7 posts tagged with "Computer Science"

In today’s hyper-connected world, the demand for efficient, reliable, and scalable data transmission across networks is ever-increasing. Traditional approaches to data communication rely heavily on forwarding techniques, where intermediate nodes simply relay data packets. While effective in many scenarios, these methods struggle with packet loss, bandwidth constraints, and dynamic network topologies. Enter Random Linear Network Coding (RLNC)—a revolutionary paradigm that leverages coding theory to enhance network performance.

Richard W. Hamming’s The Art of Doing Science and Engineering: Learning to Learn is more than a guide to technical disciplines; it’s a philosophical treatise on how to think effectively and pursue meaningful work. Hamming, known for his groundbreaking contributions to mathematics and computer science, offers insights that blend practical tools with timeless wisdom for anyone striving to make a difference in their field. In this post, I’ve distilled some of the book’s most impactful lessons and tools.

Erasure coding is a critical method used in data storage systems to enhance data durability and availability, surpassing traditional techniques like mirroring in storage efficiency. This blog post explores what erasure coding is, how it operates, and its significant role in modern storage environments.

In today's digital landscape, the ability to collaborate in real-time on applications like Google Docs, collaborative coding platforms, and online gaming environments is not just a convenience but a necessity. One of the fundamental technologies enabling this seamless, concurrent user interaction without the typical latency or conflict issues is the Conflict-Free Replicated Data Type (CRDT).

In graph theory, finding the shortest paths from a single source to all other vertices in a graph is a crucial problem that extends beyond theoretical computer science to practical applications in network routing, urban planning, and optimization. Traditionally addressed by sequential algorithms like Dijkstra’s or Bellman-Ford, the rise of parallel computing has prompted the development of methods that use multiple processors to manage larger graphs efficiently. This blog post explores the key concepts and advancements in parallel single-source shortest path (SSSP) algorithms.

So, I recently got my hands on M. Mitchell Waldrop's Dream Machine, and let me tell you, it's one heck of a ride through computing history. This book doesn't just talk about the past—it dives deep into the collaborative efforts, ethical dilemmas, and the sheer brilliance that have shaped the digital world we live in today.

Today I learned about cuckoo filters, a data structure used in computer science for probabilistic set membership queries. Cuckoo filters are similar to Bloom filters but offer more flexibility by allowing for deletion of items from the filter while maintaining good space efficiency.