An Introduction to a GIS-Based In-Road Information NetworkThe rate with which network topology changes, is an important factor in network operation. The network with lower rate of topology changing has less control messages than a one with high rate. VAPs affect this factor greatly because they control other nodes and periodically broadcast beacons, so in VAP determination process, it is important to select a one which affect the topology as less as possible. As it is said, VAP has a table with some information. VAP knows how much it takes a vehicle to leave the zone, so it knows which car stays in the zone more than others. This may be a good choice for substitute, but if we want to implement our network by current wireless equipment, it makes an important limitation. Current spread spectrum communication technologies are sensitive to speeds of nodes. It means for nodes with high speed, the efficiency of communication is reduced [3]. This factor must be considered in substitute determination, so it had better choose a SVAP among nodes with speeds near to average zone or lawful speed. This is not a defect for GIS-based network i.e. designers are free to consider any optional factors. IV. VAP AND ROUTING MECHANISM In the GIS based in-road information network, data communication has two classes: (1) data communication within a zone and (2) inter-zone data communication. Nodes (vehicles) in the same zone can communicate together directly. Before they start data transmission, notify the VAP and if there aren't any problems, the VAP will give them permission. This is done because if VAP receives a message request from another zone for one of these connected nodes, it can interrupt them and get the message to the requested node. Now suppose a typical node wants to send data packets to another one. At first it sends a request to send message (RTS) to its VAP and notifies it. The VAP looks up the information table. If destination is inside the zone, it will forward RTS to the destination node. Receiving RTS, the destination node sends a reply back to the source. Now the source and the destination can start data transmission. If a source and its requested destination are not in the same zone, VAP must find the requested node in the network, so it sends a RTS to its direct neighbor VAPs. Since all of the nodes information is saved in VAPs, the source VAP must just search among VAPs. Here, there is a "some for all" location service, because information of all nodes is saved in some nodes. It is important to notice, positions of these stations (information data bases) are fixed and known i.e. each zone has its VAP as a base station, and thus all of nodes can be connected to them without any problems.  Fig. 3. Hierarchical concept in GIS-based in- road network. There is an interesting fact concern to in-road information networks that makes the design and implementation easy. As a matter of fact, since vehicles have to drive just in roads not outside them, locations of nodes of network are nearly predetermined. If a specific car goes out of a road, it will be eliminated from the network and it's not important, because according to our aim, we want to make a network just in roads. According to this fact, it is necessary for a VAP to send RTS messages toward two directions: up-road and down-road. Then unlike other location services and routing protocols in mobile ad-hoc networks, finding an unknown destination is limited to two directions [2]. Then there is a kind of directional flooding mechanism in routing phase in road networks. By using VAPs, the amounts of RTS and control messages are reduced again. In the routing phase, the only responsible node in each zone is VAP. This means that the maximum number of hops in a two-level GIS based network is (3+ Nz), where Nz is the number of zones between a source and destination. If both of a Source and destination are VAPs then the number of hops will be (Nz+2). As we see, the maximum number of hops in a specific road is predetermined and known, so the amount of delay originated from the number of hops can not be increased from a threshold. An important source for delay is networking traffic that makes data packets wait in queues in VAPs. This is caused from bandwidth limitation and discussed in physical layer so here is not considered.  Fig. 4 Route maintenance of In-road network. After finding the destination and making a route between the source and destination, the maintenance phase is started. In this phase it is tried to maintain the route during data transmission. Like base stations in a common cellular communication system, VAPs have to control and survey movements of nodes and forward data packets to destinations in new zones. This is depicted in figure 3. As it observed, the source and destination zones are changed during transfer of data. When a connected node (source or destination) wants to leave its zone, the VAP must pass it to the next VAP and then inform the source VAP. Consequently this can be done for the source node. Because in an in-road network VAPs locate along road such as chains, informing source node may be not necessary. That is, when a message arrives to the pervious destination VAP, this VAP correct the address and forward it toward the destination where is in new zone now. It had better be done when a source and destination move in opposite directions. As a summery we can say our network is a hierarchical (two level) network in which zones is divided based on geographical map that has a communication layer. V. SIMULATION AND RESULTS Since movements of vehicles in roads are random and unpredictable, statistical software ARENA has been used to simulate and model the network. As mentioned, the rate that the network topology is changed with is an important factor that predicts the amounts of control messages and beacons. In high rate, it is expected that there are plenty of control messages in the network and vice versa. To analyze this factor in our in-road network, first we must consider a probability function that presents the rate of vehicle entrance in a special zone. An exponential function can be a good choice. In this function an average of time when a car enters a zone (μ = λ ) and the variance ( α) are given. It has the form like the below function:  In simulation the value of has been selected as 8, 30, 70, 110 and 160 second. Determination of probability distribution function is another issue. The maximum speed which cars must not pass it, is given in each road, so we can estimate the average speed of cars in a special zone as a value near to maximum allowed speed. We chose a triangle probability distribution function for speeds of vehicles. Since the numbers of cars, which have higher speeds than allowed velocity, are less than vehicles, which have speeds less than allowed one, the ramp in higher speed is sharper then the ramp in lower speed.  Fig. 5. The vehicle velocity probability distribution function The average speed of vehicles in this simulation has been chosen equal to 115 km/h. In addition, it is considered that vehicles have fixed velocity along the zone just for simplicity. Another factor in our simulation was the length of a zone. It supposed equal to 3 km. Simulation shows an interesting result. For example for λ as figure 6 indicates, the average rate of topology change is equal to average cars speed divided by the length of the zone. This is because this rate is proportional to VAP change rate. As mentioned before, VAP broadcast control messages more than other nodes, so its movements have the most effect on topology.  Fig.6. Simulation result for . After all, in our in-road information network the rate of topology change is a predetermined value and can differ by cars average speed and the length of zone (if physical layer has no limitation), so maximum delay and queuing problems can be estimated well. As another note, there is an interesting point relative to topology change rate: zones length and car velocity in many roads are inverse, in other words in mounting regions cars derive slower than flat roads and on the other hand in flat places the length of zones are shorter than one in even regions (because of the range of radio communication). Therefore we expected that topology change rate does not differ greatly from flat to even roads. VI. COMPARISON & CONCLUSION Comparison between our method with other identical researches and methods such as GLS, SOTIS [4], DSR and ZPR indicates that all methods suggest using position data in the address field of data packets [1] [2]. However, previous works have not used road characteristics and especially their maps [4] [5]. Generally GIS can be used in in-road networks, simplify models and reduce the amounts of computations. In addition, it guarantee unique zone IDs for network. This is very important and efficiently affects reliability of data delivery.  Table 1 compares our GIS-based in-road information network with other mobile ad hoc networks qualitatively. The main result of this comparison is VAP attribute in network performance. By using this content in addition to road map it is expected that the complexity of in-road network be reduced. VII. REFERENCES
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