Various kinds of content replication strategies in pure P2P networks have recently been examined. However, such strategies have not been thoroughly considered in hybrid P2P networks. In a hybrid P2P network, the target content can easily be found because there is a server that controls each peer and its content. Therefore, it is important to decrease futile storage resource consumption, since the data search cost through the network is relatively small. This paper proposes an effective content replication strategy that takes into account storage capacity restrictions. In brief, this method restricts the number of contents replicas possessed by a peer using threshold-based control by relocating or deleting excess replicas. Furthermore, the effectiveness of the proposal is evaluated using computer simulations.

On-line object tracking (OLOT) has been a core technology in computer vision, and its importance has been increasing rapidly. Because this technology is utilized for battery-operated products, energy consumption must be minimized. This paper describes a method of adaptive frame-rate optimization to satisfy that requirement. An energy trade-off occurs between image capturing and object tracking. Therefore, the method optimizes the frame-rate based on always changed object speed for minimizing the total energy while taking into account the trade-off. Simulation results show a maximum energy reduction of 50.0%, and an average reduction of 35.9% without serious tracking accuracy degradation.

Multiple context-free grammar (MCFG) is an extension of context-free grammar (CFG), which generates tuples of words. The expressive power of MCFG is between CFG and context-sensitive grammar while MCFG inherits good properties of CFG. In this paper, we introduce weighted multiple context-free grammar (WMCFG) as a quantitative extension of MCFG. Then we investigate properties of WMCFG such as polynomial-time computability of basic problems, its closure property and expressive power.