HK
Hedi Krishna
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Quality of Service (QoS) control is an important concept in computer networking, as it is related to end-user experience. While providing QoS guarantees over the Internet has long been deemed too complicated, the emergence of Software- Defined Networking (SDN), and OpenFlow as its most popular standard, may facilitate QoS control.
In this paper, we consider how to enable bandwidth guarantees with OpenFlow. Our design allows QoS flows to send more than their guaranteed rates, as long as they do not hinder other guaranteed and/or best-effort flows.
Furthermore, our design uses OpenFlow’s meter table to aggregate traffic. Our traffic aggregation functionality only adds overhead to the first switch, but no other complexity is incurred at the subsequent switches. ...
In this paper, we consider how to enable bandwidth guarantees with OpenFlow. Our design allows QoS flows to send more than their guaranteed rates, as long as they do not hinder other guaranteed and/or best-effort flows.
Furthermore, our design uses OpenFlow’s meter table to aggregate traffic. Our traffic aggregation functionality only adds overhead to the first switch, but no other complexity is incurred at the subsequent switches. ...
Quality of Service (QoS) control is an important concept in computer networking, as it is related to end-user experience. While providing QoS guarantees over the Internet has long been deemed too complicated, the emergence of Software- Defined Networking (SDN), and OpenFlow as its most popular standard, may facilitate QoS control.
In this paper, we consider how to enable bandwidth guarantees with OpenFlow. Our design allows QoS flows to send more than their guaranteed rates, as long as they do not hinder other guaranteed and/or best-effort flows.
Furthermore, our design uses OpenFlow’s meter table to aggregate traffic. Our traffic aggregation functionality only adds overhead to the first switch, but no other complexity is incurred at the subsequent switches.
In this paper, we consider how to enable bandwidth guarantees with OpenFlow. Our design allows QoS flows to send more than their guaranteed rates, as long as they do not hinder other guaranteed and/or best-effort flows.
Furthermore, our design uses OpenFlow’s meter table to aggregate traffic. Our traffic aggregation functionality only adds overhead to the first switch, but no other complexity is incurred at the subsequent switches.
Planning of transportation infrastructure is built upon an established set of planning methods to estimate the need for and specifications of roads, amongst others. The abstraction from the real world as needed for applying clear planning tools has grown to considerably differ from the complex urban fabric of activities underlying the transport demand, such as food distribution, commercial activities, education networks, health, etc, especially in busy metropolitan areas. Inclusion of new parameters and use cases in design poses new methodological challenges. The socio-cultural context of urban areas provides for meaningful explanations for the use of urban infrastructure. The cultural context determines the expectations placed on the infrastructure by the people. For example, accessibility for the elderly and children, security and availability. Rapid urbanisation and increased economic inequality in cities has provided additional parameters to understand the longevity and contribution of transport infrastructure. The use of new methods such as the availability of real time data, sensor based data and additional social network analytical methods can provide new insights to understand the needs of the urban masses. Transport infrastructure needs to cater to local needs and become part of a larger ecosystem of a city. In this work we outline a new methodology to use games and simulations based upon city sensing to include stakeholders ignored by the traditional planning processes.
...
Planning of transportation infrastructure is built upon an established set of planning methods to estimate the need for and specifications of roads, amongst others. The abstraction from the real world as needed for applying clear planning tools has grown to considerably differ from the complex urban fabric of activities underlying the transport demand, such as food distribution, commercial activities, education networks, health, etc, especially in busy metropolitan areas. Inclusion of new parameters and use cases in design poses new methodological challenges. The socio-cultural context of urban areas provides for meaningful explanations for the use of urban infrastructure. The cultural context determines the expectations placed on the infrastructure by the people. For example, accessibility for the elderly and children, security and availability. Rapid urbanisation and increased economic inequality in cities has provided additional parameters to understand the longevity and contribution of transport infrastructure. The use of new methods such as the availability of real time data, sensor based data and additional social network analytical methods can provide new insights to understand the needs of the urban masses. Transport infrastructure needs to cater to local needs and become part of a larger ecosystem of a city. In this work we outline a new methodology to use games and simulations based upon city sensing to include stakeholders ignored by the traditional planning processes.