855 research outputs found

    Performance Prediction of Cloud-Based Big Data Applications

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    Big data analytics have become widespread as a means to extract knowledge from large datasets. Yet, the heterogeneity and irregular- ity usually associated with big data applications often overwhelm the existing software and hardware infrastructures. In such con- text, the exibility and elasticity provided by the cloud computing paradigm o er a natural approach to cost-e ectively adapting the allocated resources to the application’s current needs. However, these same characteristics impose extra challenges to predicting the performance of cloud-based big data applications, a key step to proper management and planning. This paper explores three modeling approaches for performance prediction of cloud-based big data applications. We evaluate two queuing-based analytical models and a novel fast ad hoc simulator in various scenarios based on di erent applications and infrastructure setups. The three ap- proaches are compared in terms of prediction accuracy, nding that our best approaches can predict average application execution times with 26% relative error in the very worst case and about 7% on average

    Optimal control of decoupling point with deteriorating items

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    Purpose: The aim of this paper is to develop a dynamic model to simultaneously determine the optimal position of the decoupling point and the optimal path of the production rate as well as the inventory level in a supply chain. With the objective to minimize the total cost of the deviation from the target setting, the closed forms of the optimal solution are derived over a finite planning horizon with deterioration rate under time-varying demand rate. Design/methodology/approach: The Pontryagin's Maximum Principle is employed to explore the optimal position of decoupling point and the optimal production and inventory rate for the proposed dynamic models. The performances of parameters are illustrated through analytical and numerical approaches. Findings: The results denote that the optimal production rate and inventory level are closely related to the target setting which are highly dependent on production policy; meanwhile the optimal decoupling point is exist and unique with the fluctuating of deteriorating rate and product life cycle. The further analyses through both mathematic and numerical approaches indicate that the shorten of product life cycle shifts the optimal decoupling point forward to the end customer meanwhile a backward shifting appears when the deterioration rate increase. Research limitations/implications: There is no shortage allowed and the replacement policy is not taken into account. Practical implications: Solutions derived from this study of the optimal production-inventory plan and decoupling point are instructive for operation decision making. The obtained knowledge about the performance of different parameters is critical to deteriorating supply chains management. Originality/value: Many previous models of the production-inventory problem are only focused on the cost. The paper introduces the decoupling point control into the production and inventory problem such that a critical element-customer demand, can be taken into account. And the problem is solved as dynamic when the production rate, inventory level and the position of the decoupling point are all regarded as decision variables.Peer Reviewe

    Mutton Traceability Method Based on Internet of Things

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    In order to improve the mutton traceability efficiency for Internet of Things and solve the problem of data transmission, analyzed existing tracking algorithm, proposed the food traceability application model, Petri network model of food traceability and food traceability of time series data of improved K-means algorithm based on the Internet of things. The food traceability application model to convert, integrate and mine the heterogeneous information, implementation of the food safety traceability information management, Petri network model for food traceability in the process of the state transition were analyzed and simulated and provides a theoretical basis to study the behavior described in the food traceability system and structural design. The experiments on simulation data show that the proposed traceability method based on Internet of Things is more effective for mutton traceability data than the traditional K-means methods

    Mathematics in Software Reliability and Quality Assurance

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    This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment

    Design logical linguistic models to calculate necessity in trucks during agricultural cargoes logistics using fuzzy logic

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    The study is aimed to develop the logic-linguistic models to design a number of rules for the correct calculation of the vehicles needed, taking into account the technical, technological, and weather and climate conditions of the harvesting and transport complex. The article has shown that the construction of the design of logic-linguistic models was not performed earlier to solve the problem of the agro-industrial production transportation support, considering the opportunity of forecasting size of influences of the weather and climatic factors on improving the productivity of the harvesting and transport complex elements. It is determined that the experience of applying the fuzzy logic theory in many practice situations confirms the universality of the mathematical apparatus. This toolkit provides better results than classical approaches (set theory, probability theory). This aspect indicates the expediency of the chosen mathematical apparatus for solving the tasks. The article using fuzzy logic explores the relationship and interdependence of technical, technological factors and weather and climate conditions for modeling transport support in harvesting and transport complex. Fuzzification of the parameters is carried out, based on the compiled equations using trapezoidal and triangular membership functions. The set of rules necessary for the creation of logical-linguistic models (LLM) for each factor has been arranged. LLMs were developed for dependent parameters, which will allow further modeling of the transport support of the harvesting and transport complex in the Fuzzy Logic Toolbox application of the MATLAB package

    Modelling information flow for organisations delivering microsystems technology

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    Motivated by recent growth and applications of microsystems technology (MST), companies within the MST domain are beginning to explore avenues for understanding, maintaining and improving information flow, within their organisations and to/from customers, with a view to enhancing delivery performance. Delivery for organisations is the flow of goods from sellers to buyers and a classic approach to understanding information flow is via the use of modelling techniques. Cont/d
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