
Abstract Internet of Drones (IoDs) is getting growing interest of researchers due to its applicability in wide range of applications for transportation, weather monitoring, emergency monitoring for flood, earth quake, healthcare and road hazards. To update the data about emergency situation, a real-time data sharing is mandatory. However, regular message transmission by various drones may not only overwhelm a central server but it also causes congestion on the network. It is mandatory to reduce messaging cost and congestion. This paper presents a fog-assisted congestion avoidance approach for Smooth Message Dissemination (SMD). We present a message forwarding algorithm for congestion avoidance to select the appropriate next-hop node using layered model. This model is based on various layers having drones. In first phase, it looks for an appropriate drone in a layer near the fog server for message forwarding. In next step, the drone is identified in nearby layers to forward the emergency message to next-hop to further locate the group head as per priority. It is a drone that has less distance towards fog server and inform in its one-hop circle. It can stop forwarding message after delivering it to fog server. Finally, the fog server disseminates information timely towards upper layers for necessary actions for emergency situations. The performance of the proposed approach is validated through extensive simulations using NS 2.35. Results prove the dominance of SMD over counterparts in terms of messaging overhead, packet delivery ratio, throughput, energy consumption and average delay. Proposed SMD improves PDR by 85% and message overhead cost by 91% as compared to counterparts.
330, 004
330, 004
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
