Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference betwee...Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.展开更多
半年前,2007年的11月中旬,IBM在上海召开厂“2007 IBM SOA创新高峰论坛”。这次论坛应和其“创新”之名。在IBM SOA中国的发展中具有里程碑式的创新意义,因为就在这次论坛上,IBM推出了Smart SOA,正式树立了自身SOA的品牌形象和一套完整...半年前,2007年的11月中旬,IBM在上海召开厂“2007 IBM SOA创新高峰论坛”。这次论坛应和其“创新”之名。在IBM SOA中国的发展中具有里程碑式的创新意义,因为就在这次论坛上,IBM推出了Smart SOA,正式树立了自身SOA的品牌形象和一套完整的方案,使其SOA在中国由零散的概念、信息、结构成为统一的流程,为国内企业的SOA发展带来了更明晰的路径和指导。展开更多
基金funded by Project Number INML2104 under the Interdisciplinary Center of Smart Mobility and Logistics at King Fahd University of Petroleum and Minerals.This study also was supported by the Special Research Fund BOF23KV17.
文摘Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.
文摘半年前,2007年的11月中旬,IBM在上海召开厂“2007 IBM SOA创新高峰论坛”。这次论坛应和其“创新”之名。在IBM SOA中国的发展中具有里程碑式的创新意义,因为就在这次论坛上,IBM推出了Smart SOA,正式树立了自身SOA的品牌形象和一套完整的方案,使其SOA在中国由零散的概念、信息、结构成为统一的流程,为国内企业的SOA发展带来了更明晰的路径和指导。
