Communication Control and Network
4.2 Swarm of computational clouds control system
Chapter 4
Communication Control and
Table 4.1:Communication control and network
Problem Details of the issue Proposed Solution
The overload and defi-ciency of the GCS af-ter controlling multiple UAV via an IoT service.
When the GCS has installed in the cloud server, The cloud cannot handle multi-UAV effi-ciently.
A swarm of computational clouds is integrated to enhance the GCS performance when multi-UAV is used.
The master protocol is able to use two different types of protocols when using IoT.
Evaluation of TCP and UDP protocols was missing and used randomly in previous re-searches.
TCP and UDP protocols have been evaluated in real flight experiment, and an evaluation has been given.
Heterogeneous network environment.
A heterogeneous network is a possible scenario in a disaster scenario. There is no technical solution to support UAV com-munication system in a het-erogeneous network environ-ment.
NTMobile is integrated into UAV and GCS and evaluated through real flight experiment where UAV and remote con-trol device have been forced to exchange networks.
In previous work [Aljehani, 2016d] in Chapter 3, authors introduced a multi-UAV system for disaster response system. Tracking mission and scanning mission used image processing techniques in order to make an evacuation map from captured images of pedestrians and ar-eas, it also requires high computational processing capabilities to distinguish valuable data and control UAVs at the same time. So, in this Chapter 4, author is proceeding the work with intensely focusing on enhancement of the multi-UAV communication control and network, suggesting using swarm clouds as multiple GCS nodes instead of a single cloud. Author has inspired by swarm clouds after it has been verified in work of [Ardagna, 2012].
4.2.1 UAV as a device
Utilizing UAV as an IoT device, UAV must possess a capability to connect to the Internet.
Hence, the platform of the UAV must be compatible with cellular, and wireless communi-cations. Nowadays, the technology of embedded systems offers comprehensive features for engineers to configure, develop and integrate devices mutually together. In this study, au-thor used Linux single board comupter on the main frame of the UAV. It helps integrating UAV board into a cellular dongle. Moreover, author used virtual proxy network (VPN) ser-vices to earn a secure connection and identify GCSs and UAVs IPs. Figure 4.1 demonstrates the proposed system of single UAV connected to the cloud via a VPN service.
4.2.2 System design
Any simplistic IoT architecture consists of devices, networks, and applications domain (see Figure 4.1). In Figure 4.2, Multi-UAV controlled by one GCS Cloud. Technically, GCS-cloud manages UAVs and transmits and receives data based on UAV System Identification (SYS ID), which is a systemic identification for each UAV in the network. In this configuration, MAVProxy is the master protocol to control UAVs [Nirmala, 2014]. Also, specific ports have been assigned to provide a simultaneous and real-time control system.
4.2.3 Swarm clouds as Multi-GCS
Swarm clouds are more efficient to control multiple UAVs since each cloud can be assigned to a single UAV or a group of UAVs depending on the system design and cloud processing ability. Also, a third-party of clouds can analyze data, monitor the operations, and record the flight history like logs for each UAV. PPTP protocol has been used to have secure communi-cation between the VPN server and UAVs. The developed Multi-GCS is shown in Figure 4.3.
Both of Figures 4.2 and 4.3 demonstrated independent flights; however, shadow control can
VPN Server
GCS Cloud
Cellular Connection
Internet Internet
Internet
Remote Client
UAV Access Point
Figure 4.1:UAV controlled by one cloud GCS via VPN.
Cloud Devices
PPTP
VPN Server UAV1
SYS_ID1
MAVlink
MAVlink
MAVlink
Interface and Command UAV2
SYS_ID2
UAVn SYS_ID3
Assignments and Tasks Networks
Data Processing Connection Authentication 10.8.0.1:14550 GCS
10.8.0.2:14550
10.8.0.X:14550
10.8.0.4:14550 HTTPS
Telemetry and Images
Data
PPTP TCP port 1723 PPTP TCP port 1723 PPTP TCP port 1723
Figure 4.2:Multi-UAV on one cloud GCS system.
deliver central monitoring and management, which makes UAVs completely visible to the client and accessible via remote protocols such as Remote Desk Protocol (RDP) and Secure Shell Protocol (SSH).
PPTP TCP port 1723
PPTP TCP port 1723
Swarm Clouds Devices
VPN Server MAVlink UAV2
SYS_ID2
Networks
GCS Control Interface
GCS Control Interface
GCS Control Interface Telemetry
Images Data Telemetry
Images Data Telemetry
Images Data
All logs and Data All logs and Data All logs and Data
Data Process
Shadow Control MAVlink
UAV1 SYS_ID1
MAVlink UAVn
SYS_IDn
HTTPS HTTPS
HTTPS
RDP Port 3389 SSH : 22
SSH : 22 SSH : 22 PPTP
PPTP
PPTP 10.8.0.1:14550
10.8.0.2:14550
10.8.0.X:14550
10.8.0.4:14550
10.8.0.5:14550
10.8.0.X:14550 PPTP
TCP port 1723
Third-Party
GCS IP GCS IP
GCS IP
Figure 4.3:Developed system designed for Multi-GCS system.
4.2.4 Implementation
This system demonstrates two UAVs controlled by swarm clouds with and assigned with different flight modes. ArduPilot Mega (APM) flight modes is used to control UAVs [Bin, 2009]. The guided initial UAV to receive all waypoints from the cloud server. Then, Auto mode fetches all received waypoints to start autopilot mission. "Stabilized" mode is used for manual assistance and shadow control. It also uses onboard sensors to perform a sta-ble flying experience. In both of "Loiter" and Auto modes system employs 3D-GPS lock to perform better flight experience. Failsafe and Return to Launch (RTL) have been stipulated for emergency (i.e., low battery or lost connection). Figures 4.3, 4.4, and 4.5 illustrate two UAVs on different modes of control by swarm cloud after executing scanning mission in real experiments at the institution campus.
4.2.5 Summary
This system shows an invented method to control multi-UAV throughout swarm clouds servers. Each cloud server has been assigned to control one or a group of UAVs, and third-party clouds can manage the income data from the flight controller to manage UAV’s assign-ments. In this system, the performance of multi-GCS proved its dependability compared to a single-GCS system, communication was more consistent due using multiple network ports, and the approachability to the UAV controller was much faster considering each UAV has a sole connection to individual private cloud. The system has not experienced any overload on swarm clouds as he has on a single cloud system, which is reasonably anticipated. How-ever, communication requires more evaluation. Therefore, the next section will go in-depth among TCP and UDP protocols evaluation. Furthermore, it describes how UAV can be a valuable device if it converts to an IoT device.
Figure 4.4: Navigation data of two UAVs on different GCS-Cloud on real flight experiment.
Path of UAV 1 Path of UAV 2 120
100 80 60 40 20 0 -20
12:07:00 12:09:00 12:11:00 12:13:00 12:15:00 12:17:00 Time
Altitude (m) UAV1 UAV2
Start of Guided Mode
Start Points of Auto Mode
Start of RTL Mode
Stabilized Mode
Figure 4.5:Graph of altitude and time for two UAVs in mission and third party cloud represents logs of each UAV.