This paper analyzes the threat of TCG Software Stack(TSS)/TCM Service Module(TSM) deadlock in multi-user environment such as cloud and discusses its causes and mechanism.In addition,this paper puts forward a dynamic p...This paper analyzes the threat of TCG Software Stack(TSS)/TCM Service Module(TSM) deadlock in multi-user environment such as cloud and discusses its causes and mechanism.In addition,this paper puts forward a dynamic priority task scheduling strategy based on value evaluation to handle this threat.The strategy is based on the implementation features of trusted hardware and establishes a multi-level ready queue.In this strategy,an algorithm for real-time value computing is also designed,and it can adjust the production curves of the real time value by setting parameters in different environment,thus enhancing its adaptability,which is followed by scheduling and algorithm description.This paper also implements the algorithm and carries out its performance optimization.Due to the experiment result from Intel NUC,it is shown that TSS based on advanced DPTSV is able to solve the problem of deadlock with no negative influence on performance and security in multi-user environment.展开更多
We developed a multinomial-logit-based stochastic user equilibrium(MNL SUE)model incorporating time value of cargo to investigate future proportions of cargo flow through the Northeast Passage(NEP)and the Suez Canal R...We developed a multinomial-logit-based stochastic user equilibrium(MNL SUE)model incorporating time value of cargo to investigate future proportions of cargo flow through the Northeast Passage(NEP)and the Suez Canal Route between representative ports.We studied navigation during the ice-free and ice-covered seasons using sea ice projections for 2070 based on 1991–2021 NEP ice data.Sailing distance and time between selected ports are lower via the NEP than the Suez Canal Route.Under the scenario of year-round operation of the NEP,the proportion of cargo flow through the NEP is estimated to be 68.5%,which represents considerable commercial potential.Proportions are higher for the ice-free season and for ports at high latitudes.We also assessed flow under different scenarios.Under the scenario of fuel price increase,proportion of flow through the NEP in the ice-covered season is expected to increase.If time value is ignored,flow through the NEP is expected to increase all year round.If shippers become more cost-conscious,flow through the NEP is also expected to increase.展开更多
Unmanned aerial vehicles(UAVs)can be employed as aerial base stations(BSs)due to their high mobility and flexible deployment.This paper focuses on a UAV-assisted wireless network,where users can be scheduled to get ac...Unmanned aerial vehicles(UAVs)can be employed as aerial base stations(BSs)due to their high mobility and flexible deployment.This paper focuses on a UAV-assisted wireless network,where users can be scheduled to get access to either an aerial BS or a terrestrial BS for uplink transmission.In contrast to state-of-the-art designs focusing on the instantaneous cost of the network,this paper aims at minimizing the long-term average transmit power consumed by the users by dynamically optimizing user association and power allocation in each time slot.Such a joint user association scheduling and power allocation problem can be formulated as a Markov decision process(MDP).Unfortunately,solving such an MDP problem with the conventional relative value iteration(RVI)can suffer from the curses of dimensionality,in the presence of a large number of users.As a countermeasure,we propose a distributed RVI algorithm to reduce the dimension of the MDP problem,such that the original problem can be decoupled into multiple solvable small-scale MDP problems.Simulation results reveal that the proposed algorithm can yield lower longterm average transmit power consumption than both the conventional RVI algorithm and a baseline algorithm with myopic policies.展开更多
基金supported by the State Key Program of National Natural Science Foundation of China(Grant No.91118003)the National Natural Science Foundation of China(Grant No.61173138,61272452,61332019)+1 种基金the National Basic Research Program of China("973"Program)(Grant No.2014CB340600)the National High-Tech Research and Development Program of China("863"Program)(Grant No.2015AA016002)
文摘This paper analyzes the threat of TCG Software Stack(TSS)/TCM Service Module(TSM) deadlock in multi-user environment such as cloud and discusses its causes and mechanism.In addition,this paper puts forward a dynamic priority task scheduling strategy based on value evaluation to handle this threat.The strategy is based on the implementation features of trusted hardware and establishes a multi-level ready queue.In this strategy,an algorithm for real-time value computing is also designed,and it can adjust the production curves of the real time value by setting parameters in different environment,thus enhancing its adaptability,which is followed by scheduling and algorithm description.This paper also implements the algorithm and carries out its performance optimization.Due to the experiment result from Intel NUC,it is shown that TSS based on advanced DPTSV is able to solve the problem of deadlock with no negative influence on performance and security in multi-user environment.
基金supported by the Ministry of Education of People’s Republic of China(Grant no.20JHQ016)the National Social Science Fund of China(Grant no.17BGJ059)。
文摘We developed a multinomial-logit-based stochastic user equilibrium(MNL SUE)model incorporating time value of cargo to investigate future proportions of cargo flow through the Northeast Passage(NEP)and the Suez Canal Route between representative ports.We studied navigation during the ice-free and ice-covered seasons using sea ice projections for 2070 based on 1991–2021 NEP ice data.Sailing distance and time between selected ports are lower via the NEP than the Suez Canal Route.Under the scenario of year-round operation of the NEP,the proportion of cargo flow through the NEP is estimated to be 68.5%,which represents considerable commercial potential.Proportions are higher for the ice-free season and for ports at high latitudes.We also assessed flow under different scenarios.Under the scenario of fuel price increase,proportion of flow through the NEP in the ice-covered season is expected to increase.If time value is ignored,flow through the NEP is expected to increase all year round.If shippers become more cost-conscious,flow through the NEP is also expected to increase.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61901216,61631020 and 61827801the Natural Science Foundation of Jiangsu Province under Grant BK20190400+1 种基金the open research fund of National Mobile Communications Research Laboratory,Southeast University(No.2020D08)the Foundation of Graduate Innovation Center in NUAA under Grant No.KFJJ20190408.
文摘Unmanned aerial vehicles(UAVs)can be employed as aerial base stations(BSs)due to their high mobility and flexible deployment.This paper focuses on a UAV-assisted wireless network,where users can be scheduled to get access to either an aerial BS or a terrestrial BS for uplink transmission.In contrast to state-of-the-art designs focusing on the instantaneous cost of the network,this paper aims at minimizing the long-term average transmit power consumed by the users by dynamically optimizing user association and power allocation in each time slot.Such a joint user association scheduling and power allocation problem can be formulated as a Markov decision process(MDP).Unfortunately,solving such an MDP problem with the conventional relative value iteration(RVI)can suffer from the curses of dimensionality,in the presence of a large number of users.As a countermeasure,we propose a distributed RVI algorithm to reduce the dimension of the MDP problem,such that the original problem can be decoupled into multiple solvable small-scale MDP problems.Simulation results reveal that the proposed algorithm can yield lower longterm average transmit power consumption than both the conventional RVI algorithm and a baseline algorithm with myopic policies.
