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How can you maintain network performance with low-bandwidth clients?

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Network performance is a crucial factor for any computer engineering project that involves client-server communication. However, not all clients have the same bandwidth capacity, and some may experience slow or unreliable connections. How can you maintain network performance with low-bandwidth clients? Here are some tips and techniques that you can apply to your network engineering challenges.

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Sandeep S.

Advisor, Thought Leader, Investor, Strategy (Personal Account)

1 Optimize data compression

One of the simplest ways to improve network performance with low-bandwidth clients is to reduce the amount of data that needs to be transferred between the server and the client. Data compression is a technique that reduces the size of data by removing redundant or unnecessary information, such as white spaces, comments, or repeating patterns. Data compression can be applied to different types of data, such as text, images, audio, or video. However, data compression also has some trade-offs, such as increased processing time, reduced quality, or compatibility issues. Therefore, you need to choose the appropriate compression algorithm and level for your data type and network requirements.

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James Rogers

Showed how Planck's constant h is a composite number of ((length)(mass))/c, Gravitational constant is (length)/(mass), Boltzmann's constant is ((length)(mass))/(temp), and epsilon_0 is (charge)^2/ ((length)(mass))
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If you difference (diff) a status message with the last message you sent before you compress it, you can save kb of data. Often you are sending most of the data without change, or just with small changes. If you get an error back you need to send a full message and then start diff-ing again after that. The other side just saves the last message you sent and applies the diff, making sure a checksum works for the message. If the checksum fails, ask for the full status. You can keep a mb sized file synchronized over a 9600 baud modem if all that is changing is a few sentences at a time. Like someone is typing.

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2 Use caching and prefetching

Another way to enhance network performance with low-bandwidth clients is to minimize the number of requests and responses that need to be exchanged between the server and the client. Caching and prefetching are techniques that store data locally on the client side, so that the client can access it faster and without sending a request to the server. Caching is the process of storing data that has been previously requested or received by the client, such as web pages, images, or files. Prefetching is the process of downloading data that the client is likely to request in the future, such as links, resources, or updates. Caching and prefetching can reduce network latency, bandwidth consumption, and server load. However, they also have some drawbacks, such as storage space, freshness, or accuracy. Therefore, you need to implement caching and prefetching policies that balance these factors and suit your network needs.

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Sandeep S.

Advisor, Thought Leader, Investor, Strategy (Personal Account)
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Content Delivery Networks excel in caching and prefetching. Edge caching, coupled with data compression, is highly effective in low-bandwidth areas for streaming services. Time to Live (TTL) in HTTP defines data validity, demanding higher edge capacities for longer TTL. Cloud vendors use 'eventual consistency' to sync large data geographies, adaptable to low-bandwidth zones using refresh techniques. Prioritizing data becomes crucial. 'Network slicing,' common in 5G, isolates data transfer, ensuring minimal user impact. (My Original write up was more than 1000 words and has been condensed using AI content creator)

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James Rogers

Showed how Planck's constant h is a composite number of ((length)(mass))/c, Gravitational constant is (length)/(mass), Boltzmann's constant is ((length)(mass))/(temp), and epsilon_0 is (charge)^2/ ((length)(mass))
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You want to make this a layer/library that wraps your function calls at the higher level so it doesn't make your code complicated. All the complexity is hidden in the cache/prefetch layer. And by doing it this way it makes it trivial to turn off caching for high speed low latency connections.

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Thomas Treml

Cloud CTO Public Sector bei Microsoft mit Expertise in ESG und Corporate Sustainability
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Die richtige Plazierung der Content Delivery Network Knoten/ Cluster ist hier in diesem Zusammenhang der entscheidende Erlfogsfaktor

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3 Implement adaptive streaming

A specific type of data that poses a challenge for network performance with low-bandwidth clients is video. Video streaming is a popular and demanding application that requires high bandwidth and low latency to deliver smooth and high-quality playback. However, not all clients have the same network conditions and preferences, and some may experience buffering, stuttering, or pixelation. Adaptive streaming is a technique that adjusts the video quality and bitrate according to the client's bandwidth and device capabilities. Adaptive streaming works by dividing the video into segments and encoding them at different quality levels. The server then sends the appropriate segment to the client based on the available bandwidth and feedback from the client. Adaptive streaming can improve user experience, network efficiency, and resource utilization. However, it also requires more complex encoding, decoding, and switching algorithms and protocols.

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4 Apply load balancing and scaling

Another factor that affects network performance with low-bandwidth clients is the server capacity and availability. If the server is overloaded or unavailable, it may not be able to handle all the requests and responses from the clients, resulting in delays, errors, or failures. Load balancing and scaling are techniques that distribute the workload and resources among multiple servers or instances, so that no single server becomes a bottleneck or a point of failure. Load balancing is the process of assigning requests to different servers based on criteria such as load, location, or priority. Scaling is the process of adding or removing servers or instances based on demand, performance, or cost. Load balancing and scaling can improve network reliability, availability, and resilience. However, they also introduce more complexity, overhead, and coordination challenges.

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James Rogers

Showed how Planck's constant h is a composite number of ((length)(mass))/c, Gravitational constant is (length)/(mass), Boltzmann's constant is ((length)(mass))/(temp), and epsilon_0 is (charge)^2/ ((length)(mass))
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There are also methods using epoll() and sendfile() that can allow a server program to handle 10K client connections on modest hardware. These don't have the overhead of select() style network functions and the kernel handles the actual data sending on the sendfile() calls, cutting your application out of the loop for sending data from the hard disk. Of course these much improved functions are only supported on modern "UNIX" style operating systems. You can use these servers for sending large files from disk for game/program updates or level loading. You can have a different group of servers that stores game status and shares the updates with many clients. The OS these servers use don't have to match the bulk file send servers.

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5 Monitor and analyze network performance

The final tip to maintain network performance with low-bandwidth clients is to monitor and analyze the network behavior and performance metrics. Monitoring and analyzing network performance can help you identify and troubleshoot network issues, such as congestion, packet loss, latency, or throughput. It can also help you optimize and improve network design, configuration, and operation, such as routing, security, or quality of service. To monitor and analyze network performance, you need to use tools and methods that can collect, store, process, and visualize network data, such as logs, packets, flows, or events. Some examples of network performance monitoring and analysis tools are Wireshark, Ping, Traceroute, or Nmap.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Sandeep S.

Advisor, Thought Leader, Investor, Strategy (Personal Account)
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Few other considerations in low bandwidth areas include creation of private network bubbles which allow creation of small local networks for carrying data over smaller lengths with central hub to perform processing at edge. This technique is especially useful in Defense Sector, Border Protection, Disaster Areas etc. Recent innovations in areas of 5G furthers this technique. During edge processing, a decision matrix needs to be developed which will allow carrying only meaningful and prioritized data over longer geographies over SATCOM. At edge processing, please consider removing digital exhaust out of the system. It has been seen that high % of the data generated at the edge is more for observability purposes than actual business data.

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How can you maintain network performance with low-bandwidth clients?

1

2

3

4

5

6

1 Optimize data compression

2 Use caching and prefetching

3 Implement adaptive streaming

4 Apply load balancing and scaling

5 Monitor and analyze network performance

6 Here’s what else to consider

Computer Engineering

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How can you maintain network performance with low-bandwidth clients?

1

2

3

4

5

6

1 Optimize data compression

2 Use caching and prefetching

3 Implement adaptive streaming

4 Apply load balancing and scaling

5 Monitor and analyze network performance

6 Here’s what else to consider

Computer Engineering

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