Enhancement of Mobile Ad-hoc Network Models by Using Realistic Mobility and Access Control Mechanisms

ABSTRACT: A mobile ad-hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the need for base stations or any other preexisting network infrastructure. Ad-hoc networking received a great interest due to its low cost, high flexibility, fast network establishment, self-reconfiguration, high speed for data services, rapid deployment and support for mobility. However, in a wireless network without a fixed infrastructure and with nodes’ mobility enabled, the topology keeps on changing. This causes frequent path changes and leads to an increase in network congestion and transmission delay. Random waypoint (RWP) mobility model is widely used in ad-hoc network simulations. The model suffers from speed decay as simulation progresses, and may not reach the steady state in term of instantaneous average node speed. This usually leads to inaccurate results in protocol validation of MANETs modeling. The convergence of the average speed to its steady state value is delayed. Also, the probability distributions of speed vary over the simulation time, such that the node speed distribution at the initial state is different from the corresponding distribution at the end of the simulation. Gamma random waypoint (GRWP) mobility model has been proposed to overcome these problems. The nodes’ speeds of GRWP are sampled from Gamma distribution. The analysis and simulation results indicate that the proposed GRWP mobility model outperforms the existing RWP mobility models. In modeling wireless ad-hoc networks, the assumption of infinite population is usually made. However, such models lead to deficiencies in the model, since they do not hold in real applications. Therefore, we model the wireless ad-hoc network as closedform queueing network. In particular, the carrier sense multiple access with collision avoidance (CSMA/CA) based RTS/CTS handshake mechanism is modeled under finite population assumption. We take into account packet arrival time, network size, packet size, buffer size and backoff scheme. This is to ensure a realistic queueing model which describes the MAC protocol and nodes’ behavior in the network environment more precisely. The collected results indicate that the finite population model gives an accurate and more realistic behavior of the RTS/CTS mechanism. Keywords: Ad-hoc Networks, IEEE 802.11, MANETs, performance of MAC protocol, CSMA/CA, mobility models, RWP, Gamma distribution, finite population, blocking probability. ……………………………………………………………………………………………………………………………………………………………………………………………………………………