Data Delivery in a Disaster or Quarantined Area Divided into Triangles Using DTN-Based Algorithms for Unmanned Aerial Vehicles

Udroiu, Răzvan; Deaconu, Adrian; Nănău, Corina-Ştefania

doi:10.3390/s21113572

Cited by 15 publications

(12 citation statements)

References 48 publications

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“…Detailed results of the comparison between changing the battery and charging the battery cases are presented in Table 5 . The results obtained in this paper by simulation were compared with those obtained in [ 41 ].…”

Section: Simulation Results and Discussionmentioning

confidence: 94%

“…A network to cover a surface with hexagon cells containing three equilateral triangles was proposed in [ 41 ]. In the current paper, a network is proposed to cover a similar surface with square cells containing two operational squares ( Figure 2 ).…”

Section: Methodsmentioning

confidence: 99%

“…); file information (name, size, time-to-leave); route information (node codes: stations and drones); etc. The json files that store message information for the algorithms Epidemic, Spray and Wait, PRoPHET, MaxProp, and MaxDelivery implemented in the ONE environment are similar to those considered in [ 41 ]. Each route starts and ends with a station id.…”

Section: Methodsmentioning

confidence: 99%

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Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares

Deaconu

Udroiu

Nănău

2021

Sensors

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Drones are frequently used for the delivery of materials or other goods, and to facilitate the capture and transmission of data. Moreover, drone networks have gained significant interest in a number of scenarios, such as in quarantined or isolated areas, following technical damage due to a disaster, or in non-urbanized areas without communication infrastructure. In this context, we propose a network of drones that are able to fly on a map covered by regular polygons, with a well-established mobility schedule, to carry and transfer data. Two means exist to equidistantly cover an area with points, namely, grouping the points into equilateral triangles or squares. In this study, a network of drones that fly in an aerial area divided into squares was proposed and investigated. This network was compared with the case in which the area is divided into equilateral triangles. The cost of the square drone network was lower than that of the triangular network with the same cell length, but the efficiency factors were better for the latter. Two situations related to increasing the drone autonomy using drone charging or battery changing stations were analyzed. This study proposed a Delay Tolerant Network (DTN) to optimize the transmission of data. Multiple simulation studies based on experimental flight tests were performed using the proposed algorithm versus five traditional DTN methods. A light Wi-Fi Arduino development board was used for the data transfer between drones and stations using delivery protocols. The efficiency of data transmission using single-copy and multiple-copy algorithms was analyzed. Simulation results showed a better performance of the proposed Time-Dependent Drone (TD-Drone) Dijkstra algorithm compared with the Epidemic, Spray and Wait, PRoPHET, MaxProp, and MaxDelivery routing protocols.

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Section: Simulation Results and Discussionmentioning

confidence: 94%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares

Deaconu

Udroiu

Nănău

2021

Sensors

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“…Hence, in this time of the pandemic, such short commuting needs to be tackled accordingly [10,21]. One such application area that requires an infection perimeter setting is the navigation or route planning from source to destination [22,23] avoiding infectious zones. The traditional process of creating an appropriate route is carried out by considering the possibility of a route, the traffic, and the efficiency of the route based on some objective metric [24,25].…”

Section: Introductionmentioning

confidence: 99%

Application-Based COVID-19 Micro-Mobility Solution for Safe and Smart Navigation in Pandemics

Mishra

Singh

Bhattacharya

2021

IJGI

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Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity.

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“…Recently, considering such worse-case scenarios, several researchers have focused on store-carry-and-forward-based routing approaches (i.e., the delay-tolerant network (DTN) based approach) to ensure successful packet delivery [12][13][14][15][16][17][18]. In this type of routing protocol, the UAV stores data until it meets a suitable UAV to successfully forward that data to reach the destination.…”

Section: Introductionmentioning

confidence: 99%

LECAR: Location Estimation-Based Congestion-Aware Routing Protocol for Sparsely Deployed Energy-Efficient UAVs

Mahmud

Cho

2021

Sensors

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Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time.

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Data Delivery in a Disaster or Quarantined Area Divided into Triangles Using DTN-Based Algorithms for Unmanned Aerial Vehicles

Cited by 15 publications

References 48 publications

Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares

Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares

Application-Based COVID-19 Micro-Mobility Solution for Safe and Smart Navigation in Pandemics

LECAR: Location Estimation-Based Congestion-Aware Routing Protocol for Sparsely Deployed Energy-Efficient UAVs

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