Performance analysis and optimization for workflow authorization

Many workflow management systems have been developed to enhance the performance of workflow executions. The authorization policies deployed in the system may restrict the task executions. The common authorization constraints include role constraints, Separation of Duty (SoD), Binding of Duty (BoD) and temporal constraints. This paper presents the methods to check the feasibility of these constraints, and also determines the time durations when the temporal constraints will not impose negative impact on performance. Further, this paper presents an optimal authorization method, which is optimal in the sense that it can minimize a workflow’s delay caused by the temporal constraints. The authorization analysis methods are also extended to analyze the stochastic workflows, in which the tasks’ execution times are not known exactly, but follow certain probability distributions. Simulation experiments have been conducted to verify the effectiveness of the proposed authorization methods. The experimental results show that comparing with the intuitive authorization method, the optimal authorization method can reduce the delay caused by the authorization constraints and consequently reduce the workflows’ response time

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Optimizing performance of workflow executions under authorization control

“Business processes or workflows are often used to model enterprise or scientific applications. It has received considerable attention to automate workflow executions on computing resources. However, many workflow scenarios still involve human activities and consist of a mixture of human tasks and computing tasks. Human involvement introduces security and authorization concerns, requiring restrictions on who is allowed to perform which tasks at what time. Role- Based Access Control (RBAC) is a popular authorization mechanism. In RBAC, the authorization concepts such as roles and permissions are defined, and various authorization constraints are supported, including separation of duty, temporal constraints, etc. Under RBAC, users are assigned to certain roles, while the roles are associated with prescribed permissions. When we assess resource capacities, or evaluate the performance of workflow executions on supporting platforms, it is often assumed that when a task is allocated to a resource, the resource will accept the task and start the execution once a processor becomes available. However, when the authorization policies are taken into account,” this assumption may not be true and the situation becomes more complex. For example, when a task arrives, a valid and activated role has to be assigned to a task before the task can start execution. The deployed authorization constraints may delay the workflow execution due to the roles’ availability, or other restrictions on the role assignments, which will consequently have negative impact on application performance. When the authorization constraints are present to restrict the workflow executions, it entails new research issues that have not been studied yet in conventional workflow management. This thesis aims to investigate these new research issues. First, it is important to know whether a feasible authorization solution can be found to enable the executions of all tasks in a workflow, i.e., check the feasibility of the deployed authorization constraints. This thesis studies the issue of the feasibility checking and models the feasibility checking problem as a constraints satisfaction problem. Second, it is useful to know when the performance of workflow executions will not be affected by the given authorization constraints. This thesis proposes the methods to determine the time durations when the given authorization constraints do not have impact. Third, when the authorization constraints do have the performance impact, how can we quantitatively analyse and determine the impact? When there are multiple choices to assign the roles to the tasks, will different choices lead to the different performance impact? If so, can we find an optimal way to conduct the task-role assignments so that the performance impact is minimized? This thesis proposes the method to analyze the delay caused by the authorization constraints if the workflow arrives beyond the non-impact time duration calculated above. Through the analysis of the delay, we realize that the authorization method, i.e., the method to select the roles to assign to the tasks affects the length of the delay caused by the authorization constraints. Based on this finding, we propose an optimal authorization method, called the Global Authorization Aware (GAA) method. Fourth, a key reason why authorization constraints may have impact on performance is because the authorization control directs the tasks to some particular roles. Then how to determine the level of workload directed to each role given a set of authorization constraints? This thesis conducts the theoretical analysis about how the authorization constraints direct the workload to the roles, and proposes the methods to calculate the arriving rate of the requests directed to each role under the role, temporal and cardinality constraints. Finally, the amount of resources allocated to support each individual role may have impact on the execution performance of the workflows. Therefore, it is desired to develop the strategies to determine the adequate amount of resources when the authorization control is present in the system. This thesis presents the methods to allocate the appropriate quantity for resources, including both human resources and computing resources. Different features of human resources and computing resources are taken into account. For human resources, the objective is to maximize the performance subject to the budgets to hire the human resources, while for computing resources, the strategy aims to allocate adequate amount of computing resources to meet the QoS requirements

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Particle swarm optimization and differential evolution for multi-objective multiple machine scheduling

Production scheduling is one of the most important issues in the planning and operation of manufacturing systems. Customers increasingly expect to receive the right product at the right price at the right time. Various problems experienced in manufacturing, for example low machine utilization and excessive work-in-process, can be attributed directly to inadequate scheduling. In this dissertation a production scheduling algorithm is developed for Optimatix, a South African-based company specializing in supply chain optimization. To address the complex requirements of the customer, the problem was modeled as a flexible job shop scheduling problem with sequence-dependent set-up times, auxiliary resources and production down time. The algorithm development process focused on investigating the application of both particle swarm optimization (PSO) and differential evolution (DE) to production scheduling environments characterized by multiple machines and multiple objectives. Alternative problem representations, algorithm variations and multi-objective optimization strategies were evaluated to obtain an algorithm which performs well against both existing rule-based algorithms and an existing complex flexible job shop scheduling solution strategy. Finally, the generality of the priority-based algorithm was evaluated by applying it to the scheduling of production and maintenance activities at Centurion Ice Cream and Sweets. The production environment was modeled as a multi-objective uniform parallel machine shop problem with sequence-dependent set-up times and unavailability intervals. A self-adaptive modified vector evaluated DE algorithm was developed and compared to classical PSO and DE vector evaluated algorithms. Promising results were obtained with respect to the suitability of the algorithms for solving a range of multi-objective multiple machine scheduling problems. CopyrightDissertation (MEng)--University of Pretoria, 2009.Industrial and Systems Engineeringunrestricte

A Framework for Evaluating the Performance of Supply Chain Risk in E-commerce

The perceived risk is found to be a barrier for e-commerce application. It has been widely demonstrated in previous studies that the e-commerce is closely related with risk assessment. Taking into account of the scope of supply chain management, the activities of e-commerce system mostly deal with information flow, rather than either product or service flows. With regard to the rapid growth of e-commerce, there is imbalance between preparation and mitigation activities. More specifically, there is no formal model which shows supply chain risk in the e-commerce system, regarded as the research gap. Hence, one way to analyze and map out complex system as potential risk is to make Supply Chain Risk Management (SCRM) framework. This study is conducted to develop a framework about SCRM in the e-commerce area. Taking a case study on e-commerce based company, the SCRM framework is developed incorporating 8 perceived risk model in e-commerce: such as financial, social, time, performance, physical, privacy, security, and psychological risk. The expected contribution in theory and practice is discussed

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Constant Flow Management - Investigating manufacturing flow variability

This project investigates the manufacturing flow variability in order to stabilize the factory process flow. Nowadays, in manufacturing production lines and particularly in modern front end semiconductor lines, processes and equipments are very complex. Any disturbance of the process creates variability in the line, and causes substantial losses in productivity for manufacturing corporations. These disturbances are unpredictable, difficult to control and result in long recovery times. Variability occurring in a production system disturbs the whole processing flow and results in long product cycle times. Hence, a range of sources of variability was determined from the literature and analyzed. This lead with the cooperation of factory managers to the development of four main objectives: (1) Determine a proper metric to measure the variability in the production system. (2) Determine the effect of batching and tool availability on the process flow. (3) Understand the interaction between operations. (4) Develop a release strategy in order to stabilize the production flow. First, from the observation of real production data, a difference metric was developed and operations creating or removing variability were identified. The propagation of variability can be followed using a correlation coefficient. Nevertheless, the data were not detailed enough to explain the origin of the variability. Consequently, several simulation models were created to investigate variability. The simulations‘ results show that the release strategy should be adjusted as a function of batch, tool availability and constraint parameters, in order to stabilize the flow of items in the line and control cycle time and cycle time variability. The notion of critical availability is introduced and defined. Improvement of the line performance is obtained through a tighter control of the availability of high capacity operations. This lead to the development of a new hybrid push pull release strategy, named CONFLOW, to regulate the flow of items reaching the constraint operation. CONFLOW was tested under many simulating conditions (batching, parallel processing, and different line length). Compared to a push system, CONFLOW release strategy results, into significant improvement (up to 80%) in cycle time, cycle time standard deviation and WIP level at the cost of 13% reduction in throughput. CONFLOW performances were compared to common TOC strategies (SA and DBR). The results are encouraging. In the specific conditions considered, CONFLOW performances are similar to SA and slightly better than DBR