Unit 5
Discussion 1
Distributed programming is a computation method in which software will run on separate cores in multiple networked computers. It is a true parallel computation model because it can provide fully supported computing resources for multitasking. Based on different criteria, distributed programming models can be classified differently. If the term distributed system is defined as “a system consisting of networked computers and communicating through either messaging passing or shared distributed memory to coordinate the software functions to solve a problem or provide a service,” then you can divide that distributed programming into the following two models:
· Shared memory distributed programming
· Message-passing distributed programming
According to the definition of a distributed system, a cloud computing environment is considered a distributed system. Therefore, both the shared memory distributed programming and the message-passing distributed programming can be applied in the cloud. However, if you use cloud computing to conduct large-scale data processing, the existing capabilities of both the shared memory distributed programming or the message-passing distributed programming are not sufficient (Sakr & Gaber, 2014).
Complete the reading assignment, and search the Library and Internet to find and study additional references that discuss the concepts and applications of the distributed programming models. Based on the results of your research, discuss the following question:
· Why are both the shared memory distributed programming and the message-passing distributed programming insufficient when processing the large-scale data in cloud computing environment?
Discussion 2
The CAP theorem was originally proposed by Dr. E. Brewer at a symposium on distributed computing, and he stated that “in any highly distributed data system, there are three commonly desirable properties: consistency, availability, and partition tolerance. However, it is impossible for a system to provide all three properties at the same time” (2000). This theorem was later proven by S. Gilbert and N. Lynch. The CAP theorem has had great impact on the design of distributed systems and services, including distributed database management systems (DDBMS). Web-based applications have posted new requirements that traditional database systems such as SQL-based relational database systems (RDBs) cannot fully satisfy. This has triggered a new type of data storage systems called NoSQL systems to occur and gradually become a dominant alternative solution for data store and management.
One of popular practices among NoSQL data storage systems is based on the CAP theorem to make the trade-off among the three properties. Because the high performance cost of maintaining strong consistency based on the atomicity, consistency, isolation, and durability (ACID) semantics held by RDBs, NoSQL systems often apply the weak consistency model in exchange for the great reduction of performance overhead involved in enforcing strong consistency (Sakr & Gaber, 2014).
Complete the reading assignment, and search the Library and Internet to find and study additional references that discuss the concepts of strong and weak consistency. Based on the results of your research, discuss the following questions:
· Why must a NoSQL data storage system based on the cloud computing environment make trade-offs between consistency and availability?
· Where do the savings on the consistency handling overhead come from in a NoSQL data storage system executing the weak consistency?