CST 334 Week 8

    This final week in CST 334, we covered persistence and its importance both in the context of operating systems and as a student. For operating systems, persistence is crucial for maintaining data and state beyond the life of a process. It is achieved by storing data in non-volatile memory, like hard drives or SSDs, ensuring that information survives even after a system shuts down or restarts.

    As an online student, persistence is not just about data storage; it’s also about staying committed to completing the course and navigating the challenges that come with balancing my responsibilities at school and work. Managing deadlines and projects in both areas can be overwhelming, but I’ve learned that I can handle it if I stay focused. I’ve also realized that I can sometimes be too hard on myself. In the past, and honestly still today, I tend to be unforgiving when I miss a task or forget an assignment. However, I’m slowly learning that occasional setbacks aren’t the end of the world, and I can persist through these challenges without letting them derail my progress.

Comments

Post a Comment

Popular posts from this blog

CST 334 Week 4

     This week in our course, we focused on memory virtualization and memory management. In our lab, we concentrated on FIFO (First-In-First-Out), a page replacement strategy that uses a queue to manage page entries.      In FIFO, pages are loaded into memory and placed in a queue. When a page needs to be replaced, the oldest page in the queue is evicted. This approach can lead to inefficient page replacement because even if a page has been recently used, it will still be evicted if it has been in memory the longest.      In contrast, LRU (Least Recently Used) tracks the usage history of pages. LRU replaces the page that hasn't been used for the longest period of time. Because it takes into account the actual usage patterns of pages, LRU typically provides better performance, whereas FIFO only considers the order in which pages were loaded into memory.
Read more

CST363 Week 1

1. Relational database tables and spreadsheets look similar with both having rows and columns.  What are some important differences between the two?   Relational databases and spreadsheets might look similar because they both have rows and columns, but they are quite different in how they manage data. Databases can handle lots of data and keep it organized using rules like unique IDs and links between different tables. They’re built to deal with many users working at the same time and can keep track of complex relationships between data. Spreadsheets are great for smaller tasks and simpler data, but they can get messy with a lot of information and don’t handle multiple users very well. They also don’t have the same level of data protection or advanced searching features that databases offer.   2. Installing and configuration a database and learning how to use it is more complicated that just reading and writing data to a file.  What are some important reasons tha...
Read more

CST 334 Week 7

     This week, we covered topics including I/O devices, disk drives, files and directories, file systems, and RAIDs. RAID is a storage technology that combines multiple physical disks into one logical unit to enhance performance, data redundancy, or both. RAID 1, also known as mirroring, duplicates data across two or more disks, ensuring that if one disk fails, the data remains intact on the other. This provides high data reliability but requires twice the storage capacity. RAID 4, on the other hand, uses a dedicated disk for parity, with parity information calculated using XOR, and distributed across the array. This parity allows for data recovery in the event of a disk failure. While RAID 4 offers better storage efficiency than RAID 1, it may suffer from performance bottlenecks, as the parity calculations are handled by a single disk.
Read more