Autoscaling is a task of major importance in the cloud computing domain as it directly affects
both operating costs and customer experience. Although there has been active research in …

Worldwide sensor streams are expanding continuously with unbounded velocity in volume,
and for this acceleration, there is an adaptation of large stream data processing system from …

Apache Spark is an in-memory analytic framework that has been adopted in the industry and
research fields. Two memory managers, Static and Unified, are available in Spark to allocate …

This paper explores automatic heap sizing where developers let the frequency of GC
expressed as a target overhead of the application's CPU utilisation, control the size of the …

Java is the backbone of widely used big data frameworks, such as Apache Spark, due to its
productivity, portability from JVM-based execution, and support for a rich set of libraries …

Garbage collection plays a vital role in Java automatic memory management by freeing up
memory that is no longer in use by applications. Selecting the optimal Garbage Collector …

In the rapidly evolving landscape of application programming interfaces (APIs), GraphQL
has emerged as a potent query language, known for its flexibility and efficiency. However, as …

Data-intensive science (DIS) has experienced a significant boom in the past decade. The
emerging technologies of data-intensive services and infrastructures contribute to DIS's …

Serverless computing, or more specifically, Function as a Service (FaaS), offers the ability for
software developers to quickly deploy their applications to the public without worrying about …

With the development of next-generation sequencing (NGS), DNA/RNA sequencing has
become cheaper and more efficient. Today, a whole human genome can be sequenced …