An Energy-Efficient Opportunistic Routing Protocol Based on Trajectory Prediction for FANETs

Abstract

In recent years, with the emergence of UAVs(Unmanned Aerial Vehicles) in military and civil applications, the FANETs(Flying Ad-Hoc Networks) composed of multiple UAVs has attracted extensive attention from researchers. As a new type of airborne self-organizing network, the particularity in FANETs such as time-varying network topology and dynamic link makes it difficult to maintain continuous communication when performing tasks. Therefore, it is challenging to design a routing protocol for FANETs to guarantee the quality of data transmission and make communication more effective. In this paper, we propose a new opportunistic routing protocol based on trajectory prediction, named EORB-TP. To be specific, we first predict the position of nodes in three-dimensional space and solve the problem of uncertainty of node contact in opportunistic communication. Secondly, we define the node's trajectory metric value to measure the node's trajectory characteristics and effectively avoid the excessive consumption of edge nodes. In addition, when choosing relay nodes, an energy-saving data forwarding strategy is designed to deal with the limited energy resources and storage space of UAVs. Simulation results show that compared with the state-of-the-art protocols, our protocol can increase the delivery rate by approximately 40% at best and can reduce the delay by approximately 80%.

A Dynamic Clustering Mechanism With Load-Balancing for Flying Ad Hoc Networks

“…To analyze how efficient clusters are created and maintained by the proposed DCM with Load-Balancing mechanism in support of the process of routing packets end-toend, we compare the performance of an intra-and intercluster position-based routing scheme (c.f. Section IV-C) with state-of-the-art routing solutions, namely the Energy-Efficient Opportunistic Routing Protocol (EEOR) [32] and the Smart IoT Control-Based Nature Inspired Energy Efficient Routing Protocol NIEEOR [33]. Whereas, the EEOR algorithm considers the prediction of UAV location based on node trajectory metrics before performing routing aiming to reduce packets' re-transmissions and energy spending.…”

“…Their mobility is based on random way point (RWP) movement model. To get the most realistic setting for nodes progressive speed variations and direction, the JAVA code for RWP model was imported to enable the setting of moving parameters on the UAVs [32]. The simulation area was chosen to reflect the performed scenario of an increasing number of UAVs between 10 and 100.…”

Copy Adaptive Routing Algorithm Based on Network Connectivity in Flying Ad Hoc Networks

“…Combined with the delivery probability as the forwarding standard of node utility value, it solves the problem of data forwarding blindness of traditional DTN routings. e CCATalgorithm uses the number of communicable nodes to (1) for all packets in node a (2) if node a estimates the network is connected then (3) optimal node � node a (4) for all node b in node a 's neighborhood do (5) ifTP b > TP optimal node then (6) optimal node = node b (7) end if (8) end for (9) if optimal node ≠ node a then (10) forward the packet to the optimal node (11) end if (12) else (13) for all node b in node a 's neighborhood do (14) if TP b > TP a then (15) forward a copy to node b (16) end if (17) end for (18) end if (19) Mobile Information Systems locally estimate the connectivity of the network and calculates the next-hop data forwarding nodes using the measure of transmission predicted value. e complexity of the algorithm is Ο(n + log n).…”

“…e optimal number of copies is calculated and distributed to each node of the network before the transmission of messages, and the opportunistic transmission is carried out through the movement of nodes [5]. is method can reduce the transmission of unnecessary message copies and, to a certain extent, reduce network congestion.…”

Accurate Link Lifetime Computation in Autonomous Airborne UAV Networks

“…Therefore, the application of these routing schemes is severely limited. Some mobility-model-agnostic routing schemes (e.g., [18]- [20]) assume that a node can obtain the recent position of the destination node by querying a central or regional location server, and use a store-carry-forward approach to deliver the packets to the destination node. However, they are not suitable for a distributed network with no central or regional location servers [4]- [6].…”