Development of Enhanced Differentiated Services Model of Campus Internet Network

Filed in Articles by on October 31, 2022

Development of Enhanced Differentiated Services Model of Campus Internet Network.


Modern campus networks are designed for high-speed service with the capacity to handle any organization’s bandwidth requirements, support data applications such as electronic mail, web, and file-sharing services.

These networks sometimes lack the capacity to guarantee the quality of service for voice, video, and other interactive applications due to bandwidth requirements and high packet end-to-end delay.

In some networks, voice, video, and other interactive packets must be given priority in terms of bandwidth and delay over less-time-sensitive packets such as mail or file sharing for the networks to meet the QoS demand of these voices, video,

and other interactive applications. In this research, the best-effort service model currently employed in Ahmadu Bello University (ABU) Internet network and differentiated services networking model defined in RFC 2474 were analyzed.

An enhanced differentiated services model was developed to improve and achieve a better reduction in packet end-to-end delay of interactive traffic such as video conferencing and voice streaming in networks.

The simulation results obtained of simulation of the three-services model showed that enhanced differentiated services model with mean packet end-to-end of 0.10481s has 26% delay reduction as compared with differentiated services model with mean packet end-to-end of 0.10757s.

The enhanced differentiated services model has a 32% delay reduction as compared to the best-effort services model with a mean packet end-to-end of 0.15417s.

Similarly, validation results obtained of mean delay of the enhanced differentiated services model performed better than the differentiated services model by and better than the best-effort services model by 83%.

These results demonstrate the superiority of the enhanced differentiated service to differentiated service and best-effort services models in the reduction of packet end-to-end delay of a network. 


Information technology is strategically important to the goals and aspirations of business enterprises, government entities, and educational institutions, particularly Universities.

It is the cornerstone that enables the University’s faculties, researchers, students, administrators, and staff to discover, learn, reach out, and serve humanity. Campus Area Networks (CANs) such as ABU networks transmit interactive and multimedia applications such as video and audio streaming for experimental, practical, and other uses.

The numbers of such interactive and multimedia applications on such networks are on the increase. Voice, video, and data applications demand different types of performance assurance and so Quality of Service (QoS) provision is one of the important components in the design of such networks.

Researchers have done considerable work in developing QoS models, mechanisms,s and queuing disciplines to improve the transmission of interactive and multimedia applications on IP networks.

The challenge of implementation of the developed QoS models, and queuing mechanism on last-mile networks of the internet, and the inability and inappropriate implementation of most of the QoS models result in the degradation of the QoS in terms of packet loss, packet delays,

and packet delay variation for messages transmitted over the networks. Packet-based networks are networks in which packets sent from a source may traverse different paths to arrive at the final destination.

The packets that are routed over separate paths are reassembled at the destination. Transmission rates of the various paths may vary depending upon the usage of the network paths over which the packets are being transmitted (Abaye et al., 2006).

During heavy traffic conditions, packets may be delayed and lost. Packet delays and losses cause poor performance of the network and are more obvious with voice and other interactive streaming communications. 


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CSN Team.

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