-700.
[68] MA Y,HAN J J,TRIVEDI K S.Composite performance and availability analysis of communications networks:A comparison of exact and approximate approaches[C]//IEEE Global Telecommunications Conference.IEEE,2000:1771-1777.
[69] FALKNER M,DEVETSIKIOTIS M,FALKNER M.Minimum cost traffic shaping:a user's perspective on connection admission control[J].IEEE Communications Letters,1999,3(9):257-259.
[70] ZHOU J H,ZHI G H,ZHEN H L.Resource availability evaluation in service grid environment[C]//IEEE Asia-pacific Service Computing Conference.IEEE,2007:232-238.
[71] KAMALI S H,HEDAYATI M,IZADI A S,et al.The monitoring of the network traffic based on queuing theory and simulation in heterogeneous network environment[M]//2009 International Conference on Computer Technology and Development.Kota Kinabalu,Malaysia,2009:322-326.
[72] WANG J P,LI X M,JIAO C L.The network traffic management based on queuing theory[J].Applied Mechanics & Mate-rials,2011,121-126:4721-4747.
[1] GAO Shi-yao, CHEN Yan-li, XU Yu-lan. Expressive Attribute-based Searchable Encryption Scheme in Cloud Computing [J]. Computer Science, 2022, 49(3): 313-321.
[2] WANG Zheng, JIANG Chun-mao. Cloud Task Scheduling Algorithm Based on Three-way Decisions [J]. Computer Science, 2021, 48(6A): 420-426.
[3] PAN Rui-jie, WANG Gao-cai, HUANG Heng-yi. Attribute Access Control Based on Dynamic User Trust in Cloud Computing [J]. Computer Science, 2021, 48(5): 313-319.
[4] CHEN Yu-ping, LIU Bo, LIN Wei-wei, CHENG Hui-wen. Survey of Cloud-edge Collaboration [J]. Computer Science, 2021, 48(3): 259-268.
[5] WANG Wen-juan, DU Xue-hui, REN Zhi-yu, SHAN Di-bin. Reconstruction of Cloud Platform Attack Scenario Based on Causal Knowledge and Temporal- Spatial Correlation [J]. Computer Science, 2021, 48(2): 317-323.
[6] JIANG Hui-min, JIANG Zhe-yuan. Reference Model and Development Methodology for Enterprise Cloud Service Architecture [J]. Computer Science, 2021, 48(2): 13-22.
[7] MAO Han-yu, NIE Tie-zheng, SHEN De-rong, YU Ge, XU Shi-cheng, HE Guang-yu. Survey on Key Techniques and Development of Blockchain as a Service Platform [J]. Computer Science, 2021, 48(11): 4-11.
[8] WANG Qin, WEI Li-fei, LIU Ji-hai, ZHANG Lei. Private Set Intersection Protocols Among Multi-party with Cloud Server Aided [J]. Computer Science, 2021, 48(10): 301-307.
[9] LEI Yang, JIANG Ying. Anomaly Judgment of Directly Associated Nodes Under Cloud Computing Environment [J]. Computer Science, 2021, 48(1): 295-300.
[10] XU Yun-qi, HUANG He, JIN Zhong. Application Research on Container Technology in Scientific Computing [J]. Computer Science, 2021, 48(1): 319-325.
[11] LI Yan, SHEN De-rong, NIE Tie-zheng, KOU Yue. Multi-keyword Semantic Search Scheme for Encrypted Cloud Data [J]. Computer Science, 2020, 47(9): 318-323.
[12] MA Xiao-xiao and HUANG Yan. Publicly Traceable Accountable Ciphertext Policy Attribute Based Encryption Scheme Supporting Large Universe [J]. Computer Science, 2020, 47(6A): 420-423.
[13] JIN Xiao-min, HUA Wen-qiang. Energy Optimization Oriented Resource Management in Mobile Cloud Computing [J]. Computer Science, 2020, 47(6): 247-251.
[14] SUN Min, CHEN Zhong-xiong, YE Qiao-nan. Workflow Scheduling Strategy Based on HEDSM Under Cloud Environment [J]. Computer Science, 2020, 47(6): 252-259.
[15] LIANG Jun-bin, ZHANG Min, JIANG Chan. Research Progress of Social Sensor Cloud Security [J]. Computer Science, 2020, 47(6): 276-283.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!