ICT is becoming an enabler for smart city applications by making effective use of various data resources generated daily in an urban environment. Mostly this data is utilised by city authorities for city planning purposes and often citizens become ...

Data analytics has gained more and more focus during recent years and many data processing platforms have been developed. They all provide a powerful but often complex API that users have to learn. Furthermore, results can only be stored or printed, ...

Recently, some distributed stream computing platforms, such as Storm and Spark Streaming, have been developed for processing massive data streams. However, these platforms lack support for higher-level declarative languages and provide only programming ...

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 ...

Large quantities of data are generated continuously over time and from disparate sources such as users, devices, and sensors located around the globe. This results in the need for efficient geo-distributed streaming analytics to extract timely ...

Task migration happens when distributed data processing systems scale in real-time. To handle the task migration process more gracefully, we propose three task migration methods: (i) worker level migration, (ii) executor level migration, and (iii) ...

We present the STORM system to enable spatio-temporal online reasoning and management of large spatio-temporal data. STORM supports interactive spatio-temporal analytics through novel spatial online sampling techniques. Online spatio-temporal aggregation ...

The National Center for Atmospheric Research (NCAR) Weather Research and Forecasting (WRF) model has been employed on the largest yet storm prediction model using real data of over 4 billion points to simulate the landfall of Hurricane Sandy. Using an ...

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 ...

This work describes a system that enables non-commercial communities, e.g. students and researchers, to deploy pre-configured clusters of virtual machines on arbritary cloud computing stacks implementing the Open Cloud Computing Interface (OCCI). As a ...

In network analysis the ability to characterize nodes based on their attributes and surrounding network structure is a fundamental problem. For example, in financial transaction networks, it allows us to identify typical and anomalous behaviour -- ...

We present a software-based solution to the multi-dimensional packet classification problem which can operate at high line speeds, e.g., in excess of 10 Gbps, using high-end multi-core desktop platforms available today. Our solution, called Storm, ...

This paper has put forward the concept of storm magnitude and disaster intensity and designed a kind of new method by quantitative calculation. Storm magnitude is the quantitative index that describes the scale of a storm, and disaster intensity of ...

Modern advanced botnets may employ a decentralized peer-to-peer overlay network to bootstrap and maintain their command and control channels, making them more resilient to traditional mitigation efforts such as server incapacitation. As an alternative ...

Aerosol particles, ozone and carbon monoxide observed from 0-15 km altitude near Darwin (12.41°S, 130.9°E) in northern Australia, during the Aerosol and Chemical Transport in tropIcal conVEction (ACTIVE) campaign from November 2005 to February 2006, ...

A regular EGNOS Test Bed (ESTB) data collecting, 24 h per week, and analysis campaign has been developed by Eurocontrol along 2002 and 2003. During this period a geomagnetic storm was experienced on October 29th-31st 2003, degrading the ESTB performance ...