Comparison of Reactive Routing Protocol Dynamic Manet on Demand and Ad Hoc on Demand Distance Vector for Improving Vehicular Ad hoc Network Performance
SUMMARYAn extension of the well-knownParticle Swarm Optimization(PSO) to multi-robot applications has been recently proposed and denoted asRobotic Darwinian PSO(RDPSO), benefited from the dynamical partitioning of the whole population of robots. Although such strategy allows decreasing the amount of required information exchange among robots, a further analysis on the communication complexity of the RDPSO needs to be carried out so as to evaluate the scalability of the algorithm. Moreover, a further study on the most adequate multi-hop routing protocol should be conducted. Therefore, this paper starts by analyzing the architecture and characteristics of the RDPSO communication system, thus describing the dynamics of the communication data packet structure shared between teammates. Such procedure will be the first step to achieving a more scalable implementation of RDPSO by optimizing the communication procedure between robots. Second, an ad hoc on-demand distance vector reactive routing protocol is extended based on the RDPSO concepts, so as to reduce the communication overhead within swarms of robots. Experimental results with teams of 15 real robots and 60 simulated robots show that the proposed methodology significantly reduces the communication overhead, thus improving the scalability and applicability of the RDPSO algorithm.
Stability and security are the key directions of VANET (vehicular ad hoc network) research. In order to solve the related problems in VANET, an improved AODV (ad hoc on-demand distance vector) routing protocol based on fuzzy neural network, namely, GSS-AODV (AODV with genetic simulated annealing, security and stability), is proposed. The improved scheme of the protocol analyzes the data in the movement process of the mobile node in VANET, extracts the parameters that affect the link stability, and uses the fuzzy neural network optimized by genetic simulated annealing to calculate the node stability. The improved scheme extracts the main parameters that affect the security of the nodes. After normalization, the fuzzy neural network based on genetic simulated annealing algorithm is used for fuzzy processing, and the node trust value of each node is evaluated. The improved scheme uses node stability and node trust value to control each routing process and dynamically adjusts parameters of the algorithm. The experimental results show that the improved scheme is stable and secure.
The performance of an IEEE 802.11b ad-hoc network that uses the AODV (Ad hoc On-demand Distance Vector) routing protocol is evaluated. One significant issue relating to the behavior of WLAN cards that has considerable impact on AODV performance was observed during the initial testing of the system and it is discussed and a solution proposed. Some aspects of the network performance are then assessed for several scenarios with low mobility. Route discovery latency results indicate that it is possible for mobile applications to operate reasonably well over ad-hoc networks in light to moderate traffic. UDP throughput results indicate that such networks could support tens of users using low-bit rate applications or possibly higher bit rates if applications generate data in bursts. Finally, some problems with TCP operating in this context were observed.
Mobile ad hoc network (MANET) is an infrastructure-less and decentralized network without any physical connections. Nodes are mobile, free to move, and independent of each other which makes routing a difficult task. Hence, a dynamic routing protocol is needed to make MANET reliable and function properly. Several routing protocols have been proposed with different working mechanisms and performance levels. Therefore, the performance study of those protocols is needed. This paper evaluates the performance of MANET routing protocols using simulation based experiments to observe the behavior of the network as the density of the nodes increases. The paper evaluates the performance of proactive (fisheye state routing), reactive (ad hoc on-demand distance vector), and hybrid (zone routing protocol) routing protocols in terms of the packet delivery fraction, average throughput, and average end-to-end delay. The simulations of protocols to analyze their performance in different conditions were performed using the network simulator 2 (NS 2).
<p class="Default">Ad hoc networks are mobile wireless networks where each node is acting as a router. The existing routing protocols such as Destination sequences distance vector, Optimized list state routing protocols, Ad hoc on demand routing protocol, Ad hoc on demand multipath routing protocol, Dynamic source routing are optimized versions of distance vector or link state routing protocols. In this paper, existing protocols such as DSDV, AODV, AOMDV, OLSR and DSR are analyzed on 50 nodes Mobile Ad Hoc network with random mobility. Packet delivery ratio, delay, control overhead and throughput parameters are used for performance analysis.</p>
Improving security and stability of ad hoc on-demand distance vector with fuzzy neural network in vehicular ad hoc network