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This paper analyzes and compares different incentive mechanisms for a master to motivate the collaboration of smartphone users on both data acquisition and distributed computing applications. To collect massive sensitive data from users, we propose a reward-based collaboration mechanism, where the master announces a total reward to be shared among collaborators, and the collaboration is successful if there are enough users wanting to collaborate. We show that if the master knows the users' collaboration costs, then he can choose to involve only users with the lowest costs. However, without knowing users' private information, then he needs to offer a larger total reward to attract enough collaborators. Users will benefit from knowing their costs before the data acquisition. Perhaps surprisingly, the master may benefit as the variance of users' cost distribution increases.To utilize smartphones' computation resources to solve complex computing problems, we study how the master can design an optimal contract by specifying different task-reward combinations for different user types. Under complete information, we show that the master involves a user type as long as the master's preference characteristic outweighs that type's unit cost. All collaborators achieve a zero payoff in this case. If the master does not know users' private cost information, however, he will conservatively target at a smaller group of users with small costs, and has to give most benefits to the collaborators.If V < n 0 C 0 , then the master's announced total reward R is also smaller than n 0 C 0 to make a profit. This reward is not enough to compensate even n 0 users with smallest costs, thus no users will join. Regarding this, the master will not seek users' collaboration in Stage I

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Most of current video retrieval systems use video transfer protocols such that servers simply transmit video packets in the same rate as clients play them. If any packets are corrupted during transmission, they will be lost and cannot be recovered by retransmission. In video retrieval systems, howevel; the video data are stored in servers and clients can prefetch them prior to playing. So, it might be possible for the video retrieval systems to make corrupted video packets retransmitted before play-out dead line. But the application of existing reliable protocols causes problems such that, i f a packet does not arrives before the dead line due to retransmission, the packets following it will not be delivered to the upper layer even if they have already arrived.In this papel; we proposed a new video transfer protocol for video retrieval systems over ATM network, which provides the video data prefetch, the jlow control for video buffel; the selective retransmission with skipping function for video packets late for the play-out dead line, and the resynchronaization function for video buffeel: We have implemented an experimental system using our protocol and evaluated the pelformanee. The results of performance evaluation shows that the proposed protocol decreases the number of unplayed video data to less than 1/70 compared with the conventional non-retransmission protocol when random bit errors with BER of I O p 6 are inserted in an ATM network. I~t r~d u c t i~~Recently, there are many studies on video retrieval systems, such as Video-on-Demand systems, in which clients retrieve video data stored in servers through networks. Most of these systems use a video transfer protocol such that servers simply transmit video packets in the rate corresponding to the playing rate in clients[ 1] [2]. If any packets are corrupted during the transmission, they will be lost and cannot be recovered by retransmission. The main reasons for adopting such a non-reliable protocol are as follows. First, video packets must be delivered before the play-out dead line expires, and it is considered that the retransmission will not satisfy this requirement. Secondly, it is considered that, in order to realize high speed video transfer, a simple protocol will be appropriate for reducing the processing overhead of protocols.In video retrieval systems, however, video data are stored in servers and it is possible that clients prefetch them prior to playing. This feature is different from video conference systems in which video data are generated in a real time manner. So, for video retrieval systems, it is possible to arrange time enough for the retransmission before the playout. Moreover, resulting from the progress of hardware and software technologies, some software for reliable protocols with packet retransmission attains high throughput over 100 Mbps [3]. Therefore, it is considered that video retrieval systems can recover corrupted packets by retransmission, using buffer introduced for prefetching video data. So far, there are some research ...

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