Recently, there have been studies on space and time priority queues, where space priorities are given to a class of packets that are sensitive to loss, and time priorities to another class of packets that are sensitive to delay. However, these studies have been restricted to such models with push-out space priorities. In this paper, we extend the studies to the space and time priority M/G/1 model with partial-buffer-sharing (PBS) space priorities, where the whole buffer is divided into two regions: one is shared by packets of all classes and the other is dedicated only for packets of the higher space-priority class. Since the PBS space-priority mechanism can be implemented more readily in communication systems than the push-out one, there have been a lot of contributions on PBS space-priority queues. However, there are no contributions on space and time priority queues with PBS space priorities. To analyze the proposed queueing model, we first study the probabilistic structure of the service time of a packet, which is more involved to analyze than the push-out alternative because it may be divided into three different regimes: a regime (S-period) from the beginning of the service until the shared buffer region becomes full, a second one (P-period) from the end of the S-period until the whole buffer becomes full, a third one (F-period) from the end of the P-period until the end of the service. Using the distributions of the S-, P-, F-periods, we then construct and analyze the embedded Markov chain and the corresponding semi-Markov process governing the system state, and also derive system performance measures such as expected sojourn times and loss probabilities of different priority classes of packets. In numerical examples, we finally explore the effect of the shared buffer size, which is a major system control parameter of PBS priority queues, and the distributions of the service times of packets of different classes on the system performance measures.

PURPOSES : The purpose of this study is to identify the beneficiaries of car-sharing that can utilize autonomous car-sharing services when they are introduced. METHODS : This study was conducted in two stages. The first step was to analyze the characteristics of shared car usage by region and rental time using t-Ttest. The second step was to analyze the beneficiaries of autonomous car-sharing services if they are introduced. The beneficiaries were derived using parking time and survey data. RESULTS : Car-sharing behavior showed statistically different usage characteristics by region and rental period. However, the distance traveled per trip for short trips was similar. When the autonomous car sharing service with free return and rental is introduced, 31% (Jeju) to 38% (Daejeon) of short-term renters and 50 to 52% of long-term renters are expected to benefit. CONCLUSIONS : When introducing autonomous car-sharing services, it is necessary to establish a shared car strategy that reflects the characteristics of car-sharing use by region and rental period. In particular, in Jeju Island, where the rental time is relatively longer than Daejeon, the introduction of autonomous car-sharing services will contribute to reducing the cost of shared vehicles in terms of cost.

This study explains an agricultural mobile commerce case using Oauth Based Real-Time Information Sharing Technique according to the growth of the agricultural e-commerce market. Considering the characteristics of the agricultural market, it can confirm differential values with the existing agricultural mobile commerce market according to the functions and characteristics of its technique. We compare variables for introducing agricultural mobile commerce with the existing mobile commerce. Trust through information sharing with real-timefarming diaries, suitability and perceived ease of use variables are positively influenced, but influence on completeness and authority of information variables are relatively insufficient. Through this, we explained differential values of agricultural mobile commerce and suggested an applicable business model.