Efficient and highly scalable route discovey for on-demand routing protocols in ad hoc networks

This paper presents a number of different route discovery strategies for on-demand routing protocols, which provide more control to each intermediate node make during the route discovery phase to make intelligent forwarding decisions. This is achieved through the idea of selfselection. In self-selecting route discovery each node independently makes Route Request (RREQ) forwarding decisions based upon a selection criterion or by satisfying certain conditions. The nodes which do not satisfy the selection criterion do not rebroadcast the routing packets. We implemented our self-selecting route discovery strategies over AODV using the GloMoSim network simulation package, and compared the performance with existing route discovery strategies used in AODV. Our simulation results show that a significant drop in the number of control packets can be achieved by giving each intermediate node more authority for self-selection during route discovery. Furthermore, a significant increase in throughput is achieved as the number nodes in the network is increased

A Performance Study of Dynamic Zone Topology Routing Protocol

In this paper we present a simulation study of a hybrid routing protocol we proposed in our previous work. Our hybrid routing strategy is called Dynamic Zone Topology Routing protocol (DZTR). This protocol has been designed to provide scalable routing in a Mobile Ad hoc Networking (MANET) environment. DZTR breaks the network into a number of zones by using a GPS. The topology of each zone is maintained proactively and the route to the nodes in other zones are determined reactively. DZTR proposes a number of different strategies to reduce routing overhead in large networks and reduce the single point of failure during data forwarding. In this paper, we propose a number of improvements for DZTR and investigate its performance using simulations. We compare the performance of DZTR against AODV, LAR1 and LPAR. Our results show that DZTR has fewer routing overheads than the other simulated routing protocols and achieves higher levels of scalability as the size and the density of the network is increased

Wireless Power Transfer and Data Collection in Wireless Sensor Networks

In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semi-decentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular Technolog

On the outage of multihop parallel relay networks

In this paper we analyze the outage probability of a cooperative multihop parallel relay network in Nakagami-m fading channels. The general closed form expression of the outage probability is derived both for integer and arbitrary Nakagami parameter m. We present numerical results on the performance of the network. It shows a careful configuration of the network size and power sharing between nodes can ensure optimal outage performance in the network

Intelligent Spatial Interpolation-based Frost Prediction Methodology using Artificial Neural Networks with Limited Local Data

The weather phenomenon of frost poses great threats to agriculture. Since it damages the crops and plants from upstream of the supply chain, the potential impact of frosts is significant for agriculture-related industries. As recent frost prediction methods are based on on-site historical data and sensors, extra development and deployment time are required for data collection in any new site. The aim of this article is to eliminate the dependency on on-site historical data and sensors for frost prediction methods. In this article, a frost prediction method based on spatial interpolation is proposed. The models use climate data from existing weather stations, digital elevation models surveys, and normalized difference vegetation index data to estimate a target site's next hour minimum temperature. The proposed method utilizes ensemble learning to increase the model accuracy. Ensemble methods include averaging and weighted averaging. Climate datasets are obtained from 75 weather stations across New South Wales and Australian Capital Territory areas of Australia. The models are constructed with five-fold validation, splitting the weather stations into five testing dataset folds. For each fold, the other stations act as training datasets. After the models are constructed, three experiments are conducted. The first experiment compares the results generated by models between different folds. Then, the second experiment compares the accuracy of different methods. The final experiment reveals the effect of available stations on the proposed models. The results show that the proposed method reached a detection rate up to 92.55%. This method could be implemented as an alternative solution when on-site historical datasets are scarce.Comment: 13 pages, 13 figure

Characterising the interactions between unicast and broadcast in IEEE 802.11 ad hoc networks

This paper investigates the relative performance of unicast and broadcast traffic traversing a one-hop ad hoc network utilising the 802.11 DCF. An extended Markov model has been developed and validated through computer simulation, which successfully predicts the respective performance of unicast and broadcast in a variety of mixed traffic scenarios. Under heavy network traffic conditions, a significant divergence is seen to develop between the performance of the two traffic classes - in particular, when network becomes saturated, unicast traffic is effectively given higher precedence over broadcast. As a result, the network becomes dominated by unicast frames, leading to poor rates of broadcast frame delivery

Load-balanced route discovery for mobile ad hoc networks, Journal of Telecommunications and Information Technology, 2006, nr 1

This paper presents flow-aware routing protocol (FARP), a new routing strategy designed to improve load balancing and scalability in mobile ad hoc networks. FARP is a hop-by-hop routing protocol, which introduces a flow-aware route discovery strategy to reduce the number of control overheads propagating through the network and distributes the flow of data through least congested nodes to balance the network traffic. FARP was implemented in GloMoSim and compared with AODV. To investigate the load distribution capability of FARP new performance metrics were introduced to measure the data packet flow distribution capability of the each routing protocol. The simulation results obtained illustrate that FARP achieves high levels of throughput, reduces the level of control overheads during route discovery and distributes the network load more evenly between nodes when compared to AODV. This paper also describes a number of alternative strategies and improvements for the FARP

LPAR: an adaptive routing strategy for MANETs, Journal of Telecommunications and Information Technology, 2003, nr 2

This paper presents a new global positioning system (GPS)-based routing protocol, called location-based point-to-point adaptive routing (LPAR) for mobile ad hoc networks. This protocol utilises a 3-state route discovery strategy in a point-to-point manner to reduce routing overhead while maximising throughput in medium to large mobile ad hoc networks. In LPAR, data transmission is adaptable to changing network conditions. This is achieved by using a primary and a secondary data forwarding strategy to transfer data from the source to the destination when the condition of the route is changed during data transmission. A simulation study is performed to compare the performance of LPAR with a number of different exisiting routing algorithms. Our results indicate that LPAR produces less overhead than other simulated routing strategies, while maintains high levels of throughput