A simulation study of ad hoc networking of UAVs with opportunistic resource utilization networks

Lilien, Leszek T.
Angın, Pelin
Salih, Raed M.
Specialized ad hoc networks of unmanned aerial vehicles (UAVs) have been playing increasingly important roles in applications for homeland defense and security. Common resource virtualization techniques are mainly designed for stable networks; they fall short in providing optimal performance in more dynamic networks such as mobile ad hoc networks (MANETs)-due to their highly dynamic and unstable nature. We propose application of Opportunistic Resource Utilization Networks (Oppnets), a novel type of MANETs, for UAV ad hoc networking. Oppnets provide middleware to facilitate building flexible and adaptive distributed systems that provide all kinds of resources or services to the requesting application via a helper mechanism. We simulated a homeland defense use case for Oppnets that involves detecting a suspicious watercraft. Our simulation compares performance of an Oppnet with a baseline case in which no Oppnet is used. The simulation results show that Oppnets are a promising framework for high-performance ad hoc UAV networking. They provide excellent performance even under imperfect (and realistic) conditions, such as a less invasive use of helpers, denial of help by some of the candidate helpers, and imperfect detection capabilities of Oppnet components.


A temporal neural network model for constructing connectionist expert system knowledge bases
Alpaslan, Ferda Nur (Elsevier BV, 1996-04-01)
This paper introduces a temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications.
INtERCEDE: An algorithmic approach to networked control system design
Senol, Sinan; Leblebicioğlu, Mehmet Kemal; Schmidt, Şenan Ece (Elsevier BV, 2011-07-01)
Networked Control Systems (NCS) are distributed control systems where the sensor signals to the controllers and the control data to the actuators are enclosed in messages and sent over a communication network. On the one hand, the design of an NCS requires ensuring the stability of the control system and achieving system response that is as close as possible to that of an ideal system which demands network resources. On the other hand, these resources are limited and have to be allocated efficiently to acco...
A comparative study of deep reinforcement learning methods and conventional controllers for aerial manipulation
Ünal, Kazım Burak; Kalkan, Sinan; Saranlı, Afşar; Department of Computer Engineering (2021-2-26)
Aerial manipulation with unmanned aerial vehicles is increasingly becoming a necessity in many applications. In this thesis, we analyze the controller approaches for a bi-rotor aerial manipulator for a pick and place operation. First of all, we compare a classical control approach with a minimum snap trajectory generation and Deep Reinforcement actor-critic algorithms for the control of the aerial manipulator. Furthermore, we examine the effects of degrees of freedom of the manipulator for the Deep Reinforc...
Optimized Unmanned Aerial Vehicles Deployment for Static and Mobile Targets' Monitoring
Al-Turjman, Fadi; Zahmatkesh, Hadi; Al-Oqily, Ibrhaim; Daboul, Reda (Elsevier BV, 2020-01-01)
In the recent decade, drones or Unmanned Aerial Vehicles (UAVs) are getting increasing attention by both industry and academia. Due to the support of advanced technologies, they might be soon an integral part of any smart-cities related project. In this paper, we propose a cost-effective framework related to the optimal placement of drones in order to monitor a set of static and/or dynamic targets in the IoT era. The main objective of this study is to minimize the total number of drones required to monitor ...
Autonomous quadrotor flight with vision-based obstacle avoidance in virtual environment
Eresen, Aydin; Imamoglu, Nevrez; Efe, Mehmet Onder (Elsevier BV, 2012-01-01)
In this paper, vision-based autonomous flight with a quadrotor type unmanned aerial vehicle (UAV) is presented. Automatic detection of obstacles and junctions are achieved by the use of optical flow velocities. Variation in the optical flow is used to determine the reference yaw angle. Path to be followed is generated autonomously and the path following process is achieved via a PID controller operating as the low level control scheme. Proposed method is tested in the Google Earth (R) virtual environment fo...
Citation Formats
L. T. Lilien, L. BEN OTHMANE, P. Angın, A. DECARLO, R. M. Salih, and B. BHARGAVA, “A simulation study of ad hoc networking of UAVs with opportunistic resource utilization networks,” JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, pp. 3–15, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34554.