Proc. SPIE. 4907, Optical Switching and Optical Interconnection II
KEYWORDS: Gold, FDA class I medical device development, Data modeling, Silver, Networks, Computer simulations, Telecommunications, Algorithm development, Data communications, Global system for mobile communications
Multiservice networks will carry di erent kinds of applications in the near future. Bandwidth requirements change rapidly, and the network resource management will play an important role to guarantee the use of the limited resources in the most eÆcient way. We approach the channel capacity allocation problem by developing an SLA (Service Level Agreement) based channel allocation method. In our model, the channel may be wired or wireless, so this method can be adapted in multi-technique networks. The algorithm allocates resources to several di erent service classes via several di erent capacity routes. Service provider perfroms optimization by allocating data rate in such a way that the satisfactory of the customers as well as the revenue is maximized.
In the future Internet, di erent applications such as Voice over IP (VoIP) and Video-on-Demand (VoD) arise with di erent Quality of Service (QoS) parameters including e.g. guaranteed bandwidth, delay jitter, and latency. Different kinds of service classes (e.g. gold, silver, bronze) arise. The customers of di erent classes pay di erent prices to the service provider, who must share resources in a plausible way. In a router, packets are queued using a multi-queue system, where each queue corresponds to one service class. In this paper, an adaptive Weighted Fair Queue based algorithm for traÆc allocation is presented and studied. The weights in gradient type WFQ algorithm are adapted using revenue as a target function.
This paper introduces a model that can be used to share link capacity among
customers under different kind of traffic conditions. This model is suitable for
different kind of networks like the 4G networks (fast wireless access to wired network) to support connections of given duration
that requires a certain quality of service. We study different types of network
traffic mixed in a same communication link. A single link is considered as a
bottleneck and the goal is to find customer traffic profiles that maximizes the
revenue of the link. Presented allocation system accepts every calls and there is not absolute blocking, but
the offered data rate/user depends on the network load.
Data arrival rate depends on the current link utilization, user's payment (selected CoS class) and delay.
The arrival rate is (i) increasing with respect to the offered
data rate, (ii) decreasing with respect to the price, (iii)
decreasing with respect to the network load, and (iv) decreasing with respect to the delay.
As an example, explicit formula obeying these conditions is given and analyzed.