Traditional parallel computing for power management systems has prime challenges such
as execution time, computational complexity, and efficiency like process time and delays in …

A popular unsupervised learning method, known as clustering, is extensively used in data
mining, machine learning and pattern recognition. The procedure involves grouping of …

Traffic accidents have become severe risks as they are one of the causes of enormous
deaths worldwide. Reducing the number of incidents is critical to saving lives and achieving …

One of the most challenging issues in the big data research area is the inability to process a
large volume of information in a reasonable time. Hadoop and Spark are two frameworks for …

In the era of digital media, the rapidly increasing volume and complexity of multimedia data
cause many problems in storing, processing, and querying information in a reasonable time …

Background We are living in an age where data is everywhere and grows up in a very
speedy way. Thanks to sensors, mobile phones and social networks, we can gather a hug …

Network slicing is a powerful tool to harness the full potential of 5G systems. It allows
verticals to own and exploit independent logical networks on top of the same physical …

The emergence of big data processing platforms that can work globally in an integrated
manner and process the huge datasets efficiently has become very significant. A critical …

Big Data is a phenomenon that affects today's world, with new data being generated every
second. Today's enterprises face major challenges from the increasingly diverse data, as …

Data is generated by humans every day via various sources such as Instagram, Facebook,
Twitter, Google, etc at a rate of 2.5 quintillion bytes with high volume, high speed and high …