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This paper introduces β-BGR, a novel geographic routing protocol for 3-D wireless sensor networks with β-type learning automata. In our protocol, the data packets are forwarded toward the destination, and nodes which hear the packet compete for becoming the next hop. A new recovery strategy with β-type learning automata is presented for the case of empty forwarding area. The β-type learning automata are performed to coordinate adaptively the forwarding area, which is oriented toward the destination location, and its dimension ensures that all nodes within it can mutually communicate with each other sensor node. Then, the efficiency of the β-BGR is shown through several simulation results under some 3-D environments.

This paper presents a novel learning automaton, βtype, which consists of 2-state Bayesian estimators. The β-type learning automaton is presently among the fastest learning automata known, which was proposed in our earlier works. However, compared with the βtype learning automaton and the conventional learning automata, the β-type learning automaton deteriorates from the viewpoint of memory usage and other resources, for example, since computational and energy resources of some applications are limited, such as the wireless sensor networks, reducing memory footprint and performance optimization are very important issues. So, in this study, we propose the β-type learning automaton with minimum resources, 2-state Bayesian estimators. Then, the efficiency of proposed β-type learning automaton is shown through several simulation results under some random environments.

the problem, a relocation protocol by an object reloMobile Cache Protocol (MCP) was proposed as a relocation protocol of a replicated object i n a widely distributed object system. MCP has four basic features; relocating a replicated object, 2 optimistic update methods, object reservation and object sharing. To calculate relocation function, M C P uses processing time of the object at a candidate sate and predicted network delay between the client and the candidate. Thus, a client observes network status to eliminate the ambiguity. B u t the observation of the entire network may cause overhand and undesirable traffic. This paper proposes some solutions for the problem, i.e., collecting processing time information of partial network and probing delay by preceding ping. Though designed for a distributed object based system, MCP also can be applied to dynamic web caching. Evaluation using DEC web trace shows the effectiveness of these strategies.

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