Data compression system for a backbone network
How does a network backbone work?
A backbone or core network is a part of a computer network which interconnects networks, providing a path for the exchange of information between different LANs or subnetworks.
A backbone can tie together diverse networks in the same building, in different buildings in a campus environment, or over wide areas..
What are the data compression techniques in network security?
What is the compression technique in data compression? There are broadly two types of data compression techniques—lossy and lossless.
In lossy, the insignificant piece of data is removed to reduce the size, while in lossless compression, the data is transformed through encoding, and its size is reduced..
Which network topologies are used in backbone networks?
Bus Topology
This single cable is commonly referred to as a backbone.
Bus topology was used for early 1.
- Base-2, ThinNet, and 1
- Base-5, ThickNet, coaxial cable Ethernet networks
Which type of network media is typically used in backbone networks?
With the emerge of Gigabit Ethernet and 10 Gigabit Ethernet, fiber optic cable is the most appropriate choice for backbone cabling since they provide much higher bandwidth than traditional Cat5, Cat6 or even Cat7 twisted pair copper cables..
- Answer: Unshielded twisted pair cable is extensively used in horizontal & backbone cabling subsystems.
UTP cables are used as ethernet cables and telephone wires for short to medium distances to transfer data and audio signals.
How can we compare the extracted backbone network?
The Internet mapping network has real backbone node data; thus we can compare the extracted backbone network to verify the extraction results on the real backbone network.
The optimal parameters to evaluate the extracted backbone are shown in Figure 5.
,
How does compression ratio affect the performance of backbone networks?
Meanwhile, we define a metric named compression ratio to evaluate the performance of backbone networks, which provides an optimal extraction granularity based on the contributions of degree number and topology connectivity.
,
How does data compression work?
Data compression provides a coding scheme at each end of a transmission link that allows characters to be removed from the frames of data at the sending side of the link and then replaced correctly at the receiving side.
Because the condensed frames take up less bandwidth, we can transmit greater volumes at a time.
,
How to measure the performance of a backbone network?
Measuring the performance of backbones networks needs to exclude the situation of invalid compression ratio.
In the Internet mapping results, the optimal compression ratios of the networks as3356, as4755, as2914, and as7018 are about 0.23, 0.16, 0.08, and 0.035, respectively, as illustrated in Figure 4.
How does compression ratio affect the performance of backbone networks?
Meanwhile, we define a metric named compression ratio to evaluate the performance of backbone networks, which provides an optimal extraction granularity based on the contributions of degree number and topology connectivity
How does data compression work?
Data compression provides a coding scheme at each end of a transmission link that allows characters to be removed from the frames of data at the sending side of the link and then replaced correctly at the receiving side
Because the condensed frames take up less bandwidth, we can transmit greater volumes at a time
How to measure the performance of a backbone network?
Measuring the performance of backbones networks needs to exclude the situation of invalid compression ratio
In the Internet mapping results, the optimal compression ratios of the networks as3356, as4755, as2914, and as7018 are about 0
23, 0 16, 0 08, and 0
035, respectively, as illustrated in Figure 4
×Data compression techniques for backbone networks are methods to reduce the amount of data transmitted over high-speed network links. Some of the compression algorithms supported by Cisco IOS software are Hi/fn Stac LZS, Predictor, and MPPC. Some of the intelligent methods for data compression are convolutional neural network, cyclic neural network, and multilayer sparse automatic encoder. These methods can compress data and images on a per-connection basis or at the network trunk level.,Inspired by the theory of physics field, in this paper,There are no industry-standard compression specifications, but Cisco IOS® software supports several third-party compression algorithms, including Hi/fn Stac Limpel Zif Stac (LZS), Predictor, and Microsoft Point-to-Point Compression (MPPC). These compress data on a per-connection basis or at the network trunk level.Among them, convolutional neural network, cyclic neural network, and multilayer sparse automatic encoder have been applied to image compression coding, smart meter data compression, and high-throughput genome data lossless compression.Conventional techniques such as Huffman coding and the Shannon Fano method are discussed as well as more recent methods for the compression of data and images. Intelligent methods for data compression are reviewed including the use of Backpropagation and Kohonen neural networks.
The Defense Data Network (DDN) was a computer networking effort of the United States Department of Defense from 1983 through 1995.
It was based on ARPANET technology.
