IEEE Technology and Society Magazine - June 2016 - 71

enhance the scalability of the network as shown in
Figure 2. For a multicluster scenario, the selection of a
cluster head is a serious design issue when one of the
cluster heads goes down. Hence, FANETs should be
designed for highly dynamic scenarios.

Mobility Models
Efficient communication in FANETs is also dependent
on mobility models that capture trails and speed deviations of the UAVs. The selection of a mobility model is
application dependent. A Reference Point Group Mobility
Model (RPGMM) can best represent the motion of UAVs
performing autonomous military operations in groups
without centralized control. In other models such as the
Manhattan Grid Mobility Model (MGMM), which can be
used to emulate a map-based approach, the movement
of UAVs takes into account geographic restrictions [5].
The Random Waypoint Mobility Model (RWMM) can be
used for patrolling applications where UAVs are allowed
to adopt flexible trajectories [26]. The Gauss Markov
Mobility Model (GMMM) can serve to model FANETs as
relaying networks since in this model the movement of
UAVs is dependent on previous speed and directions [9].
Table 1 proposes feasible mobility models for different
application scenarios.

Addressing Concerns about FANET
Communication Protocols
Due to their unique characteristics, FANETs face communication design challenges. An insignificant amount
of work has been done over the higher layers, and development of dedicated communication protocols for the
MAC, network, and transport layers still remain an open
area of research in FANETs. Figure 3 describes the proposed cross layer architecture for FANETs.

MAC Layer

Table 1. Mobility Models Feasibility
for FaNeT application Scenarios
Mobility models

Application scenarios

Manhattan Grid

Complex urban environments [5]

Random WayPoint

Patrol systems [26]

Reference Point
Group Mobility

Disaster management [6][10]
Search and destroy/rescue missions [2]

Gauss Markov

Relaying networks [9]

UAV location information, and tasks assignment
updates [23]. Thus, UAV-to-UAV communication can be
realized efficiently by deploying a low data rate protocol
such as IEEE 802.15.4, which has not been exploited so
far for FANETs.

Network Layer
The dynamic nature of FANETs causes sudden changes
in the network topology and thus makes routing among
UAVs a daunting task. Considering UAV-to-UAV communication, the routing protocol plays an important role in
reliable end-to-end data delivery and makes routing an
engaging research prospect in the FANET domain.
Proactive routing protocols have resulted in minimized routing overheads, while reactive protocols have
proved to address the demand of frequent and unstable
topological changes in FANET studies [20], [27]. Since
there is a clear line of sight between transmitter and
receiver UAVs, geographic routing protocols can make

FANET Scenario Definition

The important issues that the FANET MAC layer should
address are the variable link quality, packet delays, and
optimal channel utilization during real-time network
operation. For the MAC layer protocol, IEEE 802.11 has
been used along with the optimization of commercialoff-the-shelf hardware components, such as directional
and omnidirectional antennas. We propose the use of
another low power, less complex and low data rate protocol, IEEE 802.15.4 MAC, for UAV-to-UAV communication in FANETs. This protocol can be exploited for less
bandwidth hungry applications such as monitoring and
control, wildfire management, remote sensing, and
relaying networks that require control information to be
exchanged within the network. Such applications do not
necessarily require a high data rate protocol such as
IEEE 802.11, as the nature of the in-network messages
exchanged is primarily of time sensitive control data,
june 2016

∕

Upper Layers
Routing
PositionBased Hierarchical Reactive Proactive

MAC

UAV to UAV

802.11 802.15.4
UAV to
Ground Station

PHY

FIGURE 3. Proposed cross layer architecture.

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