摘要:Any node can receive a lot of information about the network by placing its interface into promiscuous mode. The information the node can receive can be used to build trust levels for different modes.
provides paths to every feasible destination making use of Minimum Hop Count (MHC) as the metric to find routing paths. However, it is not very efficient due to its lack of knowledge, such as full topology, node and link status (e.g. buffer, battery, link quality, etc.) and network load when finding routing paths. Actually, MHC paths are usually constructed by longer links (between nodes located at farther distances), which tend to provide lower throughput and frequent breakage.
In Our proposed model path selection is not based on Minimum Hop Count strategy.
In our model path selection is based on trusty nodes and trusty nodes have trusty links. So the links from source to destination have more throughputs and have less frequent breakages.
6.1.2 Link breakage due to node mobility
In OLSR there is no criterion to know about the mobility of nodes. It can select routes with nodes that are mobile most of the time, so packet losses due to frequent link breakages.
In our proposed model the trust value of a node that is mobile most of the time will be low. So this link will not be selected as MPR most of the times. Only nodes that are less mobile will have greater trust value, and data will be mostly forwarded through those nodes.
6.1.3 Selecting less reliable links
OLSR is a proactive routing protocol. It means that it is most suitable in emergency situations, where loss of data is undesirable. To construct optimal paths to each destination OLSR makes use of Minimum Hop Count (MHC) as its metric, however, MHC only cares about the existence of links but not about their quality (link throughput strongly depends on link quality), therefore, two links with completely different qualities (high and poor quality) may be evenly chosen by MHC; or even worst, a one-hop path built by one poor quality link may be chosen over a two-hops path built by two high quality links. Sometime those links which are not too reliable can be selected, which is undesirable in emergency situations.
Our proposed model address this issue in the way that route is selected based on nodes reliability not on MHC. That’s why loss of data is less in our model. So OLSR with our model integration is more suitable for emergency situations.
6.2 Drawbacks:
Although this model addresses some of the OLSR issues in an efficient manner, but this model has some drawbacks which are summarized below:
6.2.1 Computational Overhead
This model requires every node to do some calculation and storage at the start of sending and reception of each and every packet, consuming precious processing unit time, which makes it unusable for nodes with slow processing power.
6.2.2 Memory Usage
Every node has to maintain three tables, which consume memory. This makes the model unusable for nodes with less memory.
6.2.3 Battery Constraint
As nodes have to do a lot of computation and memory storage, which consume precious node battery.
6.3 Future Work:
We have presented a framework for trust establishment in an ad-hoc network without the existence of a central trust authority. The proposed trust model is most suitable for such networks as
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