Archive: 2017-08

The first blog entry in this series introduced the basic concepts of multicore processing and virtualization, highlighted their benefits, and outlined the challenges these technologies present. This second post will concentrate on multicore processing, where I will define its various types, list its current trends, examine its pros and cons, and briefly address its safety and security ramifications.

Multicore processing and virtualization are rapidly becoming ubiquitous in software development. They are widely used in the commercial world, especially in large data centers supporting cloud-based computing, to (1) isolate application software from hardware and operating systems, (2) decrease hardware costs by enabling different applications to share underutilized computers or processors, (3) improve reliability and robustness by limiting fault and failure propagation and support failover and recovery, and (4) enhance scalability and responsiveness through the use of actual and virtual concurrency in architectures, designs, and implementation languages. Combinations of multicore processing and virtualization are also increasingly being used to build mission-critical, cyber-physical systems to achieve these benefits and leverage new technologies, both during initial development and technology refresh.

In this introductory blog post, I lay the foundation for the rest of the series by defining the basic concepts underlying multicore processing and the two main types of virtualization: (1) virtualization by virtual machines and hypervisors and (2) virtualization by containers. I will then briefly compare the three technologies and end by listing some key technical challenges these technologies bring to system and software development.

The Department of Defense is increasingly relying on biometric data, such as iris scans, gait recognition, and heart-rate monitoring to protect against both cyber and physical attacks. "Military planners, like their civilian infrastructure and homeland security counterparts, use video-linked 'behavioral recognition analytics,' leveraging base protection and counter-IED operations," according to an article in Defense Systems. Current state-of-the-art approaches do not make it possible to gather biometric data in real-world settings, such as border and airport security checkpoints, where people are in motion. This blog post presents the results of exploratory research conducted by the SEI's Emerging Technology Center to design algorithms that extract heart rate from video of non-stationary subjects in real time.