Energy-Aware Multi-UAV Networks for On-Demand Task Execution

Author(s):  
Abhishek Bera ◽  
Sudip Misra ◽  
Chandranath Chatterjee
Author(s):  
Zhou Zhou ◽  
Kenli Li ◽  
Jemal Abawajy ◽  
Mohammad Shojafar ◽  
Chowdhury Morshed ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Waqas Shah

As the world’s economic activities are expanding, the energy comes to the fore to the question of the sustainable growth in all technological areas, including wireless mobile networking. Energyaware routing schemes for wireless networks have spurred a great deal of recent research towards achieving this goal. Recently, an energy-aware routing protocol for MANETs (so-called energy-efficient ad hoc on-demand routing protocol (EEAODR) for MANETs was proposed, in which the energy load among nodes is balanced so that a minimum energy level is maintained and the resulting network lifetime is increased. In this paper, an Ant Colony Optimization (ACO) inspired approach to EEAODR (ACO-EEAODR) is proposed. To the best of our knowledge, no attempts have been made so far in this direction. Simulation results are provided, demonstrating that the ACO-EEAODR outperforms the EEAODR scheme in terms of energy consumed and network lifetime, chosen as performance metrics.


Author(s):  
Shiv Prakash ◽  
Deo Prakash Vidyarthi

Consumption of energy in the large computing system is an important issue not only because energy sources are depleting fast but also due to the deteriorating environmental conditions. A computational grid is a large heterogeneous distributed computing platform which consumes enormous energy in the task execution. Energy-aware job scheduling, in the computational grid, is an important issue that has been addressed in this work. If the tasks are properly scheduled, keeping the optimal energy concern, it is possible to save the energy consumed by the system in the task execution. The prime objective, in this work, is to schedule the dependent tasks of a job, on the grid nodes with optimal energy consumption. Energy consumption is estimated with the help of Dynamic Voltage Frequency Scaling (DVFS). Makespan, while optimizing the energy consumption, is also taken care of in the proposed model. GA is applied for the purpose and therefore the model is named as Energy Aware Genetic Algorithm (EAGA). Performance evaluation of the proposed model is done using GridSim simulator. A comparative study with other existing models viz. min-min and max-min proves the efficacy of the proposed model.


2021 ◽  
Vol 11 (3) ◽  
pp. 1054
Author(s):  
Ing-Chau Chang ◽  
Chi-Sheng Liao ◽  
Chin-En Yen

For handling the broken-down communication infrastructure when a disaster event happens, this paper proposes to dispatch the unmanned aerial vehicle (UAV) to the disaster area as the relay node, which further forms a Flying Ad hoc Network (FANET). Since the UAV only owns limited energy and a disaster event may need multiple UAVs to cover its area, an efficient multi-UAV dispatch algorithm is critical to recover the communication link of the disaster area. In this paper, we adopt the mobile ground control station (GCS) to transport UAVs to the boundary of the disaster area first. According to the UAV energy consumption rate during flight and two communication modes, the UAV charging progress, and the number of required UAVs of the event, the mobile GCS then executes the proposed energy-aware multi-UAV dispatch algorithm (EAMUD) to dispatch multiple UAVs to this disaster area for building the FANET. Hence, the broken-down link in the disaster area is recovered after the FANET connects to nearby network infrastructure. Further, we propose the multi-UAV handoff scheme and exception handling processes to replace energy-exhausted UAVs for maximizing the event communication time of the disaster event. Finally, we execute simulations for related work and four EAMUD variants under different parameter values in the real scenario. These results exhibit that EAMUD with the Postpone method (EAMUD-P) achieves the highest event communication time among all these schemes.


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