Networking
a network is essentially a bunch of computer or internet devices that are connected with wires so they can communicate
This network, however, will take a long time to have A comunicate with G. So a network that will work faster is shown below. There are different benefits to each as well, the first one takes less resources, but if one of the wires breaks, the whole comunication fails. But wih the second one, it takes a lot of resources, but if one wire fails, the comunication will still work. This second network in this case is fault tolerent.
popcorn hack 1
Is this network fault tolerent? If not, how can you make this network fault tolerant?
No, add one between tampa and oakland
Redundancy
The Internet is fault tolerant and has been made to withstand errors or problems that may occur. It does this by using redundancy. Redundancy is the inclusion of extra components in order to mitigate the failure of one part of the system. One method of to achieve this is having multiple paths between connected devices allowing transfers to have alternative routes. If a route fails the data will be sent down a different path. Fault tolerance allows users to use a network even if there are system failures. One example where redundancy wasn’t present was the backend during the night at the museum. The pathway to transfer data likely broke, and there was no redundancy to allow for an alternative path.
Popcorn Hack #2
What would make this network fault-tolerant. A
What is Computing?
In simple terms: Computing is the use or operation of computers. To elaborate, computing includes designing and building hardware and software systems for a wide range of purposes: processing structuring, and managing various kinds of information, doing scientific studies using computers, making computer systems behave intelligently, creating and using communications and entertainment media, finding and gathering information relevant to any particular purpose, and so on.
College Board Essential Knowlege
- Sequential compututing is a computational model where operations are performed one at a time in a specific order. This method is very easy to manage and implement, but it can be very slow and recorce intesive.
- Parallel computing is a computational model where the program is broken into multiple smaller parts, so some of them can be computed simaltaneously. This method of computing has alot more risks, and is more difficult to manage, however it is much faster than sequential computing.
- Distributed compututing is another computational model where multiple devices are used to run program. This can increase computing power, while not comsoming many resorces.
- Efficiency of of models can be determined by the time they take to complete a task
Sequential Computing
- The computer works on one task at a time. Reasons for this could be old or bad harware (fewer CPUs)
- Each task is dependant on the tast before it.
- Execution time equals the sum of time it take for each of the individual tasks to run
- Think of Sequential Computing like computing items one at a time on a conveyer belt.
Parallel Computing
- Parallel computing schedules tasks to run at the same time
- Normally all done on a single computer
- Contains a Sequential portion along with a Parallel portion.
- Intensive on resources, so requires more advanced and newer hardware
- Usually much faster than sequential, and can scale a lot easier.
- Execution time equals the length of the longest task.
Distibuted Computing
- Sending tasks to other computors to reduce load
- Is a mix of sequential and parallel computing
- Requires a network to send tasks
- Can take a longer amount of time, based on network and waiting for responces from other computers
Popcorn Hack #3: Sequential, Parallel, or Distributed?
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A small business collects data from daily operations, such as sales, transactions and customer feedback. The owner watch to perform monthly data analysis for his business. What form of computing would best to handle this situation? Sequential
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A company wants to run a web search engine that will receive and process user requests from a data base.
Distributed
- A meteorological institute wants to run a high resolution weather solution to predict weather patterns in real time. This simulations will require vast amouts of data from various sources such as satilite imagrey and historical weather data.
Parallel Computing