Tuesday, April 24, 2018

Software-Defined Data Services: Interoperable and Network-Aware Big Data Executions

Today I presented my work titled "Software-Defined Data Services: Interoperable and Network-Aware Big Data Executions" at the Fifth International Conference on Software Defined Systems (SDS), in UPC Barcelona. This is my third time in Barcelona. However, this is the first time I am on my own here without my friends, as my previous visits were for the EMDC and EMJD-DC events in 2013 and 2015. This is my 4th time attending an SDS conference consecutively. 

I have attended the SDS'17 (Valencia, Spain), SDS'16 (Berlin, Germany), and SDS'15 (Tempe, AZ, USA) before. I have only missed the first installment of SDS (SDS'14), as I was doing my MSc those days, and my topic was not related to SDS. SDS started as a workshop co-located with IC2E in 2014, and promoted as a symposium in 2016. It graduated as a conference on its own in 2017.

Abstract: Services that access or process a large volume of data are known as data services. Big data frameworks consist of diverse storage media and heterogeneous data formats. Through their service-based approach, data services offer a standardized execution model to big data frameworks. Software-Defined Networking (SDN) increases the programmability of the network, by unifying the control plane centrally, away from the distributed data plane devices. In this paper, we present Software-Defined Data Services (SDDS), extending the data services with the SDN paradigm. SDDS consists of two aspects. First, it models the big data executions as data services or big services composed of several data services. Then, it orchestrates the services centrally in an interoperable manner, by logically separating the executions from the storage. We present the design of an SDDS orchestration framework for network-aware big data executions in data centers. We then evaluate the performance of SDDS through microbenchmarks on a prototype implementation. By extending SDN beyond data centers, we can deploy SDDS in broader execution environments.

This paper received the Best Paper Award at the SDS 2018!

Please read more about this news at the INESC-ID web site.

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