ABSTRACT
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 Fog computing, Cloud computing, and Internet of Things.
- L. Aniello, R. Baldoni, and L. Querzoni. Adaptive online scheduling in Storm. In Proc. of ACM DEBS '13, pages 207--218, 2013. Google ScholarDigital Library
- V. Cardellini, V. Grassi, F. Lo Presti, and M. Nardelli. Distributed QoS-aware scheduling in Storm. Technical Report DICII RR-15.7, Univ. Roma Tor Vergata, 2015. www.ce.uniroma2.it/publications/RR-15.7.pdf.Google ScholarDigital Library
- F. Dabek, R. Cox, F. Kaashoek, and R. Morris. Vivaldi: A decentralized network coordinate system. SIGCOMM Comput. Commun. Rev., 34(4), 2004. Google ScholarDigital Library
- T. Heinze, L. Aniello, L. Querzoni, and Z. Jerzak. Cloud-based data stream processing. In Proc. of ACM DEBS '14, pages 238--245, 2014. Google ScholarDigital Library
- J. Kephart and D. Chess. The vision of autonomic computing. IEEE Computer, 36(1):41--50, Jan. 2003. Google ScholarDigital Library
- P. Pietzuch et al. Network-aware operator placement for stream-processing systems. In Proc. of IEEE ICDE '06, 2006. Google ScholarDigital Library
- J. Xu, Z. Chen, J. Tang, and S. Su. T-Storm: Traffic-aware online scheduling in Storm. In Proc. of IEEE ICDCS '14, pages 535--544, June 2014. Google ScholarDigital Library
Index Terms
- Distributed QoS-aware scheduling in storm
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