Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other

Enhancing Spatiotemporal Traffic Prediction through Urban Human Activity Analysis

Traffic prediction is one of the key elements to ensure the safety and convenience of citizens. Existing traffic prediction models primarily focus on deep learning architectures to capture spatial and temporal correlation. They often overlook the underlying nature of traffic. Specifically, the sensor networks in most traffic datasets do not accurately represent the actual road network exploited by vehicles, failing to provide insights into the traffic patterns in urban activities. To overcome these limitations, we propose an improved traffic prediction method based on graph convolution deep learning algorithms. We leverage human activity frequency data from National Household Travel Survey to enhance the inference capability of a causal relationship between activity and traffic patterns. Despite making minimal modifications to the conventional graph convolutional recurrent networks and graph convolutional transformer architectures, our approach achieves state-of-the-art performance without introducing excessive computational overhead.Comment: CIKM 202

OCI-Based Group Communication Support in CORBA

Group communication is a useful mechanism guaranteeing consistency among replicated objects. The existing approaches do not allow transparent plug-in of group communication protocols into CORBA. They either require modification of CORBA or OS, or provide no room for incorporating group communication transport protocols into CORBA. We thus propose a generic group communication framework that allows transparent plug-in of various group communication protocols with no modification of existing CORBA. We extend the open communications interface (OCI) to support interoperability, reusability of existing group communication, and independency on ORB and OS. We also define the group communication inter-ORB protocol (GCIOP) as a group communication instantiation of the general inter-ORB protocol (GIOP) that encapsulates underlying group communication protocols. The proposed scheme can be exploited for fault-tolerant CORBA (FT CORBA)

MetaWeather: Few-Shot Weather-Degraded Image Restoration via Degradation Pattern Matching

Real-world vision tasks frequently suffer from the appearance of adverse weather conditions including rain, fog, snow, and raindrops in captured images. Recently, several generic methods for restoring weather-degraded images have been proposed, aiming to remove multiple types of adverse weather effects present in the images. However, these methods have considered weather as discrete and mutually exclusive variables, leading to failure in generalizing to unforeseen weather conditions beyond the scope of the training data, such as the co-occurrence of rain, fog, and raindrops. To this end, weather-degraded image restoration models should have flexible adaptability to the current unknown weather condition to ensure reliable and optimal performance. The adaptation method should also be able to cope with data scarcity for real-world adaptation. This paper proposes MetaWeather, a few-shot weather-degraded image restoration method for arbitrary weather conditions. For this, we devise the core piece of MetaWeather, coined Degradation Pattern Matching Module (DPMM), which leverages representations from a few-shot support set by matching features between input and sample images under new weather conditions. In addition, we build meta-knowledge with episodic meta-learning on top of our MetaWeather architecture to provide flexible adaptability. In the meta-testing phase, we adopt a parameter-efficient fine-tuning method to preserve the prebuilt knowledge and avoid the overfitting problem. Experiments on the BID Task II.A dataset show our method achieves the best performance on PSNR and SSIM compared to state-of-the-art image restoration methods. Code is available at (TBA).Comment: 12 pages, 6 figure

OCI-Based Group Communication Support in CORBA

Group communication is a useful mechanism guaranteeing consistency among replicated objects. The existing approaches do not allow transparent plug-in of group communication protocols into CORBA. They either require modification of CORBA or OS, or provide no room for incorporating group communication transport protocols into CORBA. We thus propose a generic group communication framework that allows transparent plug-in of various group communication protocols with no modification of existing CORBA. We extend the open communications interface (OCI) to support interoperability, reusability of existing group communication, and independency on ORB and OS. We also define the group communication inter-ORB protocol (GCIOP) as a group communication instantiation of the general inter-ORB protocol (GIOP) that encapsulates underlying group communication protocols. The proposed scheme can be exploited for fault-tolerant CORBA (FT CORBA)