Vehicular Edge Computing(VEC)brings the computational resources in close proximity to the service requestors and thus supports explosive computing demands from smart vehicles.However,the limited computing capability o...Vehicular Edge Computing(VEC)brings the computational resources in close proximity to the service requestors and thus supports explosive computing demands from smart vehicles.However,the limited computing capability of VEC cannot simultaneously respond to large amounts of offloading requests,thus restricting the performance of VEC system.Besides,a mass of traffic data can incur tremendous pressure on the front-haul links between vehicles and the edge server.To strengthen the performance of VEC,in this paper we propose to place services beforehand at the edge server,e.g.,by deploying the services/tasks-oriented data(e.g.,related libraries and databases)in advance at the network edge,instead of downloading them from the remote data center or offloading them from vehicles during the runtime.In this paper,we formulate the service placement problem in VEC to minimize the average response latency for all requested services along the slotted timeline.Specifically,the time slot spanned optimization problem is converted into per-slot optimization problems based on the Lyapunov optimization.Then a greedy heuristic is introduced to the drift-plus-penalty-based algorithm for seeking the approximate solution.The simulation results reveal its advantages over others in terms of optimal values and our strategy can satisfy the long-term energy constraint.展开更多
Many studies based on acute short-term noise exposure have demonstrated that animals can adjust their vocalizations in response to ambient noise.However,the effects of chronic noise over a relatively long time s...Many studies based on acute short-term noise exposure have demonstrated that animals can adjust their vocalizations in response to ambient noise.However,the effects of chronic noise over a relatively long time scale of multiple days remain largely unclear.Bats rely mainly on acoustic signals for perception of environmental and social communication.Nearly all previous studies on noise-induced vocal adjustments have focused on echolocation pulse sounds.Relatively little is known regarding the effects of noise on social communication calls.Here,we examined the dynamic changes in the temporal parameters of echolocation and communication vocalizations of Vespertilio sinensis when exposed to traffic noise over multiple days.We found that the bats started to modify their echolocation vocalizations on the fourth day of noise exposure,with an increase of 42-91%in the total number of pulse sequences per day.Under noisy conditions,the number of pulses within a pulse sequence decreased by an average of 17.2%,resulting in a significantly slower number of pulses/sequence(P<0.001).However,there was little change in the duration of a pulse sequence.These parameters were not significantly adjusted in most communication vocalizations under the noise condition(all P>0.05),except that the duration decreased and the number of syllables/sequences increased in 1 type of communicative vocalization(P<0.05).This study suggests that bats routinely adjust temporal parameters of echolocation but rarely of communication vocalizations in response to noise condition.展开更多
基金supported by National Natural Science Foundation of China(No.62071327)Tianjin Science and Technology Planning Project(No.22ZYYYJC00020)。
文摘Vehicular Edge Computing(VEC)brings the computational resources in close proximity to the service requestors and thus supports explosive computing demands from smart vehicles.However,the limited computing capability of VEC cannot simultaneously respond to large amounts of offloading requests,thus restricting the performance of VEC system.Besides,a mass of traffic data can incur tremendous pressure on the front-haul links between vehicles and the edge server.To strengthen the performance of VEC,in this paper we propose to place services beforehand at the edge server,e.g.,by deploying the services/tasks-oriented data(e.g.,related libraries and databases)in advance at the network edge,instead of downloading them from the remote data center or offloading them from vehicles during the runtime.In this paper,we formulate the service placement problem in VEC to minimize the average response latency for all requested services along the slotted timeline.Specifically,the time slot spanned optimization problem is converted into per-slot optimization problems based on the Lyapunov optimization.Then a greedy heuristic is introduced to the drift-plus-penalty-based algorithm for seeking the approximate solution.The simulation results reveal its advantages over others in terms of optimal values and our strategy can satisfy the long-term energy constraint.
基金the National Natural Science Foundation of China(31500314 and 31872681 to A.L.,31670390 to J.F.and 31470457 to T.L.)the Fundamental Research Funds for the Central Universities(2412017FZ024 to A.L.)+1 种基金the Fund of Jilin Province Science and Technology Development Project(20180101024JC to T.L.)the“1000 Talent Plan for High-Level Foreign Experts”from the Organization Department of the CPC Central Committee(WQ20142200259 to W.M.).
文摘Many studies based on acute short-term noise exposure have demonstrated that animals can adjust their vocalizations in response to ambient noise.However,the effects of chronic noise over a relatively long time scale of multiple days remain largely unclear.Bats rely mainly on acoustic signals for perception of environmental and social communication.Nearly all previous studies on noise-induced vocal adjustments have focused on echolocation pulse sounds.Relatively little is known regarding the effects of noise on social communication calls.Here,we examined the dynamic changes in the temporal parameters of echolocation and communication vocalizations of Vespertilio sinensis when exposed to traffic noise over multiple days.We found that the bats started to modify their echolocation vocalizations on the fourth day of noise exposure,with an increase of 42-91%in the total number of pulse sequences per day.Under noisy conditions,the number of pulses within a pulse sequence decreased by an average of 17.2%,resulting in a significantly slower number of pulses/sequence(P<0.001).However,there was little change in the duration of a pulse sequence.These parameters were not significantly adjusted in most communication vocalizations under the noise condition(all P>0.05),except that the duration decreased and the number of syllables/sequences increased in 1 type of communicative vocalization(P<0.05).This study suggests that bats routinely adjust temporal parameters of echolocation but rarely of communication vocalizations in response to noise condition.