Organizations can use a variety of bandwidth management methods to ensure that bandwidth is readily available for time sensitive voice communication and collaboration. Software-based distributed bandwidth management includes a number of common techniques, but the least amount of bandwidth is usually allocated over a group of machines or servers (look at this site to get all the details). Data-based distributed bandwidth management focuses on optimizing data bandwidth, rather than bandwidth for a particular application. If the capacity of a server or connection is a limiting factor in the use of bandwidth, then its consumption and storage demands can be quantified by manually assigning a monthly maximum bandwidth to each server or application.
Monthly bandwidth limitations can be tracked to understand which applications or devices require bandwidth the most. Service-based bandwidth management is similar to data-based bandwidth management, but instead of improving utilization, it uses the total bandwidth to determine whether and how much to optimize application delivery. Generally, the solution does not allocate a maximum bandwidth by disk. Rather, bandwidth usage is evaluated by computer-on-computer and server-to-server. One aspect of service-based bandwidth management that we’re testing in this study is the availability of the bandwidth in each region to the carrier.
Many recent solutions to broadband network congestion and capacity have involved reconfiguring network equipment, often hardware-based, to provide improved network speeds in a defined range of frequencies. This often requires obtaining small changes to network equipment to gain a significant improvement. In addition, the industry has tried to minimize bandwidth usage by making the packet count (the amount of data transmitted per unit time) lower.
With the rapid spread of large data sets and cloud computing, the availability of bandwidth is a critical resource for nearly every application, regardless of the type of data. While most systems already have tools to automatically manage bandwidth, a primary constraint remains the expensive hardware necessary to manage bandwidth on a large scale. We believe that a number of techniques to manage bandwidth will be useful in future environments. We consider some of these techniques as an opportunity for improvement to the current broadband network.
We tested several bandwidth management techniques, and then evaluated their results against three benchmark specifications. In order to test network service, we used POTS, IS-IS, GIGA and T1/7. The three criteria for each technique were:
Packet loss ratio (PBR) used to quantify the impact of packet loss; the average number of lost packets per kilobyte of transmission. This is a key indicator of network capacity. Packet loss must be isolated from the loss of connections, and is typically measured with a packet loss test tool. This test determines how much of the total data sent across the network is lost.
Loss per unit time (LPUt) used to quantify the impact of packet loss. The average number of lost packets per second, or lost packet per second. This is a key indicator of network congestion and bandwidth consumption. LPUt helps indicate how much bandwidth is wasted.
Bandwidth utilization (Bandwidth consumption) the percentage of data sent that is actually delivered to its intended destination.
The performance of bandwidth management techniques was evaluated with respect to three scenarios, one based on real-world conditions, two in which an application can be limited by the bandwidth available. In real-world situations, degradation from a bandwidth management technique results in slower connections.