Consistency degree calculation is established on the basis of known correspondence, but in real life, the correspondence is generally unknown, so how to calculate consistency of two models under unknown correspondence...Consistency degree calculation is established on the basis of known correspondence, but in real life, the correspondence is generally unknown, so how to calculate consistency of two models under unknown correspondence has become a problem. For this condition, we should analyze unknown correspondence due to the influence of different correspondences.In this paper we obtain the relations of transitions based on event relations using branching processes, and build a behavioral matrix of relations. Based on the permutation of behavioral matrix, we express different correspondences, and define a new formula to compute the maximal consistency degree of two workflow nets. Additionally, this paper utilizes an example to show these definitions, computation as well as the advantages.展开更多
The soundness is a very important criterion for the correctness of the workflow. Specifying the soundness with Computation Tree Logic （CTL） allows us to verify the soundness with symbolic model checkers. Therefore t...The soundness is a very important criterion for the correctness of the workflow. Specifying the soundness with Computation Tree Logic （CTL） allows us to verify the soundness with symbolic model checkers. Therefore the state explosion problem in verifying soundness can be overcome efficiently. When the property is not satisfied by the system, model checking can give a counter-example, which can guide us to correct the workflow. In addition, relaxed soundness is another important criterion for the workflow. We also prove that Computation Tree Logic ＊ （CTL ＊ ） can be used to character the relaxed soundness of the workflow.展开更多
BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces im...BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces image acquisition time of CMR compared to conventional CINE(C-CINE).METHODS Cardio-oncology patients(n=60)and healthy volunteers(n=29)underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner.Acquisition time,visual image quality assessment,and biventricular metrics(end-diastolic volume,endsystolic volume,stroke volume,ejection fraction,left ventricular mass,and wall thickness)were analyzed and compared between C-CINE and AI-CS-CINE with Bland–Altman analysis,and calculation of intraclass coefficient(ICC).RESULTS In 89 participants(58.5±16.8 years,42 males,47 females),total AI-CS-CINE acquisition and reconstruction time(37 seconds)was 84%faster than C-CINE(238 seconds).C-CINE required repeats in 23%(20/89)of cases(approximately 8 minutes lost),while AI-CS-CINE only needed one repeat(1%;2 seconds lost).AICS-CINE had slightly lower contrast but preserved structural clarity.Bland-Altman plots and ICC(0.73≤r≤0.98)showed strong agreement for left ventricle(LV)and right ventricle(RV)metrics,including those in the cardiac amyloidosis subgroup(n=31).AI-CS-CINE enabled faster,easier imaging in patients with claustrophobia,dyspnea,arrhythmias,or restlessness.Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.CONCLUSION AI-CS-CINE accelerated CMR image acquisition and reconstruction,preserved anatomical detail,and diminished impact of patient-related motion.Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients,including the cardiac amyloidosis cohort,as well as healthy volunteers regardless of left and right ventricular size and function.AI-CS-CINE significantly enhanced CMR workflow,particularly in challenging cases.The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.展开更多
Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich da...Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich data for prognostication and clinical care.They can handle complex nonlinear relation-ships in medical data and have advantages over traditional predictive methods.A number of models are used:(1)Feedforward networks;and(2)Recurrent NN and convolutional NN to predict key outcomes such as mortality,length of stay in the ICU and the likelihood of complications.Current NN models exist in silos;their integration into clinical workflow requires greater transparency on data that are analyzed.Most models that are accurate enough for use in clinical care operate as‘black-boxes’in which the logic behind their decision making is opaque.Advan-ces have occurred to see through the opacity and peer into the processing of the black-box.In the near future ML is positioned to help in clinical decision making far beyond what is currently possible.Transparency is the first step toward vali-dation which is followed by clinical trust and adoption.In summary,NNs have the transformative ability to enhance predictive accuracy and improve patient management in ICUs.The concept should soon be turning into reality.展开更多
The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tas...The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.展开更多
Workflow management is an important aspect in CSCW at present. The elementary knowledge of workflow process is introduced, the Petri nets based process modeling methodology and basic definitions are provided, and the ...Workflow management is an important aspect in CSCW at present. The elementary knowledge of workflow process is introduced, the Petri nets based process modeling methodology and basic definitions are provided, and the analysis and verification of structural and behavioral correctness of workflow process are discussed. Finally, the algorithm of verification of process definitions is proposed.展开更多
Along with the extensive use of workflow, analysis methods to verify the correctness of the workflow are becoming more and more important. In the paper, we exploit the verification method based on Petri net for workfl...Along with the extensive use of workflow, analysis methods to verify the correctness of the workflow are becoming more and more important. In the paper, we exploit the verification method based on Petri net for workflow process models which deals with the verification of workflow and finds the potential errors in the process design. Additionally, an efficient verification algorithm is given.展开更多
Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be exec...Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be executed,which resources are authorised to perform which tasks,and data that is required for,and produced by,these tasks.As workflow instances may run over a sustained period of time,it is important that workflow specifications be checked before they are deployed.Workflow verification is usually concerned with control-flow dependencies only;however,transition conditions based on data may further restrict possible choices between tasks.In this paper we extend workflow nets where transitions have concrete conditions associated with them,called WTC-nets.We then demonstrate that we can determine which execution paths of a WTC-net that are possible according to the control-flow dependencies,are actually possible when considering the conditions based on data.Thus,we are able to more accurately determine at design time whether a workflow net with transition conditions is sound.展开更多
Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current acce...Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current access control models. The model supports roles assignment and dynamic authorization. The paper defines the workflow using Petri net. It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM). Finally, an example of an e-commerce workflow access control model is discussed in detail.展开更多
In a cloud-native era,the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes.However,when encountering continuous workflow requests and unexpected re...In a cloud-native era,the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes.However,when encountering continuous workflow requests and unexpected resource request spikes,the engine is limited to the current workflow load information for resource allocation,which lacks the agility and predictability of resource allocation,resulting in over and underprovisioning resources.This mechanism seriously hinders workflow execution efficiency and leads to high resource waste.To overcome these drawbacks,we propose an adaptive resource allocation scheme named adaptive resource allocation scheme(ARAS)for the Kubernetes-based workflow engines.Considering potential future workflow task requests within the current task pod’s lifecycle,the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios.The ARAS offers resource discovery,resource evaluation,and allocation functionalities and serves as a key component for our tailored workflow engine(KubeAdaptor).By integrating the ARAS into KubeAdaptor for workflow containerized execution,we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS.Compared with the baseline algorithm,experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows,time-saving of 26.4% to 79.86% in the average duration of individual workflow,and an increase of 1% to 16% in centrol processing unit(CPU)and memory resource usage rate.展开更多
The correctness of workflow models is one of the major challenges in context of workflow analysis. The aim of this paper is to provide an improved Petri net-based reduction approach for verifying the correctness of wo...The correctness of workflow models is one of the major challenges in context of workflow analysis. The aim of this paper is to provide an improved Petri net-based reduction approach for verifying the correctness of workflow models. To the end, how to represent well-behaved building blocks and control structures of business processes by Petri nets is given at first, and then how to build well-structured process nets is presented. According to the structural characteristics of well-structured process nets, a set of legacy reduction rules are improved and extended, and then a complete Petri-net-based verification approach is proposed. The sound ness and the complexity with polynomial time for the improved re duction method are also proven.展开更多
For business service workflow,QoS-based services selection can't guarantee whether the composite service satisfies user' s requirement after delivery,because once any service interrupts or quality of service(Q...For business service workflow,QoS-based services selection can't guarantee whether the composite service satisfies user' s requirement after delivery,because once any service interrupts or quality of service(QoS) maliciously reduces,the quality of workflow will be reduced.Trustworthy services can provide reliable QoS,so trustworthiness research could improve the efficiency of services selection.This paper investigates trust assessment in the perspective of workflow.Firstly,trust network of business service workflow(TN-BSW) is proposed to analyze trust attributes;then,the trust measurement system of TN-BSW is investigated to assess the trust value quantitatively;and then,a trust-aware service recommendation model(TaSRM) is proposed to enhance the efficiency of QoS-basedservices selection;finally,experiment shows the feasibility of TN-BSWand the performance of TaSRM.展开更多
The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior tea...The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior team performance can influence the values of structural measures such as centrality and connectedness. In this work we propose a novel simulation model based on agent-based modeling that allows social network structure to be treated as an exogeneous variable but still be allowed to evolve over time. The simulation model consists of experiments with multiple runs in each experiment. The social network amongst the agents is allowed to evolve between runs based on past performance. However, within each run, the social network is treated as an exogenous variable where it directly affects workflow performance. The simulation model we describe has several inputs and parameters that increase its validity, including a realistic workflow management depiction and real-world cognitive strategies by the agents.展开更多
Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of wor...Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of workflow products and research prototypes provide the few supports for the verification of XML-based workflow model, such as free-deadlock properties, which is essential to successful application of workflow technology. In this paper, we tackle this problem by mapping the XML-based workflow model into Petri-net, a kind of well-known formalism for modeling, analyzing and verifying system. As a result, the XML-based workflow model can be automatically verified with the help of general Petri-net tools, such as DANAMICS. The presented approach not only enables end users to represent workflow model with XML-based modeling language, but also the correctness of model can be ensured, thus satisfying the needs of business processes.展开更多
In order to effectively control the random tasks submitted and executed in grid workflow,a grid workflow model based on hybrid petri-net is presented. This model is composed of random petri-net,colored petri-net and g...In order to effectively control the random tasks submitted and executed in grid workflow,a grid workflow model based on hybrid petri-net is presented. This model is composed of random petri-net,colored petri-net and general petri-net. Therein random petri-net declares the relationship between the number of grid users' random tasks and the size of service window and computes the server intensity of grid system. Colored petri-net sets different color for places with grid services and provides the valid interfaces for grid resource allocation and task scheduling. The experiment indicated that the model presented in this letter could compute the valve between the number of users' random tasks and the size of grid service window in grid workflow management system.展开更多
Accurate performance prediction of Grid workflow activities can help Grid schedulers map activitiesto appropriate Grid sites.This paper describes an approach based on features-ranked RBF neural networkto predict the p...Accurate performance prediction of Grid workflow activities can help Grid schedulers map activitiesto appropriate Grid sites.This paper describes an approach based on features-ranked RBF neural networkto predict the performance of Grid workflow activities.Experimental results for two kinds of real worldGrid workflow activities are presented to show effectiveness of our approach.展开更多
In this paper, workflow technology is firstly applied to the cabinet dyeing order system for cabinet dyeing unit. The system setup workflow models which conform to the existing system and resource and the system adopt...In this paper, workflow technology is firstly applied to the cabinet dyeing order system for cabinet dyeing unit. The system setup workflow models which conform to the existing system and resource and the system adopts flexible workflow process mechanism to enhance the adaptability and opening and solve the exception and abnormality manipulation. The results show that it can not only provide the better dyeing order process, but also set dyer free from the fussy daily business and predigest task flow and heighten production efficiency.展开更多
In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our ...In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.展开更多
Cloud workloads are highly dynamic and complex,making task scheduling in cloud computing a challenging problem.While several scheduling algorithms have been proposed in recent years,they are mainly designed to handle ...Cloud workloads are highly dynamic and complex,making task scheduling in cloud computing a challenging problem.While several scheduling algorithms have been proposed in recent years,they are mainly designed to handle batch tasks and not well-suited for real-time workloads.To address this issue,researchers have started exploring the use of Deep Reinforcement Learning(DRL).However,the existing models are limited in handling independent tasks and cannot process workflows,which are prevalent in cloud computing and consist of related subtasks.In this paper,we propose SA-DQN,a scheduling approach specifically designed for real-time cloud workflows.Our approach seamlessly integrates the Simulated Annealing(SA)algorithm and Deep Q-Network(DQN)algorithm.The SA algorithm is employed to determine an optimal execution order of subtasks in a cloud server,serving as a crucial feature of the task for the neural network to learn.We provide a detailed design of our approach and show that SA-DQN outperforms existing algorithms in terms of handling real-time cloud workflows through experimental results.展开更多
An evaluation approach for the response time probability distribution of workflows based on the fluid stochastic Petri net formalism is presented. Firstly, some problems about stochastic workflow net modeling are disc...An evaluation approach for the response time probability distribution of workflows based on the fluid stochastic Petri net formalism is presented. Firstly, some problems about stochastic workflow net modeling are discussed. Then how to convert a stochastic workflow net model into a fluid stochastic Petri net model is described. The response time distribution can be obtained directly upon the transient state solution of the fluid stochastic Petri net model. In the proposed approach, there are not any restrictions on the structure of workflow models, and the processing times of workflow tasks can be modeled by using arbitrary probability distributions. Large workflow models can be efficiently tackled by recursively using a net reduction technique.展开更多
基金supported in part by the National Key R&D Program of China(2017YFB1001804)Shanghai Science and Technology Innovation Action Plan Project(16511100900)the National Natural Science Foundation of China(61572360)
文摘Consistency degree calculation is established on the basis of known correspondence, but in real life, the correspondence is generally unknown, so how to calculate consistency of two models under unknown correspondence has become a problem. For this condition, we should analyze unknown correspondence due to the influence of different correspondences.In this paper we obtain the relations of transitions based on event relations using branching processes, and build a behavioral matrix of relations. Based on the permutation of behavioral matrix, we express different correspondences, and define a new formula to compute the maximal consistency degree of two workflow nets. Additionally, this paper utilizes an example to show these definitions, computation as well as the advantages.
基金Supported by the National Natural Science Foun-dation of China (60573046)
文摘The soundness is a very important criterion for the correctness of the workflow. Specifying the soundness with Computation Tree Logic （CTL） allows us to verify the soundness with symbolic model checkers. Therefore the state explosion problem in verifying soundness can be overcome efficiently. When the property is not satisfied by the system, model checking can give a counter-example, which can guide us to correct the workflow. In addition, relaxed soundness is another important criterion for the workflow. We also prove that Computation Tree Logic ＊ （CTL ＊ ） can be used to character the relaxed soundness of the workflow.
基金Supported by James Russell Hornsby and Jun Xiong Fund and United Imaging Healthcare.
文摘BACKGROUND A key cardiac magnetic resonance(CMR)challenge is breath-holding duration,difficult for cardiac patients.AIM To evaluate whether artificial intelligence-assisted compressed sensing CINE(AICS-CINE)reduces image acquisition time of CMR compared to conventional CINE(C-CINE).METHODS Cardio-oncology patients(n=60)and healthy volunteers(n=29)underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner.Acquisition time,visual image quality assessment,and biventricular metrics(end-diastolic volume,endsystolic volume,stroke volume,ejection fraction,left ventricular mass,and wall thickness)were analyzed and compared between C-CINE and AI-CS-CINE with Bland–Altman analysis,and calculation of intraclass coefficient(ICC).RESULTS In 89 participants(58.5±16.8 years,42 males,47 females),total AI-CS-CINE acquisition and reconstruction time(37 seconds)was 84%faster than C-CINE(238 seconds).C-CINE required repeats in 23%(20/89)of cases(approximately 8 minutes lost),while AI-CS-CINE only needed one repeat(1%;2 seconds lost).AICS-CINE had slightly lower contrast but preserved structural clarity.Bland-Altman plots and ICC(0.73≤r≤0.98)showed strong agreement for left ventricle(LV)and right ventricle(RV)metrics,including those in the cardiac amyloidosis subgroup(n=31).AI-CS-CINE enabled faster,easier imaging in patients with claustrophobia,dyspnea,arrhythmias,or restlessness.Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.CONCLUSION AI-CS-CINE accelerated CMR image acquisition and reconstruction,preserved anatomical detail,and diminished impact of patient-related motion.Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients,including the cardiac amyloidosis cohort,as well as healthy volunteers regardless of left and right ventricular size and function.AI-CS-CINE significantly enhanced CMR workflow,particularly in challenging cases.The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.
文摘Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich data for prognostication and clinical care.They can handle complex nonlinear relation-ships in medical data and have advantages over traditional predictive methods.A number of models are used:(1)Feedforward networks;and(2)Recurrent NN and convolutional NN to predict key outcomes such as mortality,length of stay in the ICU and the likelihood of complications.Current NN models exist in silos;their integration into clinical workflow requires greater transparency on data that are analyzed.Most models that are accurate enough for use in clinical care operate as‘black-boxes’in which the logic behind their decision making is opaque.Advan-ces have occurred to see through the opacity and peer into the processing of the black-box.In the near future ML is positioned to help in clinical decision making far beyond what is currently possible.Transparency is the first step toward vali-dation which is followed by clinical trust and adoption.In summary,NNs have the transformative ability to enhance predictive accuracy and improve patient management in ICUs.The concept should soon be turning into reality.
文摘The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.
文摘Workflow management is an important aspect in CSCW at present. The elementary knowledge of workflow process is introduced, the Petri nets based process modeling methodology and basic definitions are provided, and the analysis and verification of structural and behavioral correctness of workflow process are discussed. Finally, the algorithm of verification of process definitions is proposed.
文摘Along with the extensive use of workflow, analysis methods to verify the correctness of the workflow are becoming more and more important. In the paper, we exploit the verification method based on Petri net for workflow process models which deals with the verification of workflow and finds the potential errors in the process design. Additionally, an efficient verification algorithm is given.
基金Project supported by the National Science and Technology Major Project of China (No.2010ZX01042-002-002-01)the National Basic Research Program (973) of China (No.2009CB320700)the National Natural Science Foundation of China (Nos.61073005 and 61003099)
文摘Workflow management is concerned with automated support for business processes.Workflow management systems are driven by process models specifying the tasks that need to be executed,the order in which they can be executed,which resources are authorised to perform which tasks,and data that is required for,and produced by,these tasks.As workflow instances may run over a sustained period of time,it is important that workflow specifications be checked before they are deployed.Workflow verification is usually concerned with control-flow dependencies only;however,transition conditions based on data may further restrict possible choices between tasks.In this paper we extend workflow nets where transitions have concrete conditions associated with them,called WTC-nets.We then demonstrate that we can determine which execution paths of a WTC-net that are possible according to the control-flow dependencies,are actually possible when considering the conditions based on data.Thus,we are able to more accurately determine at design time whether a workflow net with transition conditions is sound.
文摘Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current access control models. The model supports roles assignment and dynamic authorization. The paper defines the workflow using Petri net. It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM). Finally, an example of an e-commerce workflow access control model is discussed in detail.
基金supported by the National Natural Science Foundation of China(61873030,62002019).
文摘In a cloud-native era,the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes.However,when encountering continuous workflow requests and unexpected resource request spikes,the engine is limited to the current workflow load information for resource allocation,which lacks the agility and predictability of resource allocation,resulting in over and underprovisioning resources.This mechanism seriously hinders workflow execution efficiency and leads to high resource waste.To overcome these drawbacks,we propose an adaptive resource allocation scheme named adaptive resource allocation scheme(ARAS)for the Kubernetes-based workflow engines.Considering potential future workflow task requests within the current task pod’s lifecycle,the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios.The ARAS offers resource discovery,resource evaluation,and allocation functionalities and serves as a key component for our tailored workflow engine(KubeAdaptor).By integrating the ARAS into KubeAdaptor for workflow containerized execution,we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS.Compared with the baseline algorithm,experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows,time-saving of 26.4% to 79.86% in the average duration of individual workflow,and an increase of 1% to 16% in centrol processing unit(CPU)and memory resource usage rate.
基金Supported by the Scientific Research Foundation of Edu-cation Agency of Liaoning Province (20040088) and Scientific ResearchFoundation of Dalian Nationalities University (20046202)
文摘The correctness of workflow models is one of the major challenges in context of workflow analysis. The aim of this paper is to provide an improved Petri net-based reduction approach for verifying the correctness of workflow models. To the end, how to represent well-behaved building blocks and control structures of business processes by Petri nets is given at first, and then how to build well-structured process nets is presented. According to the structural characteristics of well-structured process nets, a set of legacy reduction rules are improved and extended, and then a complete Petri-net-based verification approach is proposed. The sound ness and the complexity with polynomial time for the improved re duction method are also proven.
基金Supported by the Research Fund for the Doctoral Program of Higher Education of China(No.20120002110034)Initiative Scientific Research Program of Tsinghua University(No.20111080998)
文摘For business service workflow,QoS-based services selection can't guarantee whether the composite service satisfies user' s requirement after delivery,because once any service interrupts or quality of service(QoS) maliciously reduces,the quality of workflow will be reduced.Trustworthy services can provide reliable QoS,so trustworthiness research could improve the efficiency of services selection.This paper investigates trust assessment in the perspective of workflow.Firstly,trust network of business service workflow(TN-BSW) is proposed to analyze trust attributes;then,the trust measurement system of TN-BSW is investigated to assess the trust value quantitatively;and then,a trust-aware service recommendation model(TaSRM) is proposed to enhance the efficiency of QoS-basedservices selection;finally,experiment shows the feasibility of TN-BSWand the performance of TaSRM.
文摘The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior team performance can influence the values of structural measures such as centrality and connectedness. In this work we propose a novel simulation model based on agent-based modeling that allows social network structure to be treated as an exogeneous variable but still be allowed to evolve over time. The simulation model consists of experiments with multiple runs in each experiment. The social network amongst the agents is allowed to evolve between runs based on past performance. However, within each run, the social network is treated as an exogenous variable where it directly affects workflow performance. The simulation model we describe has several inputs and parameters that increase its validity, including a realistic workflow management depiction and real-world cognitive strategies by the agents.
文摘Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of workflow products and research prototypes provide the few supports for the verification of XML-based workflow model, such as free-deadlock properties, which is essential to successful application of workflow technology. In this paper, we tackle this problem by mapping the XML-based workflow model into Petri-net, a kind of well-known formalism for modeling, analyzing and verifying system. As a result, the XML-based workflow model can be automatically verified with the help of general Petri-net tools, such as DANAMICS. The presented approach not only enables end users to represent workflow model with XML-based modeling language, but also the correctness of model can be ensured, thus satisfying the needs of business processes.
基金the National Natural Science Foundation of China (No.60573141, 70271050)the Natural Science Foundation of Jiangsu Province (No.BK2005146)+3 种基金the High Technology Research Programme of Jiangsu Prov-ince (No.BG2005037, BG2005038, BG2006001)the High Technology Research Programme of Nanjing (No. 2006RZ105)the Foundation of National Laboratory for Modern Communications (No.9140C1101010603)the Key Laboratory of Information Technology Processing of Jiangsu Province (No.kjs05001, kjs0606).
文摘In order to effectively control the random tasks submitted and executed in grid workflow,a grid workflow model based on hybrid petri-net is presented. This model is composed of random petri-net,colored petri-net and general petri-net. Therein random petri-net declares the relationship between the number of grid users' random tasks and the size of service window and computes the server intensity of grid system. Colored petri-net sets different color for places with grid services and provides the valid interfaces for grid resource allocation and task scheduling. The experiment indicated that the model presented in this letter could compute the valve between the number of users' random tasks and the size of grid service window in grid workflow management system.
基金Supported by the European Union through the IST-034601 edutain@grid project
文摘Accurate performance prediction of Grid workflow activities can help Grid schedulers map activitiesto appropriate Grid sites.This paper describes an approach based on features-ranked RBF neural networkto predict the performance of Grid workflow activities.Experimental results for two kinds of real worldGrid workflow activities are presented to show effectiveness of our approach.
文摘In this paper, workflow technology is firstly applied to the cabinet dyeing order system for cabinet dyeing unit. The system setup workflow models which conform to the existing system and resource and the system adopts flexible workflow process mechanism to enhance the adaptability and opening and solve the exception and abnormality manipulation. The results show that it can not only provide the better dyeing order process, but also set dyer free from the fussy daily business and predigest task flow and heighten production efficiency.
文摘In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.
基金supported by the Fundamental Research Funds for the Central Universities(2023JC004 and 2023YQ002)。
文摘Cloud workloads are highly dynamic and complex,making task scheduling in cloud computing a challenging problem.While several scheduling algorithms have been proposed in recent years,they are mainly designed to handle batch tasks and not well-suited for real-time workloads.To address this issue,researchers have started exploring the use of Deep Reinforcement Learning(DRL).However,the existing models are limited in handling independent tasks and cannot process workflows,which are prevalent in cloud computing and consist of related subtasks.In this paper,we propose SA-DQN,a scheduling approach specifically designed for real-time cloud workflows.Our approach seamlessly integrates the Simulated Annealing(SA)algorithm and Deep Q-Network(DQN)algorithm.The SA algorithm is employed to determine an optimal execution order of subtasks in a cloud server,serving as a crucial feature of the task for the neural network to learn.We provide a detailed design of our approach and show that SA-DQN outperforms existing algorithms in terms of handling real-time cloud workflows through experimental results.
基金The National Natural Science Foundation of China(No.60175027).
文摘An evaluation approach for the response time probability distribution of workflows based on the fluid stochastic Petri net formalism is presented. Firstly, some problems about stochastic workflow net modeling are discussed. Then how to convert a stochastic workflow net model into a fluid stochastic Petri net model is described. The response time distribution can be obtained directly upon the transient state solution of the fluid stochastic Petri net model. In the proposed approach, there are not any restrictions on the structure of workflow models, and the processing times of workflow tasks can be modeled by using arbitrary probability distributions. Large workflow models can be efficiently tackled by recursively using a net reduction technique.
