Performance Evaluation of Ad Hoc Routing in a Swarm of Autonomous Aerial Vehicles

This thesis investigates the performance of three mobile ad hoc routing protocols in the context of a swarm of autonomous unmanned aerial vehicles (UAVs). It is proposed that a wireless network of nodes having an average of 5.1774 log n neighbors, where n is the total number of nodes in the network, has a high probability of having no partitions. By decreasing transmission range while ensuring network connectivity, and implementing multi-hop routing between nodes, spatial multiplexing is exploited whereby multiple pairs of nodes simultaneously transmit on the same channel. The proposal is evaluated using the Greedy Perimeter Stateless Routing (GPSR), Optimized Link State Routing (OLSR), and Ad hoc On-demand Distance Vector (AODV) routing protocols in the context of a swarm of UAVs using the OPNET network simulation tool. The first-known implementation of GPSR in OPNET is constructed, and routing performance is observed when routing protocol, number of nodes, transmission range, and traffic workload are varied. Performance is evaluated based on proportion of packets successfully delivered, average packet hop count, and average end-to-end delay of packets received. Results indicate that the routing protocol choice has a significant impact on routing performance. While GPSR successfully delivers 50% more packets than OLSR, and experiences a 53% smaller end-to-end delay than AODV when routing packets in a swarm of UAVs, increasing transmission range and using direct transmission to destination nodes with no routing results in a level of performance not achieved using any of the routing protocols evaluated

Evaluation of an OPNET Model for Unmanned Aerial Vehicle Networks

The concept of Unmanned Aerial Vehicles (UAVs) was first used as early as the American Civil War, when the North and the South unsuccessfully attempted to launch balloons with explosive devices. Since the American Civil War, the UAV concept has been used in all subsequent military operations. Over the last few years, there has been an explosion in the use of UAVs in military operations, as well as civilian and commercial applications. UAV Mobile Ad Hoc Networks (MANETs) are fast becoming essential to conducting Network-Centric Warfare (NCW). As of October 2006, coalition UAVs, exclusive of hand-launched systems, had flown almost 400,000 flight hours in support of Operations Enduring Freedom and Iraqi Freedom [1]. This study develops a verified network model that emulates UAV network behavior during flight, using a leading simulation tool. A flexible modeling and simulation environment is developed to test proposed technologies against realistic mission scenarios. The simulation model evaluation is performed and findings documented. These simulations are designed to understand the characteristics and essential performance parameters of the delivered model. A statistical analysis is performed to explain results obtained, and identify potential performance irregularities. A systemic approach is taken during the preparation and execution simulation phases to avoid producing misleading results

Performance Analysis of a Cooperative Search Algorithm for Multiple Unmanned Aerial Vehicles under Limited Communication Conditions

This research investigates the impacts of realistic wireless communications upon a group of unmanned aerial vehicles (UAVs) utilizing a distributed search algorithm. The UAVs are used to survey an area for mobile targets and they require communication to cooperatively locate the targets. The mobile targets do not continually radiate energy, which exacerbates the search effort; a UAV could fly directly over a target and not detect it. A simulation of cooperative UAVs is implemented using the OPNET Modeler network simulation tool. The search performance of a group of UAVs is observed when communication range, data rate, and the number of UAVs are varied. The performance is evaluated based on the total time it takes for the UAVs to completely detect all the targets in a given search area, the number of times internal areas are scanned, the amount of communication throughput achieved, the network traffic generated, network latency, and number of network collisions. The results indicate that the number of UAVs was found to have the greatest impact on the group\u27s ability to search an area, implying that the data shared between the UAVs provides little benefit to the search algorithm. In addition, it was found that a network with a 100 Kbps or faster data rate should allow for minimal congestion and a large degree of scalability. The findings demonstrate that the proposed four-stage search algorithm should operate reasonably well under realistic conditions

On the Delay of Reactive-Greedy-Reactive Routing in Unmanned Aeronautical Ad-hoc Networks

AbstractReactive-Greedy-Reactive (RGR) has been proposed as a promising routing protocol in highly mobile density-variable Unmanned Aeronautical Ad-hoc Networks (UAANETs). In RGR, location information of Unmanned Aerial Vehicles (UAVs) as well as reactive end-to-end paths are employed in the routing process. It had already been shown that RGR outperforms existing routing protocols in terms of packet delivery ratio. In this paper, the delay performance of RGR is evaluated and compared against Ad-hoc On-demand Distance Vector (AODV) and Greedy Geographic Forwarding (GGF).We considerextensive simulation scenariostocover both searchingand tracking applicationsofUAANETs. The results illustrate that when the number of UAVs is high enough in a searching mission to form a connected UAANET, RGR performs well. In sparsely connected searching scenarios or dense tracking scenarios, RGR may also slightly decrease delay compared to traditional reactive routing protocols for similar PDR

Airborne Wireless Communication Modeling and Analysis with MATLAB

Over the past decade, there has been a dramatic increase in the use of unmanned aerial vehicles (UAV) for military, commercial, and private applications. Critical to maintaining control and a use for these systems is the development of wireless networking systems [1]. Computer simulation has increasingly become a key player in airborne networking developments though the accuracy and credibility of network simulations has become a topic of increasing scrutiny [2-5]. Much of the inaccuracies seen in simulation are due to inaccurate modeling of the physical layer of the communication system. This research develops a physical layer model that combines antenna modeling using computational electromagnetics and the two-ray propagation model to predict the received signal strength. The antenna is modeled with triangular patches and analyzed by extending the antenna modeling algorithm by Sergey Makarov, which employs Rao-Wilton-Glisson basis functions. The two-ray model consists of a line-of-sight ray and a reflected ray that is modeled as a lossless ground reflection. Comparison with a UAV data collection shows that the developed physical layer model improves over a simpler model that was only dependent on distance. The resulting two-ray model provides a more accurate networking model framework for future wireless network simulations

A Novel Communications Protocol Using Geographic Routing for Swarming UAVs Performing a Search Mission

This research develops the UAV Search Mission Protocol (USMP) for swarming UAVs and determines the protocol\u27s effect on search mission performance. It is hypothesized that geographically routing USMP messages improves search performance by providing geography-dependent data to locations where it impacts search decisions. It is also proposed that the swarm can use data collected by the geographic routing protocol to accurately determine UAV locations and avoid sending explicit location updates. The hypothesis is tested by developing several USMP designs that are combined with the Greedy Perimeter Stateless Routing (GPSR) protocol and a search mission swarm logic into a single network simulation. The test designs use various transmission power levels, sensor types and swarm sizes. The simulation collects performance metrics for each scenario, including measures of distance traveled, UAV direction changes, number of searches and search concentration. USMP significantly improves mission performance over scenarios without inter-UAV communication. However, protocol designs that simply broadcast messages improve search performance by 83% in total searches and 20% in distance traveled compared to geographic routing candidates. Additionally, sending explicit location updates generates 3%-6% better performance per metric versus harvesting GPSR\u27s location information

A survey on network simulators in three-dimensional wireless ad hoc and sensor networks

© 2016 The Author(s). As steady research in wireless ad hoc and sensor networks is going on, performance evaluation through relevant network simulator becomes indispensable procedure to demonstrate superiority to comparative schemes and suitability in most literatures. Thus, it is very important to establish credibility of simulation results by investigating merits and limitations of each simulator prior to selection. Based on this motivation, in this article, we present a comprehensive survey on current network simulators for new emerging research area, three-dimensional wireless ad hoc and sensor networks which is represented by airborne ad hoc networks and underwater sensor networks by reviewing major existing simulators as well as presenting their main features in several aspects. In addition, we address the outstanding mobility models which are main components in simulation study for self-organizing ad hoc networks. Finally, open research issues and research challenges are discussed and presented

Improving routing in networks of Unmanned Aerial Vehicles: Reactive-Greedy-Reactive

Because of their specific characteristics, Unmanned Aeronautical Ad-hoc Networks (UAANETs) can be classified as a special kind of mobile ad hoc networks. Because of the high mobility of Unmanned Aerial Vehicles, designing a good routing protocol for UAANETs is challenging. Here, we present a new protocol called Reactive-Greedy-Reactive (RGR) as a promising routing protocol in high mobility and density-variable scenarios. RGR combines features of reactive MANET routing protocols such as Ad-hoc On-demand Distance Vector with geographic routing protocols, exploiting the unique characteristics of UAANETs. In addition to combining reactive and geographic routing, the protocol has a number of features to further improve the overall performance. We present the rationale and design of the protocol, discuss the specific performance improvements in detail and provide extensive simulation results that demonstrate that RGR outperforms purely reactive or geographic routing protocols. The results also demonstrate the impact of the various protocol modifications

RGIM: An Integrated Approach to Improve QoS in AODV, DSR and DSDV Routing Protocols for FANETS Using the Chain Mobility Model

Flying ad hoc networks (FANETs) are a collection of unmanned aerial vehicles that communicate without any predefined infrastructure. FANET, being one of the most researched topics nowadays, finds its scope in many complex applications like drones used for military applications, border surveillance systems and other systems like civil applications in traffic monitoring and disaster management. Quality of service (QoS) performance parameters for routing e.g. delay, packet delivery ratio, jitter and throughput in FANETs are quite difficult to improve. Mobility models play an important role in evaluating the performance of the routing protocols. In this paper, the integration of two selected mobility models, i.e. random waypoint and Gauss–Markov model, is implemented. As a result, the random Gauss integrated model is proposed for evaluating the performance of AODV (ad hoc on-demand distance vector), DSR (dynamic source routing) and DSDV (destination-Sequenced distance vector) routing protocols. The simulation is done with an NS2 simulator for various scenarios by varying the number of nodes and taking low- and high-node speeds of 50 and 500, respectively. The experimental results show that the proposed model improves the QoS performance parameters of AODV, DSR and DSDV protocol