MIDDLEWARE

The quality of machine learning (ML) and deep learning (DL) models are very sensitive to many different adjustable parameters that are set before training even begins, commonly called hyperparameters. Efficient hyperparameter exploration is of great ...

Major cloud computing operators provide powerful monitoring tools to understand the current (and prior) state of the distributed systems deployed in their infrastructure. While such tools provide a detailed monitoring mechanism at scale, they also pose ...

High performance computing (HPC) applications, such as metagenomics and other big data systems, need to store and analyze huge volumes of semi-structured data. Such applications often rely on NoSQL-based datastores, and optimizing these databases is a ...

Rivulet is a fault-tolerant distributed platform for running smart-home applications; it can tolerate failures typical for a home environment (e.g., link losses, network partitions, sensor failures, and device crashes). In contrast to existing cloud-...

Mobile apps make extensive use of GPUs on smartphones and tablets to access Web content. To support pervasive Web content, we introduce three key OS techniques for binary graphics compatibility necessary to build a real-world system to run iOS and ...

The rapid adoption of smartphones with different types of advanced sensors has led to an increasing trend in the usage of mobile crowdsensing applications, e.g., to create hyper-local weather maps. However, the high energy consumption of crowdsensing, ...

Onboarding network functions onto current clouds requires labor-intensive configuration of the virtual environment. Developers need to dimension the resources available to each virtual machine such as CPU and memory, define thresholds for scaling ...

Data analytic applications built upon big data processing frameworks such as Apache Spark are an important class of applications. Many of these applications are not latency-sensitive and thus can run as batch jobs in data centers. By running multiple ...

Developers use Machine Learning (ML) platforms to train ML models and then deploy these ML models as web services for inference (prediction). A key challenge for platform providers is to guarantee response-time Service Level Agreements (SLAs) for ...

Traditionally, active storage techniques have been proposed to move computation tasks to storage nodes in order to exploit data locality. However, we argue in this paper that active storage is ill-suited for cloud storage for two reasons: 1. Lack of ...

Multipath TCP enables remarkable optimizations for throughput, load balancing, and mobility in today's networks. The design space of Multipath TCP scheduling, i.e., the application-aware mapping of packets to paths, is largely unexplored due to its ...

Big Data applications suffer from unpredictable and unacceptably high pause times due to bad memory management (Garbage Collection, GC) decisions. This is a problem for all applications but it is even more important for applications with low pause time ...

Distributed Complex Event Processing (DCEP) is a paradigm to infer the occurrence of complex situations in the surrounding world from basic events like sensor readings. In doing so, DCEP operators detect event patterns on their incoming event streams. ...

We investigate the use of content-based publish/subscribe for data dissemination in large-scale applications with expressive filtering requirements. In particular, we focus on top-k subscription filtering, where a publication is delivered only to the k ...

Approximate computing aims for efficient execution of workflows where an approximate output is sufficient instead of the exact output. The idea behind approximate computing is to compute over a representative sample instead of the entire input dataset. ...

The exploitation of user search queries by search engines is at the heart of their economic model. As consequence, offering private Web search functionalities is essential to the users who care about their privacy. Nowadays, there exists no satisfactory ...

Web applications hosted on the cloud are exposed to cyberattacks and can be compromised by HTTP requests that exploit vulnerabilities. Platform as a Service (PaaS) offerings often provide a backup service that allows restoring application state after a ...

The wide adoption of SMP virtual machines (VMs) and resource consolidation present challenges to efficiently executing multi-threaded programs in the cloud. An important problem is the semantic gaps between the guest OS and the hypervisor. The well-...

Derivative clouds, light weight application containers provisioned in virtual machines, are becoming viable and cost-effective options for infrastructure and software-based services. Ubiquitous dynamic memory management techniques in virtualized systems ...

Disaster Recovery (DR) is a crucial feature to ensure availability and data protection in modern information systems. A common DR approach requires the replication of services in a set of virtual machines running in the cloud as backups. This leads to ...