Free Data Networking Quality of Service Essay Sample

Data networking is a significant aspect of computer science. It is made up of various hardware modules and computers that are linked through communication systems, which facilitate distribution of data and resources. The quality of service is concerned with several linked features of computer networks, which enable the transfer of traffic with particular necessities. Quality of service makes it possible for network administrators to utilize available resources properly. They can offer high quality services without necessarily enlarging their networks.

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Quality of service can greatly be achieved through installation of non shared communication links. For instance, two computers can be linked through a cable. Despite its effectiveness, quality of service may sometimes be degraded in the following circumstances. First, shared network connections that are composed of more than two devices have to compete for a similar communication link. Secondly, the quality of services may be impacted on by setbacks stemming from networking equipment. For instance, lack of capacity to process huge loads. Thirdly, distance may also corrupt the quality of service.

These obstacles culminate into network congestion. Network congestion is one of the hitches that usually arise in the networks especially when a data transmission node is overloaded. Besides this, some network congestions stem from overflowing queues. In this case, a link becomes less effective since its efficiency deteriorates considerably when it is overstretched with data. Network congestions are usually characterized with packet loss, and new connections may also be intercepted. These situations can be handled as follows.

Congestion management systems can be employed in mitigating congestion when it arises. For instance, end system flow management can be used to solve this problem. Although it is not regarded as a congestion control mechanism, it can stop the dispatcher from overrunning the recipient’s buffer. Network blockage control is another viable approach. In this method, end scheme strangle back with an aim of preventing networking jamming. Network –based jamming prevention is also applicable in this context. In this mechanism, a router identifies potential overcrowding, and it tries to slowdown dispatchers before blocking queues. Lastly, resource allocation is a rather complicated approach that can help in clearing network congestion by jamming excess traffic that cannot be handled by the network capacity.

In the intricate tapestry of data networking, it's crucial to delve into the realm of packet prioritization to further enhance quality of service. Prioritizing certain types of data over others ensures that critical information receives preferential treatment, reducing latency and enhancing overall network efficiency. This can be particularly beneficial in scenarios where real-time communication or time-sensitive data transmission is paramount. Moreover, advancements in technology have given rise to Quality of Service (QoS) protocols, such as Differentiated Services (DiffServ) and Multiprotocol Label Switching (MPLS), which offer more granular control over traffic management. DiffServ employs a differentiated approach to packet marking, allowing for the classification of packets into different service classes. MPLS, on the other hand, introduces label-switching technology, enabling routers to make forwarding decisions based on these labels, leading to more efficient routing and resource allocation.

In the pursuit of addressing network congestion, emerging technologies like Software-Defined Networking (SDN) have garnered attention. SDN introduces a centralized and programmable network architecture, allowing administrators to dynamically manage network resources based on real-time demands. This adaptive approach enables swift responses to changing network conditions, mitigating congestion more effectively. Furthermore, as the Internet of Things (IoT) continues to proliferate, the landscape of data networking expands to accommodate a myriad of connected devices. This influx of devices with diverse communication requirements necessitates innovative solutions for maintaining quality of service. Edge computing, where data processing occurs closer to the source rather than relying solely on centralized cloud servers, emerges as a viable strategy to reduce latency and enhance the efficiency of data transmission in IoT ecosystems.

In conclusion, the evolution of data networking involves not only navigating the existing challenges but also embracing cutting-edge technologies and methodologies. Packet prioritization, QoS protocols like DiffServ and MPLS, the advent of SDN, and the integration of edge computing in the context of IoT contribute to a more comprehensive understanding of how to elevate the quality of service in the ever-expanding landscape of computer networks.


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