Storm is a distributed stream processing system that has recently gained increasing interest. We extend Storm to make it suitable to operate in a geographically distributed and highly variable environment such as that envisioned by the convergence of ...

Processing complex queries on unbounded event streams in real-time, is a challenge for many data processing systems. These systems are expected to process data with reduced latency to generate real-time events, and at high throughput to minimize the ...

The DEBS 2014 Grand Challenge targets the monitoring and prediction of energy loads of smart plugs installed in private households. This paper presents details of our middleware solution and efficient median calculation, shows how we address data ...

Phenomena clouds are characterized by nondeterministic, dynamic variations of shapes, sizes, direction, and speed of motion along multiple axes. The phenomena detection and tracking should not be limited to some traditional applications such as oil ...

The ubiquity of sensor data calls for automatic processing to extract valuable information. Realtime Locating Systems (RTLS) provide many parallel position data streams for interacting objects, and event-based systems are the method of choice to analyze ...

Today we are witnessing a dramatic shift toward a data-driven economy, where the ability to efficiently and timely analyze huge amounts of data marks the difference between industrial success stories and catastrophic failures. In this scenario Storm, an ...

In surveillance, sports, finances, etc., distributed event-based systems are used to detect meaningful events with low latency in high data rate event streams. Both known approaches to deal with the predominant out-of-order event arrival at the ...

Financial institutions, acting as financial intermediaries, need to handle numerous information sources and feed them to multiple processing, storage, and display services. This requires filtering and routing, but these feeds are usually provided in ...

Building scalable back-end infrastructures for data-centric applications is becoming important. Applications used in data-centres have complex, multilayer software stacks and are required to scale to a large number of nodes. Today, there is increased ...

In this paper we present a framework for building policy-based autonomic distributed agent systems. The autonomic mechanisms of configuration and recovery are supported through a distributed event processing model and a set of policy enforcement ...