An Energy Efficient Design for UAV Communication With Mobile Edge Computing
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摘要
This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm.
This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm.
This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm.
引文
[1]Kumar,K.,Liu,J.,Lu,Y.H.,&Bhargava,B.(2013)."A survey of computation offloading for mobile systems."Mobile Networks and Applications18.1(2013):129-140.
[2]M.Messous,H.Sedjelmaci,N.Houari and S.Senouci,"Computation offloading game for an UAV network in mobile edge computing,"2017IEEE International Conference on Communications(ICC),Paris,2017,pp.1-6.
[3]J.Zhang et al.,"Energy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks,"in IEEE Internet of Things Journal,vol.5,no.4,pp.2633-2645,Aug.2018.
[4]Y.Mao,J.Zhang,S.H.Song and K.B.Letaief,"Power-Delay Tradeoff in Multi-User Mobile-Edge Computing Systems,"2016 IEEE Global Communications Conference(GLOBECOM),Washington,DC,2016,pp.1-6.
[5]H.Wang,R.Li,L.Fan and H.Zhang,"Joint computation offloading and data caching with delay optimization in mobile-edge computing systems,"2017 9th International Conference on Wireless Communications and Signal Processing(WCSP),Nanjing,2017,pp.1-6.
[6]C.Wang,C.Liang,F.R.Yu,Q.Chen and L.Tang,"Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing,"in IEEE Transactions on Wireless Communications,vol.16,no.8,pp.4924-4938,Aug.2017.
[7]Y.Zeng,R.Zhang and T.J.Lim,"Wireless communications with unmanned aerial vehicles:opportunities and challenges,"in IEEE Communications Magazine,vol.54,no.5,pp.36-42,May 2016.
[8]Y.Wang,M.Sheng,X.Wang,L.Wang and J.Li,"Mobile-Edge Computing:Partial Computation Offloading Using Dynamic Voltage Scaling,"in IEEE Transactions on Communications,vol.64,no.10,pp.4268-4282,Oct.2016.
[9]Y.Zeng and R.Zhang,"Energy-Efficient UAVCommunication With Trajectory Optimization,"in IEEE Transactions on Wireless Communications,vol.16,no.6,pp.3747-3760,June 2017.
[10]Q.Shi,C.Peng,W.Xu,M.Hong and Y.Cai,"Energy Efficiency Optimization for MISO SWIPTSystems With Zero-Forcing Beamforming,"in IEEE Transactions on Signal Processing,vol.64,no.4,pp.842-854,Feb.15,2016.
[11]Grant,M.,Boyd,S.,&Ye,Y."CVX:Matlab software for disciplined convex programming."(2008).
[12]Boyd,S.,&Vandenberghe,L.(2004).Convex optimization.Cambridge university press.
[13]Y.Mao,J.Zhang and K.B.Letaief,"Joint Task Offloading Scheduling and Transmit Power Allocation for Mobile-Edge Computing Systems,"2017 IEEE Wireless Communications and Networking Conference(WCNC),San Francisco,CA,2017,pp.1-6.
[14]Q.Wu et al.,"Cognitive Internet of Things:ANew Paradigm Beyond Connection,"in IEEEInternet of Things Journal,vol.1,no.2,pp.129-143,April 2014.
[15]Q.Wu,G.Ding,J.Wang and Y.Yao,"Spatial-Temporal Oppor tunity Detection for Spectrum-Heterogeneous Cognitive Radio Networks:Two-Dimensional Sensing,"in IEEETransactions on Wireless Communications,vol.12,no.2,pp.516-526,February 2013.
[16]Lanckriet,G.R.,&Sriperumbudur,B.K."On the convergence of the concave-convex procedure."Advances in neural information processing systems.2009.
[2]M.Messous,H.Sedjelmaci,N.Houari and S.Senouci,"Computation offloading game for an UAV network in mobile edge computing,"2017IEEE International Conference on Communications(ICC),Paris,2017,pp.1-6.
[3]J.Zhang et al.,"Energy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks,"in IEEE Internet of Things Journal,vol.5,no.4,pp.2633-2645,Aug.2018.
[4]Y.Mao,J.Zhang,S.H.Song and K.B.Letaief,"Power-Delay Tradeoff in Multi-User Mobile-Edge Computing Systems,"2016 IEEE Global Communications Conference(GLOBECOM),Washington,DC,2016,pp.1-6.
[5]H.Wang,R.Li,L.Fan and H.Zhang,"Joint computation offloading and data caching with delay optimization in mobile-edge computing systems,"2017 9th International Conference on Wireless Communications and Signal Processing(WCSP),Nanjing,2017,pp.1-6.
[6]C.Wang,C.Liang,F.R.Yu,Q.Chen and L.Tang,"Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing,"in IEEE Transactions on Wireless Communications,vol.16,no.8,pp.4924-4938,Aug.2017.
[7]Y.Zeng,R.Zhang and T.J.Lim,"Wireless communications with unmanned aerial vehicles:opportunities and challenges,"in IEEE Communications Magazine,vol.54,no.5,pp.36-42,May 2016.
[8]Y.Wang,M.Sheng,X.Wang,L.Wang and J.Li,"Mobile-Edge Computing:Partial Computation Offloading Using Dynamic Voltage Scaling,"in IEEE Transactions on Communications,vol.64,no.10,pp.4268-4282,Oct.2016.
[9]Y.Zeng and R.Zhang,"Energy-Efficient UAVCommunication With Trajectory Optimization,"in IEEE Transactions on Wireless Communications,vol.16,no.6,pp.3747-3760,June 2017.
[10]Q.Shi,C.Peng,W.Xu,M.Hong and Y.Cai,"Energy Efficiency Optimization for MISO SWIPTSystems With Zero-Forcing Beamforming,"in IEEE Transactions on Signal Processing,vol.64,no.4,pp.842-854,Feb.15,2016.
[11]Grant,M.,Boyd,S.,&Ye,Y."CVX:Matlab software for disciplined convex programming."(2008).
[12]Boyd,S.,&Vandenberghe,L.(2004).Convex optimization.Cambridge university press.
[13]Y.Mao,J.Zhang and K.B.Letaief,"Joint Task Offloading Scheduling and Transmit Power Allocation for Mobile-Edge Computing Systems,"2017 IEEE Wireless Communications and Networking Conference(WCNC),San Francisco,CA,2017,pp.1-6.
[14]Q.Wu et al.,"Cognitive Internet of Things:ANew Paradigm Beyond Connection,"in IEEEInternet of Things Journal,vol.1,no.2,pp.129-143,April 2014.
[15]Q.Wu,G.Ding,J.Wang and Y.Yao,"Spatial-Temporal Oppor tunity Detection for Spectrum-Heterogeneous Cognitive Radio Networks:Two-Dimensional Sensing,"in IEEETransactions on Wireless Communications,vol.12,no.2,pp.516-526,February 2013.
[16]Lanckriet,G.R.,&Sriperumbudur,B.K."On the convergence of the concave-convex procedure."Advances in neural information processing systems.2009.