车载自组网中GPSR路由最优化

In this paper, we try to proposal a new mechanism for optimizing the route of the Greedy parts of GPSR. By studying the GPSR, we find that the Greedy part of GPSR is not always to find the most optimized route, especially in the denser scenario. So according to this problem, we try to propose a mechanism to find an optimized route. In our proposal, we give out a formula to compute a unique value for each of neighbors. The one with the smallest value will be chosen as the next forwarding hop. The main advantage of our mechanism is that it integrates the influence of both of the denser and sparse environment. Therefore, wherever we located, we can always find an optimized route comparing with GPSR. In this paper, we also give out a mathematical model to evaluate the performance of our proposal. Basing on the model, we use ns to simulate the highway condition. Form the result, we find that our proposal is better that GPSR at aspect of time delay. But in the packet delivery ratio, it doesn't bring us a remarkable improvement. In the following part, I will describe them in detail
security issues. In this paper, we mainly focus on a key networking problem: routing protocol for VANETs. The main requirement of routing protocols is to achieve minimal communication time with minimum consumption of network resources. As we know many routing protocols have been developed for Mobile Ad Hoc Networks (MANETs), and some of them can be applied directly to VANETs, Such as AODV [2] (Adhoc On-demand Distance Vector) and DSR [4] (Dynamic Source Routing). They are designed for general purpose mobile ad hoc networks and do not maintain routes unless they are needed. Hence, they can reduce overhead, especially in scenarios with s small number of network flows. However, VANET differs from MANET by its highly dynamic topology. A number of studies have been done to simulate and compare the performance of routing protocol in various traffic conditions in VANETs[5][6][8][9][11], the simulation results showed that they suffer from poor performances because of the characteristics of fast vehicle's Movement, dynamic information exchange and relative high speed of mobile nodes. So finding and maintaining routes is a very challenging task in VANETs. To consider the Vehicle network, we intuitively think to use the geographical position Keyword: routingprotocol optimal, VANET, GPSR. information to decide the route. The position-based routing protocols have been brought forward. Most 1. Introduction position based routing algorithms base forwarding Vehicular Ad Hoc Networks (VANETs) are t tdecision on location information. For example, greedy emerging new technology to integrate the capabilities. routing always forwards the packet to the vehicle that of new generation wireless networks to vehicles. It geographically closest to the destination. GPSR includes a variety of applications such as co-operative (Greedy Perimeter Stateless Routing) [1] is one of the traffic monitoring, control of traffic flows, blind best known position-based protocols in literature. It crossing, prevention of collisions, nearby information combined the greedy routing with face routing by services and real-time detour routes computation. face using routing to get out of the local minimum Anothe important application for VANETs.is Another Inmptt appication for V nETs where greedy fails. It works best in a free open space scenario with evenly distributed nodes. GPSR is used while on the move, so the users can download music, perform simulations in [6] and itS results were ' ' ~~~~~~~to cmaet S nahgwyseai.I sage send emails, or play back-seat passenger games. Because of that geographic routing achieves better results. GPSR chne codtos VAE ha niu also suffers several from several problems in the city seais[][][] isl,ged owrigi fe characteristics which pose many challenging research retice beas dietcmuiain'ewe issues, such as data dissemination, data sharing, and
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Abstract
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vehicles man not exist due to obstacles such as buildings and trees. Secondly, if apply first the planarized graph to build the routing topology and then return greedy of face routing on it, the routing performance will degrade. i.e., packets need to travel a longer path with higher delays. Thirdly, according to our analysis, we find that the greedy part of GPSR can't always find the most optimal route to the destination, especially in the denser scenario. In this paper, we try to propose a novel mechanism to find the optimal route in any kinds of scenarios. In the following parts, I will describe them in detail.
Patiala, India, 6-7 March 2009
2009 IEEE International Advance Computing Conference (IACC 2009)
Route Optimization for GPSR in VANET
Zhang Ning*, Yunho Jung, Yan Jin, Kee-Cheon Kim** School of the Computer Science and Engineering, MBC Lab, Konkuk University 1 Hwayang, Gwangjin, Seoul 143-701, Korea {truezn, jyhO7, jinyan, kckim}( konkuk.ac.kr