Supersymmetric QCD on the Lattice: Fine-Tuning of the Yukawa Couplings

We determine the fine-tuning of the Yukawa couplings of supersymmetric QCD, discretized on a lattice. We use perturbation theory at one-loop level. The Modified Minimal Subtraction scheme ($\overline{{\rm MS}}$) is employed; by its definition, this scheme requires perturbative calculations, in the continuum and/or on the lattice. On the lattice, we utilize the Wilson formulation for gluon, quark and gluino fields; for squark fields we use na\"ive discretization. The sheer difficulties of this study lie in the fact that different components of squark fields mix among themselves at the quantum level and the action's symmetries, such as parity and charge conjugation, allow an additional Yukawa coupling. Consequently, for an appropriate fine-tuning of the Yukawa terms, these mixings must be taken into account in the renormalization conditions. All Green's functions and renormalization factors are analytic expressions depending on the number of colors, $N_c$, the number of flavors, $N_f$, and the gauge parameter, $\alpha$, which are left unspecified. Knowledge of these renormalization factors is necessary in order to relate numerical results, coming from nonperturbative studies, to the renormalized, ``physical" Green's functions of the theory.Comment: 14 pages, 2 figure

A Survey on Automatic Parameter Tuning for Big Data Processing Systems

Big data processing systems (e.g., Hadoop, Spark, Storm) contain a vast number of configuration parameters controlling parallelism, I/O behavior, memory settings, and compression. Improper parameter settings can cause significant performance degradation and stability issues. However, regular users and even expert administrators grapple with understanding and tuning them to achieve good performance. We investigate existing approaches on parameter tuning for both batch and stream data processing systems and classify them into six categories: rule-based, cost modeling, simulation-based, experiment-driven, machine learning, and adaptive tuning. We summarize the pros and cons of each approach and raise some open research problems for automatic parameter tuning.Peer reviewe

Stubby: A Transformation-based Optimizer for MapReduce Workflows

There is a growing trend of performing analysis on large datasets using workflows composed of MapReduce jobs connected through producer-consumer relationships based on data. This trend has spurred the development of a number of interfaces--ranging from program-based to query-based interfaces--for generating MapReduce workflows. Studies have shown that the gap in performance can be quite large between optimized and unoptimized workflows. However, automatic cost-based optimization of MapReduce workflows remains a challenge due to the multitude of interfaces, large size of the execution plan space, and the frequent unavailability of all types of information needed for optimization. We introduce a comprehensive plan space for MapReduce workflows generated by popular workflow generators. We then propose Stubby, a cost-based optimizer that searches selectively through the subspace of the full plan space that can be enumerated correctly and costed based on the information available in any given setting. Stubby enumerates the plan space based on plan-to-plan transformations and an efficient search algorithm. Stubby is designed to be extensible to new interfaces and new types of optimizations, which is a desirable feature given how rapidly MapReduce systems are evolving. Stubby's efficiency and effectiveness have been evaluated using representative workflows from many domains.Comment: VLDB201

Automatic Performance Tuning for Distributed Data Stream Processing Systems

Peer reviewe

Speedup Your Analytics : Automatic Parameter Tuning for Databases and Big Data Systems

Database and big data analytics systems such as Hadoop and Spark have a large number of configuration parameters that control memory distribution, I/O optimization, parallelism, and compression. Improper parameter settings can cause significant performance degradation and stability issues. However, regular users and even expert administrators struggle to understand and tune them to achieve good performance. In this tutorial, we review existing approaches on automatic parameter tuning for databases, Hadoop, and Spark, which we classify into six categories: rule-based, cost modeling, simulation-based, experiment-driven, machine learning, and adaptive tuning. We describe the foundations of different automatic parameter tuning algorithms and present pros and cons of each approach. We also highlight real-world applications and systems, and identify research challenges for handling cloud services, resource heterogeneity, and real-time analytics.Peer reviewe

MULTI-WEAR: A Multi-Wearable Platform for Enhancing Mobile Experiences

The uptake of wearable technology suggests that the time is ripe to explore new opportunities for improving mobile experiences. Apps, however, are not keeping up with the pace of technological advancement because wearables are treated as standalone devices, although their individual capabilities better classify them as peripherals with complementary roles. We foresee that the next generation of apps will orchestrate multiple wearable devices to enhance mobile user experiences. However, currently there is limited support for combining heterogeneous devices. This paper introduces Multi-Wear, a platform to scaffold the development of apps that span multiple wearables. It demonstrates experimentally how MULTI-WEAR can help bring changes to mobile apps that go beyond conventional practices

Port-2-Port Communication Enhancing Short Sea Shipping Performance: The Case Study of Cyprus and the Eastern Mediterranean

The sustainability of Short Sea Shipping (SSS) is central to a clean, safe, and efficient European Union (EU) transport system. We report on key challenges for advancing reliability, quality, and safety, and removing unnecessary costs and delays at SSS hubs, with a particular focus on Cyprus and the Eastern Mediterranean. Specifically, we consider the effect of port-2-port (P2P) communication on port efficiency by investigating the factors influencing the various waiting times at the Port of Limassol, both from a qualitative and a quantitative perspective. The qualitative results are based on the views of key stakeholders involved in the port call process. The quantitative analysis relies on data from over 8000 port calls during 2017&ndash 2018, which are analyzed with respect to ship type, port of origin, and shipping agent. The calculated Key Performance Indicators (KPIs) include arrival punctuality, berth waiting, and berth utilization. The analysis clearly reveals considerable variation in agent performance regarding the KPIs, suggesting a lack of attention to the social aspect of a port&rsquo s socio-technical system. We propose measures for improving agent performance based on the principles of Port Collaborative Decision Making (PortCDM), including P2P communication, data sharing and transparency among all involved in a port call process including the agents, and open dissemination of agent-specific KPIs. Document type: Articl

Enhancing Virtual Reality Systems with Smart Wearable Devices

The proliferation of wearable and smartphone devices with embedded sensors has enabled researchers and engineers to study and understand user behavior at an extremely high fidelity, particularly for use in industries such as entertainment, health, and retail. However, identified user patterns are yet to be integrated into modern systems with immersive capabilities, such as VR systems, which still remain constrained by limited application interaction models exposed to developers. In this paper, we present SmartVR, a platform that allows developers to seamlessly incorporate user behavior into VR apps. We present the high-level architecture of SmartVR, and show how it facilitates communication, data acquisition, and context recognition between smart wearable devices and mediator systems (e.g., smartphones, tablets, PCs). We demonstrate SmartVR in the context of a VR app for retail stores to show how it can be used to substitute the requirement of cumbersome input devices (e.g., mouse, keyboard) with more natural means of user-app interaction (e.g., user gestures such as swiping and tapping) to improve user experience