SLA-based operations of massively multiplayer online games in clouds

Successful massively multiplayer online games (MMOGs) have today millions of registered users and hundreds of thousands of active concurrent players. To be able to guarantee quality of service (QoS) to a highly variable number of concurrent users, game operators statically over-provision a large infrastructure capable of sustaining the game peak load, even though a large portion of the resources is unused most of the time. To address this problem, we introduce in this work a new MMOG ecosystem for hosting and provisioning of MMOGs which effectively splits the traditional monolithic MMOG companies into three main service providers: game providers, game operators, and resource providers. Their interaction is regulated through comprehensive service level agreements (SLA) that establish the price, terms of operation, and compensation for service violations. In our model, game operators efficiently provision resources for MMOGs from multiple cloud providers, based on dynamic load forecasts, and ensure proper game operation that maintains the required QoS to all clients under varying resource availability. Game providers manage multiple distributed MMOGs for which they lease services under strict operational SLAs from game operators to satisfy all client requests. These three self-standing, smaller, more agile service providers enable access to the MMOG market for the small and medium enterprises, and to the current commercial cloud providers. We evaluate, through simulations based on real-life MMOG traces and commercial cloud SLAs, the impact of resource availability on the QoS offered to the MMOG clients. We find that our model can mitigate the negative effects of resource failures within four minutes and that MMOG server consolidation can accentuate the negative effects of failures in a resource-scarce environment. We further investigate different methods of ranking MMOG operational offers with either single or multiple (competing) MMOG providers. Our results show that compensations for SLA faults in the offer selection process can lead up to 11–16 % gain in the game providers’ income. We also demonstrate that adequate ranking of offers can lead to MMOG operational cost reductions from 20 up to 60 %.     

Automated bank cheque verification using image processing and deep learning methods

Multimedia Tools and Applications - Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate...     

Monitoring the temperature in the cutting zone with chip removal

A system for determining the temperature in the cutting zone is considered. This system assists in minimizing experimental costs and predicting the cutting process on the basis of the technological parameters, with significant gains in tool life and precision of the manufactured part.     

Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments

Economy models have long been considered as a promising complement to the classical distributed resource management not only due of their dynamic and decentralized nature, but also because the concept of financial valuation of resources and services is an inherent part of any such model. In its broadest sense, scheduling of scientific applications in distributed Grid and Cloud environments can be regarded as a market-based negotiation between a scheduling service optimizing user-centric objectives (execution time, budget), and a resource manager optimizing provider-centric metrics (resource utilization, income, job throughput). In this paper, we propose a new instantiation of the negotiation protocol between the scheduler and resource manager using a market-based Continuous Double Auction (CDA) model. We analyze different scheduling strategies that can be applied and identify general strategic patterns that can lead to a fast and cheap work ow execution. In the experimental study, we demonstrate that under certain circumstances one can benefit by applying an aggressive scheduling strategy.     

Overhead Analysis of Scientific Workflows in Grid Environments

Scientific workflows are a topic of great interest in the grid community that sees in the workflow model an attractive paradigm for programming distributed wide-area grid infrastructures. Traditionally, the grid workflow execution is approached as a pure best effort scheduling problem that maps the activities onto the grid processors based on appropriate optimization or local matchmaking heuristics such that the overall execution time is minimized. Even though such heuristics often deliver effective results, the execution in dynamic and unpredictable grid environments is prone to severe performance losses that must be understood for minimizing the completion time or for the efficient use of high-performance resources. In this paper, we propose a new systematic approach to help the scientists and middleware developers understand the most severe sources of performance losses that occur when executing scientific workflows in dynamic grid environments. We introduce an ideal model for the lowest execution time that can be achieved by a workflow and explain the difference to the real measured grid execution time based on a hierarchy of performance overheads for grid computing. We describe how to systematically measure and compute the overheads from individual activities to larger workflow regions and adjust well-known parallel processing metrics to the scope of grid computing, including speedup and efficiency. We present a distributed online tool for computing and analyzing the performance overheads in real time based on event correlation techniques and introduce several performance contracts as quality-of-service parameters to be enforced during the workflow execution beyond traditional best effort practices. We illustrate our method through postmortem and online performance analysis of two real-world workflow applications executed in the Austrian grid environment.     

Differences in safety belt use by race

The purpose of the study was to identify daytime differences in safety belt use by race. Safety belt use was investigated in a direct observation survey of drivers and front-outboard passengers throughout Michigan. Data were weighted to calculate statewide safety belt use rates by race. Race was assessed visually by trained observers. The study showed that motor vehicle occupants identified as Black had significantly lower safety belt use than those occupants identified as White or Other.     

Driver hand-held mobile phone use and safety belt use

The purposes of the study were to identify hand-held mobile phone use trends for Michigan and to compare safety belt use between users and nonusers. Mobile phone and safety belt use was investigated by a direct observation survey of drivers at intersections in Michigan. Data were weighted to calculate mobile phone use and safety belt use rates statewide. The study showed 2.7% of Michigan drivers were using a mobile phone at any given daylight time. Safety belt use of current mobile phone users was significantly lower than those not using mobile phones.