IEEE802.16e is the major global cellular wireless standard that enables low-cost mobile Internet application. However, existing handover process system still has latency affects time-sensitive applications. In this pa...IEEE802.16e is the major global cellular wireless standard that enables low-cost mobile Internet application. However, existing handover process system still has latency affects time-sensitive applications. In this paper, the handover procedures of 802.16e and Fast Handover for Hierarchical MIPv6 (F-HMIPv6) are reconstructed to achieve a better transmission performance. The concept of cross layer design is adopted to refine the existing handover procedure specified in 802.16e MAC layer and F-HMIPv6. More specifically, layer2 and layer3 signaling messages for handover are analyzed and combined/interleaved to optimize the handover performance. Extensive simulations show that the proposed scheme in this paper is superior to the other scheme proposed by IETF.展开更多
With the increasing of civil aviation business,flight delay has become a key problem in civil aviation field in recent years,which has brought a considerable economic impact to airlines and related industries.The dela...With the increasing of civil aviation business,flight delay has become a key problem in civil aviation field in recent years,which has brought a considerable economic impact to airlines and related industries.The delay prediction of specific flights is very important for airlines’plan,airport resource allocation,insurance company strategy and personal arrangement.The influence factors of flight delay have high complexity and non-linear relationship.The different situations of various regions and airports,and even the deviation of airport or airline arrangement all have certain influence on flight delay,which makes the prediction more difficult.In view of the limitations of the existing delay prediction models,this paper proposes a flight delay prediction model with more generalization ability and corresponding machine learning classification algorithm.This model fully exploits temporal and spatial characteristics of higher dimensions,such as the influence of preceding flights,the situation of departure and landing airports,and the overall situation of flights on the same route.In the process of machine learning,the model is trained with historical data and tested with the latest actual data.The test result shows that the model and this machine learning algorithm can provide an effective method for the prediction of flight delay.展开更多
文摘IEEE802.16e is the major global cellular wireless standard that enables low-cost mobile Internet application. However, existing handover process system still has latency affects time-sensitive applications. In this paper, the handover procedures of 802.16e and Fast Handover for Hierarchical MIPv6 (F-HMIPv6) are reconstructed to achieve a better transmission performance. The concept of cross layer design is adopted to refine the existing handover procedure specified in 802.16e MAC layer and F-HMIPv6. More specifically, layer2 and layer3 signaling messages for handover are analyzed and combined/interleaved to optimize the handover performance. Extensive simulations show that the proposed scheme in this paper is superior to the other scheme proposed by IETF.
基金supported by the National Natural Science Foundation of China(61871046).
文摘With the increasing of civil aviation business,flight delay has become a key problem in civil aviation field in recent years,which has brought a considerable economic impact to airlines and related industries.The delay prediction of specific flights is very important for airlines’plan,airport resource allocation,insurance company strategy and personal arrangement.The influence factors of flight delay have high complexity and non-linear relationship.The different situations of various regions and airports,and even the deviation of airport or airline arrangement all have certain influence on flight delay,which makes the prediction more difficult.In view of the limitations of the existing delay prediction models,this paper proposes a flight delay prediction model with more generalization ability and corresponding machine learning classification algorithm.This model fully exploits temporal and spatial characteristics of higher dimensions,such as the influence of preceding flights,the situation of departure and landing airports,and the overall situation of flights on the same route.In the process of machine learning,the model is trained with historical data and tested with the latest actual data.The test result shows that the model and this machine learning algorithm can provide an effective method for the prediction of flight delay.
