An inter-vehicle communication system, called vehicular ad hoc network (VANET), is one of the most promising applications of a mobile ad hoc network (MANET). One of the important issues in VANET is scalability. Compared with topology-based routing protocols, a routing protocol using position information may alleviate the issues of scalability or control overhead. Car navigation systems using a global positioning system (GPS) are widespread, and position-based routing is a useful approach in VANETs. A next-hop forwarding method is a type of position-based routing protocol, wherein a selection scheme for the next-hop node is very important. In this paper, we propose a novel selection scheme for the next-hop node in the next-hop forwarding method in VANET. In the proposed scheme, a new link metric, expected progress distance, is introduced in order to consider both forwarding distance and transmission quality of the wireless link. We evaluate the performance of our proposed scheme, and show that it can achieve much higher throughput and a better packet delivery ratio than existing conventional schemes.

VANET is an application of a mobile ad hoc network to inter-vehicle communication. Each vehicle is aware of its position information by GPS or other methods. Position-based routing is a useful approach in VANET. The Position-based routing protocol can be classified roughly into a next-hop forwarding method and a directed flooding method. We evaluate performance of both methods by analysis and simulation and compare them in this paper.

In this paper, we describe an outline of “Procedure based help desk system”.

In the case of intelligent work that requires sophisticated judgments of experienced workers, if the know-how of those experienced workers could be reused then it is expected that even inexperienced workers would be able to perform similar work. This paper describes the "IntelligentWorkFlow System" that uses the know-how of experienced workers by focusing on the sequence of procedures in job. It stores details of the work processes as a "work-log", and discovers the "know-how" of the job by analyzing the stored work-log. Since this system accumulates know-how through practical work and its know-how acquisition method doesn't focus on application-dependent data, it is easy to acquire the know-how without depending on the particular application.