GAME-SCORE: Game-based energy-aware cloud scheduler and simulator for computational clouds

Energy-awareness remains one of the main concerns for today's cloud computing (CC) operators. The optimisation of energy consumption in both cloud computational clusters and computing servers is usually related to scheduling problems. The definition of an optimal scheduling policy which does not negatively impact to system performance and task completion time is still challenging. In this work, we present a new simulation tool for cloud computing, GAME-SCORE, which implements a scheduling model based on the Stackelberg game. This game presents two main players: a) the scheduler and b) the energy-efficiency agent. We used the GAME-SCORE simulator to analyse the efficiency of the proposed game-based scheduling model. The obtained results show that the Stackelberg cloud scheduler performs better than static energy-optimisation strategies and can achieve a fair balance between low energy consumption and short makespan in a very short tim

Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

Continuous urbanization and industrialization lead to plenty of rural residents migrating to cities for a living, which seriously accelerated the population hollowing issues. This generated series of social issues, including residential estate idle and numerous vigorous laborers migrating from undeveloped rural areas to wealthy cities and towns. Quantitatively determining the population hollowing characteristic is the priority task of realizing rural revitalization. However, the traditional field investigation methods have obvious deficiencies in describing socio-economic phenomena, especially population hollowing, due to weak efficiency and low accuracy. Here, this paper conceives a novel scheme for representing population hollowing levels and exploring the spatiotemporal dynamic of population hollowing. The nighttime light images were introduced to identify the potential hollowing areas by using the nightlight decreasing trend analysis. In addition, the entropy weight approach was adopted to construct an index for evaluating the population hollowing level based on statistical datasets at the political boundary scale. Moreover, we comprehensively incorporated physical and anthropic factors to simulate the population hollowing level via random forest (RF) at a grid-scale, and the validation was conducted to evaluate the simulation results. Some findings were achieved. The population hollowing phenomenon decreasing gradually was mainly distributed in rural areas, especially in the north of the study area. The RF model demonstrated the best accuracy with relatively higher R2 (Mean = 0.615) compared with the multiple linear regression (MLR) and the geographically weighted regression (GWR). The population hollowing degree of the grid-scale was consistent with the results of the township scale. The population hollowing degree represented an obvious trend that decreased in the north but increased in the south during 2016–2020 and exhibited a significant reduction trend across the entire study area during 2019–2020. The present study supplies a novel perspective for detecting population hollowing and provides scientific support and a first-hand dataset for rural revitalization

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Conception, Implementation and Empirical Evaluation of a Domain-Specific Language for Multi-Agent Traffic and Transport Simulations

Conception and implementation of agent-based simulation programs is a complex task. One of the key problems is the requirement of technical agent-based software engineering expertise on the one hand and professional knowledge of the application domain on the other. Either skill set is rare and only few people possess adequate knowledge of both domains. A joint development of software engineers and domain experts is often impeded by inaccurate communication resulting from the incompatible terminologies of the technical and the application domain. This is especially problematic since every change commences a new development cycle based on inapt communication. Domain-specific languages (DSLs) are a promising approach to overcome this gap. A well-designed concrete syntax can serve as the communicational basis. An expressive meta-model in combination with a concise concrete syntax allows modelling on a more abstract level close to the application domain. Via pre-defined transformations, executable simulation software can be generated from DSL-models. DSLs thus have the potential to increase the quality of the software and at the same time accelerate the entire development process. Realisation of this potential demands a perfectly designed language which in turn renders a proper language evaluation indispensable. However, this crucial step is often neglected by DSL developers. Therefore, there is a general demand for further contributions in this area of language engineering. This thesis presents the development of a DSL for the domain of agent-based traffic simulation and vehicle-routing optimisation together with a comprehensive empirical language evaluation. It depicts how an expressive meta-model was developed and merged with a concise concrete textual syntax. It also presents transformations that allow the generation of executable software for different platforms. Most importantly, it provides empirical evidence that language users with little programming knowledge as well as modellers with advanced software development skills can benefit from the application of the DSL in terms of software quality and development time