Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Internet applications and users have very diverse service expectations, making the current  same-service-to-all  model inadequate and limiting. In the  relative differentiated services  approach, the network traffic is grouped in a small number of  service classes which are ordered based on their packet forwarding quality , in terms of per-hop metrics for the queueing delays and packet losses. The users and applications, in this context, can  adaptively choose the class that best meets their quality and pricing constraints, based on the assurance that  higher classes will be better, or at least no worse, than lor classes . In this work,  propose the  proportional differentiation model  as a way to refine and quantify this basic premise of relative differentiated services. The proportional differentiation model aims to provide the network operator with the ' tuning knobs ' for adjusting the quality spacing beten classes,  independent of the class loads ; this cannot be achieved with other relative differentiation models, such as strict prioritization or capacity differentiation.  apply the proportional model on queueing-delay differentiation only, leaving the problem of coupled delay and loss differentiation for future work.  discuss the  dynamics  of the proportional delay differentiation model and state the conditions under which it is  feasible . Then,  identify and evaluate (using simulations) two  packet schedulers  that approximate the proportional differentiation model in heavy-load conditions, even in short timescales. Finally,  demonstrate that such per-hop and class-based mechanisms can provide consistent end-to-end differentiation to  individual flows  from different classes, independently of the network path and flow characteristics.
['Constantinos Dovrolis', 'Dimitrios Stiliadis', 'Parameswaran Ramanathan']
I am writing a research paper on a idea Proportional differentiated services: delay differentiation and packet scheduling
[{"from": "human", "value": "I am writing a research paper on a idea Proportional differentiated services: delay differentiation and packet scheduling"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Internet applications and users have very diverse service expectations, making the current  same-service-to-all  model inadequate and limiting. In the  relative differentiated services  approach, the network traffic is grouped in a small number of  service classes which are ordered based on their packet forwarding quality , in terms of per-hop metrics for the queueing delays and packet losses. The users and applications, in this context, can  adaptively choose the class that best meets their quality and pricing constraints, based on the assurance that  higher classes will be better, or at least no worse, than lor classes . In this work,  propose the  proportional differentiation model  as a way to refine and quantify this basic premise of relative differentiated services. The proportional differentiation model aims to provide the network operator with the ' tuning knobs ' for adjusting the quality spacing beten classes,  independent of the class loads ; this cannot be achieved with other relative differentiation models, such as strict prioritization or capacity differentiation.  apply the proportional model on queueing-delay differentiation only, leaving the problem of coupled delay and loss differentiation for future work.  discuss the  dynamics  of the proportional delay differentiation model and state the conditions under which it is  feasible . Then,  identify and evaluate (using simulations) two  packet schedulers  that approximate the proportional differentiation model in heavy-load conditions, even in short timescales. Finally,  demonstrate that such per-hop and class-based mechanisms can provide consistent end-to-end differentiation to  individual flows  from different classes, independently of the network path and flow characteristics."}]