A ferry mobility based direction and time‐aware greedy delay‐tolerant routing (FM‐DT‐GDR) protocol for sparse flying ad‐hoc network

Abstract

Flying Ad-hoc Networks (FANETs) play a major role in various civilian and non-civilian applications especially in search and rescue operations after natural disasters. Unmanned aerial vehicles (UAVs) collect critical information in the form of images and videos from disaster areas and send it to the ground station (GS) for immediate rescue operations. UAVs capture the information and send it to the GS to carry out the rescue operations without any delay. A small number of UAVs operate over a large geographic area for rescue operations when a sudden natural disaster occurs that creates a sparse or intermittent network. Therefore, routing is the most challenging issue in sparse FANETs due to the low-node density network and high mobility of UAVs Existing routing protocols for connected or dense FANETs cannot be directly adopted in extremely sparse FANETs. Only a few works exist that focus on sparse networks as most of the work is based on connected networks. Traditional routing algorithms for sparse FANETs are based on a flood-based strategy that creates unnecessary delays in the network. Some recently developed routing algorithms directly adopt greedy-based forwarding for routing in sparse networks and consider the non-realistic assumption without considering delay as a significant constraint of search and rescue operations. This paper presents a novel ferry mobility-based direction and time-aware greedy delay-tolerant routing (FM-DT-GDR) protocol for data transfer to GS during disaster relief operations in the sparse FANETs without delay. FM-DT-GDR uses a store, carry, and forward (SCF) mechanism to prevent data loss when no neighbors are present. Upon receiving the beacon from the ferry node, the search nodes calculate the nearest destination from their location between the ferry and the GS and send the data accordingly. The ferry collects data from the search UAVs and sends it to the GS. Optimized ferry trajectories significantly improve route availability between GS and search UAVs Furthermore, the proposed routing scheme efficiently selects the forwarder node to send the data to the selected destination without any delay. FM-DT-GDR provides significant improvements in packet delivery ratio, routing overhead, and end-to-end delay compared to traditional routing protocols.

MF‐DLB: Multimetric forwarding and directed acyclic graph‐based load balancing for geographic routing in FANETs

“…In FANETs, to improve the resilience of geographic routing against frequency network disconnections, several delay-tolerant network-based geographical routing schemes have been proposed. 30,48,49 In Bujari et al, 30 a delay-tolerant routing protocol is introduced for SAR missions. The scheduled movement path of neighboring UAVs is considered by the forwarding UAV to transmit a data packet based on its predicted encounter with the destination.…”

“…In FANETs, to improve the resilience of geographic routing against frequency network disconnections, several delay‐tolerant network‐based geographical routing schemes have been proposed 30,48,49 . In Bujari et al, 30 a delay‐tolerant routing protocol is introduced for SAR missions.…”

“…Otherwise, the source UAV employs a store‐carry‐wait approach or selects the farthest neighboring UAV as the next hop. Further, in Agrawal et al, 49 the trajectory of ferry UAVs is optimized to improve the connectivity between searching UAVs and the GS. However, instead of avoiding the local minima, these DTN approaches rely solely on store‐carry‐forward mechanisms, resulting in higher delay.…”

Congestion aware reward based scheme based on delay tolerant networks for emergency evacuation in 6G‐based internet of things networks

“…Authors in Reference 33, proposed a ferry mobility based direction and time aware greedy DTN (FM‐DT‐GDR) for flying ad‐hoc network. This protocol is used for data communication during disaster relief operations.…”

A Novel Geo-Social-Aware Video Edge Delivery Strategy Based on Modeling of Social-Geographical Dynamic in an Urban Area

“…Video services such as IPTV, VoD, and video living rely on wonderful content and quality of services (QoS) and have become the most popular application on the Internet, so much so that video traffic has become more than 70% of the world's total traffic [5][6][7][8]. The combination between video applications and social networks promotes the process and range of video dissemination because the video spread considers social links between users as the new sharing channel [9][10][11][12][13]. The assistance of social networks further results in the blowout of video traffic, which brings a heavy burden for the core networks.…”