| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2005: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2004: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Research Abstract |
The networks of today are going through a rapid evolution and they are expected to support a wide range of multimedia applications. The requirement for timely delivery of multimedia data raises new challenges for the next generation broadband networks. The key issue is the Quality of Service (QoS) routing. Also, ensuring the QoS demands to traffic flows and groups of flows is an important challenge for future broadband networks, and resource provisioning via Call Admission Control (CAC) is a key mechanism for achieving this. In order to support multimedia communication over broadband networks, it is necessary to develop routing algorithms which use for routing more than one QoS parameter such as throughput, delay, and loss probability. This is because new services such as video on demand and remote meeting systems require better QoS. But, the problem of QoS routing is difficult due to the following reasons. The distributed applications have very diverse QoS constraints on delay, loss r
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atio and bandwidth. Multiple constraints often make the routing problem intractable. For example, finding a feasible route with two independent path constraints is NP-complete.
In our previous work, we proposed an intelligent routing and CAC strategy using cooperative agents. However, we only considered the time delay for the routing. The QoS and Congestion Control (CC) parameters were considered as indicators of QoS satisfication and congestion. The proposed a GA based routing algorithm called ARGAQ could support two QoS parameters : delay and transmission success rate. The simulation results show that ARGAQ method has better performance than a routing algorithm with only one QoS parameter called ARGA method. However, the ARGAQ method is effective only if the parameters have a relation between them and the GA fitness function can be expressed by a mathematical formula. In this work, we extend our previous work by proposing and implementing new algorithms based on Fuzzy Logic (FL) and Genetic Algorithm (GA) which use for CAC and routing many QoS parameters. The proposed GA-based multi-objective optimization algorithm uses a multi-division group model for multi-objective optimization. The simulation results show that proposed framework has a good performance and is a promising method for QoS routing and CAC decision.
We also applied the proposed GA-based algorithm for QoS routing in ad-hoc networks and we showed that the proposed algorithm can be applied for ad-hoc networks. We proposed and implemented also a P2P system and Distance Learning System which show a good performance in broadband networks Less
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