In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management str...In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.展开更多
Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primari...Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primarily focuses on identifying the maximum tolerated dose(MTD),therapies involving targeted and immune agents facilitate the identifica-tion of an optimal biological dose combination(OBDC)by simultaneously evaluating both toxicity and efficacy.Cur-rently,most approaches to determining the OBDC in the literature are model-based and require complex model fittings,making them cumbersome and challenging to implement.To address these challenges,we developed a novel model-as-sisted approach called uTPI-Comb.This approach refines the established utility-based toxicity probability interval design by integrating a strategically devised zone-based local and global candidate set searching strategy,which can effectively optimize the decision-making process for two-agent dose escalation or de-escalation in drug combination trials.Extensive simulation studies demonstrate that the uTPI-Comb design speeds up the dose-searching process and provides substantial improvements over existing model-based methods in determining the optimal biological dose combinations.展开更多
Content distribution in large-scale vehicular ad hoc networks is difficult due to the scalability issue. A message may need to be carried by several vehicles till it reaches the destination. To select an appropriate n...Content distribution in large-scale vehicular ad hoc networks is difficult due to the scalability issue. A message may need to be carried by several vehicles till it reaches the destination. To select an appropriate next-hop carrier, the current carrier should ex- change control messages with a large number of vehicles encountered, and thus the pure ad hoc solution is not scalable. In this paper, we introduce a hybrid-network solution. We first divide the area into regions, and select a hot spot in each region to install a road-side unit （RSU）. RSUs can coordinate message exchanges between vehicles, and storage devices are used to temporarily hold a message waiting for the next-hop carrier. The RSUs and the vehicles traveling between them construct an overlay store-car- ry-and-forward content distribution network. Two types of vehicles exist, one with fixed mobility patterns such as buses, and the other with random patterns such as taxis. Considering one or both types of vehicles, utility-based optimization problems can be formulated to find the optimal routing solutions. Using the bus and taxi traces of Shanghai city, we demonstrate the effectiveness of the hybrid framework in terms of delivery delay, delivery ratio and overhead ratio.展开更多
基金supported by the National Natural Science Fund of China under Grant No. 61472097the Education Ministry Doctoral Research Foundation of China (20132304110017)the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation
文摘In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.
基金This work was supported by the Natural Science Foundation of Anhui Province(2022AH050703)the National Natural Science Foundation of China(11671375).
文摘Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primarily focuses on identifying the maximum tolerated dose(MTD),therapies involving targeted and immune agents facilitate the identifica-tion of an optimal biological dose combination(OBDC)by simultaneously evaluating both toxicity and efficacy.Cur-rently,most approaches to determining the OBDC in the literature are model-based and require complex model fittings,making them cumbersome and challenging to implement.To address these challenges,we developed a novel model-as-sisted approach called uTPI-Comb.This approach refines the established utility-based toxicity probability interval design by integrating a strategically devised zone-based local and global candidate set searching strategy,which can effectively optimize the decision-making process for two-agent dose escalation or de-escalation in drug combination trials.Extensive simulation studies demonstrate that the uTPI-Comb design speeds up the dose-searching process and provides substantial improvements over existing model-based methods in determining the optimal biological dose combinations.
文摘Content distribution in large-scale vehicular ad hoc networks is difficult due to the scalability issue. A message may need to be carried by several vehicles till it reaches the destination. To select an appropriate next-hop carrier, the current carrier should ex- change control messages with a large number of vehicles encountered, and thus the pure ad hoc solution is not scalable. In this paper, we introduce a hybrid-network solution. We first divide the area into regions, and select a hot spot in each region to install a road-side unit （RSU）. RSUs can coordinate message exchanges between vehicles, and storage devices are used to temporarily hold a message waiting for the next-hop carrier. The RSUs and the vehicles traveling between them construct an overlay store-car- ry-and-forward content distribution network. Two types of vehicles exist, one with fixed mobility patterns such as buses, and the other with random patterns such as taxis. Considering one or both types of vehicles, utility-based optimization problems can be formulated to find the optimal routing solutions. Using the bus and taxi traces of Shanghai city, we demonstrate the effectiveness of the hybrid framework in terms of delivery delay, delivery ratio and overhead ratio.
