A Cyberinfrastructure for Big Data Transportation Engineering

Algorithm Engineering for Big Data

Perhaps the most fundamental challenge implied by advanced applications of big data sets is how to perform the vast amount of required computations sufficiently efficiently. Efficient algorithms are at the heart of this question. But how can we obtain innovative algorithmic solutions for demanding application problems with exploding input sizes using complex modern hardware and advanced algorit...

A Privacy Engineering Framework for Big Data

In the Big Data era, the collection and mining of high-dimensional user data has become a fast growing and common practice by a large number of private and public institutions. In some cases, these institutions share data with third parties without an anonymity preferring user’s consent or awareness, thereby risking his privacy. In other cases, data is released voluntarily by a user not necessa...

A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection

Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....

A New Model for Transportation Problem with Qualitative Data

 In today’s highly competitive market, the pressure on organizations to find a better way to create and deliver value to customers is mounting. The decision involves many quantitative and qualitative factors that may be conflicting in nature. Here, we present a new model for transportation problem with consideration of quantitative and qualitative data. In the model, we quantify the qua...

Software Engineering for Big Data Systems