Subscribe Us

Get free daily email updates!

Follow us!

Friday, July 1, 2011

Next-Generation Internet: Cognitive routing protocols concepts

Nowadays, there are many routing protocols available for mobile ad-hoc networks. They mainly use instantaneous parameters rather than the predicted parameters to perform the routing functions. They are not aware of the parameter history. The value of hop counts is measured by the route control packets. Current physical topology is used to construct the network topology. If the future physical topology is predicted, a better network topology might be constructed by avoiding the potential link failure or finding a data path with high transmission data rate.
Most traditional routing protocols do not consider the channel conditions and link load. In this case, it is assumed that the channel conditions for all links are the same and the load levels for all links are the same. Unlike the wired networks, the channel conditions and the link load in a wireless network tend to vary significantly because of the node mobility or environment changes. Therefore, the nodes in a wireless network should be able to differentiate the links with different channel conditions or load levels to have a general view of the network. In this way, the routing functions can be better performed. Further, the network performance might be increased.

cognitive techniques are increasingly becoming common in wireless networks. Compared to the traditional routing protocols, the main advantage of the cognitive routing protocols is that the network topology can be better constructed, because the routing functions are performed based on the predicted parameters. The predicted parameters are implied from the parameter history. With the predicted parameters, the nodes can have a general view which reflects the history and the future rather than an instantaneous view of the network topology. Consequently, cognitive routing protocols should be able to increase the network performance.

In optimum situations, the network topology should be adaptive and stable. To make the network topology adaptive, the routing updates should be triggered frequently to accommodate the physical topology changes which might incur lots of overhead. On the other hand, to make the network topology stable, the routing updates should be triggered infrequently to minimize the overhead. Therefore, there is a tradeoff between the accuracy and overhead. Cognitive routing protocols should be able to adjust the tradeoff to maximize the network performance by learning the history and predicting the future. mobility-aware routing protocol (MARP) and spectrum-aware routing protocol (SARP) constitute such required cognitive routing protocols. The mobility-aware routing protocol is aware of node mobility. With MARP, the nodes are able to trigger the routing updates before the link breaks. With SARP, the nodes are able to select an appropriate frequency for each link and select an appropriate path to route application packets.

With MARP, the nodes perform the local optimization when triggering the routing updates. When a node predicts that the link is about to break, it informs the upstream node. The upstream node floods the route request packets. In many cases, the source node is transparent to the local optimization. In other words, the packet transmission is not interrupted. The source node does not need to worry about the local optimization or the link failure. Therefore, MARP performs seamless handover. Mobility-aware routing protocol uses the predicted throughput increment as the metric to select the path. Unlike in traditional routing protocols, the predicted throughput increment is updated along the path. The destination node selects the path with the biggest predicted throughput increment. In this way, MARP overcomes the issues of traditional routing protocols which use hop counts as the metric to select the path in terms of network topology construction.

0 Responses to “ Next-Generation Internet: Cognitive routing protocols concepts ”

Post a Comment