Objective Stream processing applications process high-volume, continuous feeds from live data sources, employ data-in-motion analytics to analyze these feeds, and produce near real-time results with low latency. With the explosion in the amount of data available as live feeds, stream computing has found wide applications in areas ranging from telecommunications to health-care to cyber-security. The high volume of the data to be processed, the velocity at which the results need to be produced, and the variety of the data sources involved make stream processing applications unique and challenging. One of the major limitations of existing stream processing middleware is their inability to take advantage of parallelism opportunities that exist in stream processing applications, in order to scale in the presence of additional resources and workload. This often requires manual intervention by the application developers to specify what is 'safe' to parallelize and/or how much parallelization is 'profitable'. Yet another challenge is to dynamically adapt to the changes in workload and resource availability. We propose system-level techniques that address these challenges via 'transparent' and 'elastic' scaling. The transparent nature of the scaling means that the application developers do not need to specify what parts of the application is safe to parallelize, and instead this information will be derived through automatic analysis.The elastic nature of the scaling means that the level of parallelism is dynamically adjusted as resource and workload availability changes. Furthermore, in the presence of multiple kinds of parallelism as well as multiple instances of application segments that can benefit from these, we propose techniques to effectively manage resources in order to maximize application performance. Fields of science engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsnatural sciencescomputer and information sciencescomputer security Programme(s) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Topic(s) FP7-PEOPLE-2012-CIG - Marie-Curie Action: "Career Integration Grants" Call for proposal FP7-PEOPLE-2012-CIG See other projects for this call Funding Scheme MC-CIG - Support for training and career development of researcher (CIG) Coordinator BILKENT UNIVERSITESI VAKIF EU contribution € 100 000,00 Address ESKISEHIR YOLU 8 KM 06800 Bilkent Ankara Türkiye See on map Region Batı Anadolu Ankara Ankara Activity type Higher or Secondary Education Establishments Administrative Contact Cevdet Aykanat (Prof.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data