Hadoop and Spark are widely used distributed processing frameworks for large-scale data
processing in an efficient and fault-tolerant manner on private or public clouds. These big …

The problem of distributed consensus has played a major role in the development of
distributed data management systems. This includes the development of distributed atomic …

In this paper, we propose Dynamic Paxos (DPaxos), a Paxos-based consensus protocol to
manage access to partitioned data across globally-distributed datacenters and edge nodes …

Emerging edge applications require both a fast response latency and complex processing.
This is infeasible with-out expensive hardware that can process complex operations-such as …

This article describes the methods used to integrate a Bluetooth based ECG system into a T-
Shirt. Some of the components are integrated into the garment, while the flexible electronic …

With the rise of scalable, distributed web applications, latency has become a fundamental
challenge for cloud data management. The delays caused by accessing data from cloud …

Global-scale data management (GSDM) empowers systems by providing higher levels of
fault-tolerance, read availability, and efficiency in utilizing cloud resources. This has led to …

Caching-Technologie kann anhand mehrerer Dimensionen kategorisiert werden, wie in
Abb. 5.1 dargestellt ist. Die erste Dimension ist der Standort des Caches. In diesem Buch …

Caching technology can be categorized by several dimensions as illustrated in Fig. 5.1. The
first dimension is the location of the cache. In this book, we focus on caches relevant for …

From Controlled Data-Center Environments to Open Distributed Environments: Scalable,
Efficient, and Robust Systems with Extended Page 1 University of California Santa Barbara From …