Energy-Aware Cloud Management through Progressive SLA Specification

Novel energy-aware cloud management methods dynamically reallocate computation across geographically distributed data centers to leverage regional electricity price and temperature differences. As a result, a managed VM may suffer occasional downtimes. Current cloud providers only offer high availability VMs, without enough flexibility to apply such energy-aware management. In this paper we show how to analyse past traces of dynamic cloud management actions based on electricity prices and temperatures to estimate VM availability and price values. We propose a novel SLA specification approach for offering VMs with different availability and price values guaranteed over multiple SLAs to enable flexible energy-aware cloud management. We determine the optimal number of such SLAs as well as their availability and price guaranteed values. We evaluate our approach in a user SLA selection simulation using Wikipedia and Grid'5000 workloads. The results show higher customer conversion and 39% average energy savings per VM.Comment: 14 pages, conferenc

Synthesis and Stochastic Assessment of Cost-Optimal Schedules

We present a novel approach to synthesize good schedules for a class of scheduling problems that is slightly more general than the scheduling problem FJm,a|gpr,r_j,d_j|early/tardy. The idea is to prime the schedule synthesizer with stochastic information more meaningful than performance factors with the objective to minimize the expected cost caused by storage or delay. The priming information is obtained by stochastic simulation of the system environment. The generated schedules are assessed again by simulation. The approach is demonstrated by means of a non-trivial scheduling problem from lacquer production. The experimental results show that our approach achieves in all considered scenarios better results than the extended processing times approach

Approximate performance analysis of production lines with continuous material flows and finite buffers

In this paper, we analyze production lines consisting of a number of machines or servers in series with a finite buffer between each pair of machines. The flow of products through the machines is continuous. Each machine suffers from breakdowns, because of, for example, failures, cleaning and changeover. The up- and downtimes are independent and generally distributed. We develop a new method to efficiently and accurately estimate the throughput and the mean buffer content of the production line. This method relies on decomposition of the production line into two-stage, one-buffer subsystems aggregating the up- and downstream part of the line. For each subsystem, the parameters of the aggregate up- and downtimes are determined iteratively by employing matrix-analytic techniques. The proposed method performs very well on a large test set consisting of over 49,000 cases. Remarkably, the performance of the method does not deteriorate in case of highly unpredictable up- and downtimes, as often seen in practice. We apply the method to a bottling line at brewery Heineken Den Bosch and an assembly line at NXP Semiconductors

Analysis and improvement of a bottling line using a simulation modelling approach

This project thesis is focused on the study of a bottling production line using a modelling simulation method, through which we analyse the inefficiencies and then improve their performance. Moreover, the line is also analysed thorugh an analytic approach applying a formula to optimize the buffer sizing. The two approachs are compared to highlight the differences

Semi-Markov and delay time models of maintenance

This thesis is concerned with modelling inspection policies of facilities which Qraduallv deteriorate in time. The context of inspection policies lends itself readily to probabilistic modelling. Indeed, many of the published theoretical models to be found in the literature adopt a Markov approach, where states are usually 'operating', 'operating but fault present', and 'failed'. However, most of these models fail to discuss the 'fit' of the model to data,a nd virtually no exampleso f actual applications or case-studiesa re to be found. hi a series of recent papers dating from 1984, a robust approach to solve these problems has been introduced and developed as the Delay Time Model (DTM). The central concept for this model is the delay time, h, of a fault which is the time lapse from when a fault could first be noticed until the time when its repair can be delayed no longer because of unacceptable consequences. The bottle neck in delay time modelling is how to estimate the delay time distribution parameters. Two methods for estimating these parameters have been developed. namely the subjective method and the objective method. Markov models have the advantage of an extensive body of theory. 'fliere are, however. difficulties of definition, measurement, and calculation when applying Markov models to real-world situations within a maintenance context. Indeed. this problem has motivated the current research which ainis to explore the two modelling methodologies in cases where comparison is valid, and also to gain an insight as to how robust Markov inspection models can be as decision-aids where Markovian properties are not strictly satisfied. It Nvill be seen that a class of inspection problems could be solved by a serni- Markov model using the delay time concept. In this thesis, a typical senii-i%Ia, rkov inspection model based upon the delay time concept is presented for a complex repairable systein that may fail during the course of its service lifetime and the results are compared. Finally, a case study of the senii-Markov inspection model and the delay time model is discussed

Production Systems with Deteriorating Product Quality : System-Theoretic Approach

Manufacturing systems with perishable products are widely seen in practice (e.g., food, metal processing, etc.). In such systems, the quality of a part is highly dependent on its residence time within the system. However, the behavior and properties of these systems have not been studied systematically, and, therefore, is carried out in this dissertation. Specifically, it was assumed that the probability that each unfinished part is of good quality is a decreasing function of its residence time in the preceding buffer. Then, in the framework of serial production lines with machines having Bernoulli and geometric reliability models, closed-form formulas for performance evaluation in the two-machine line case were derived, and develop an aggregation-based procedure to approximate the performance measures in M\u3e2-machine lines. In addition, the monotonicity properties of these production lines using numerical experiments were studied. A case study in an automotive stamping plant is described to illustrate the theoretical results obtained. Also, Bernoulli serial lines with controlled parts released was analyzed for both deterministic and stochastic releases. Finally, bottleneck analysis in Bernoulli serial lines with deteriorating product quality were studied

Prediction of job completion times and optimal overtime allocation for satisfying production due dates

One of the important aspects contributing to the competitiveness and success of a manufacturer is the efficient management for timely order delivery. After production orders are scheduled, there arises the need of a support tool to aid in the analysis with the available information, and to support managerial decision making which ultimately aims at on-time delivery. One way in which companies can meet due-dates of orders that are in jeopardy of being late, is to schedule overtime. This research presents a method used for 1) predict the completion times of scheduled jobs; and 2) optimizing overtime allocation when delays are foreseen. Mathematical mixed-integer linear program models are developed to represent the above problems for a tandem production line with single machine work stages. Non-operational downtime occurrences are considered in the production horizons which can be varied by work stage. Buffer areas (queues) are also included in the production system. These MILP models are solved using commercial optimizer ILOG-OPL studio. Using VBA script with OPL, a friendly interface is built in MS Excel for ease in user manipulation. The interface can also be used in production test to hypothetical “what if” questions. The models are verified using simulation. Runtime evaluation is also preformed to determine the capabilities and limitations of the models

Adaptation of coordination mechanisms to network structures

The coordination efficiency of Supply Chain Management is determined by two opposite poles: benefit from improved planning results and associated coordination cost. The centralization grade, applied coordination mechanisms and IT support have influence on both categories. Therefore three reference types are developed and subsequently detailed in business process models for different network structures. In a simulation study the performance of these organization forms are compared in a process plant network. Coordination benefit is observed if the planning mode is altered by means of a demand planning IT tool. Coordination cost is divided into structural and activity-dependent cost. The activity level rises when reactive planning iterations become necessary as a consequence of inconsistencies among planning levels. Some characteristic influence factors are considered to be a reason for uninfeasible planning. In this study the effect of capacity availability and stochastic machine downtimes is investigated in an uncertain demand situation. Results that if the network runs with high overcapacity, central planning is less likely to increase benefit enough to outweigh associated cost. Otherwise, if capacity constraints are crucial, a central planning mode is recommendable. When also unforeseen machine downtimes are low, the use of sophisticated IT tools is most profitablePeer Reviewe