text: The present invention relates to a network system, a radio communication device, and a radio communication method for acquiring and distributing information concerning the real world as well as to a computer program for the same. More specifically this invention relates to a network system, a radio communication device, and a radio communication method for collecting, on a network including a number of sensor nodes each having a sensor, a processing function, and a radio communication function distributed in a relatively wide area, data acquired by each sensor.
  More particularly the present invention relates to a network system in which a plurality of sensor nodes each having a traveling function forms an ad-hoc network topology by operating in the self-directive and dispersive state, a radio communication device, a radio communication method, and a computer program for the same, and more specifically to a network system in which a plurality of sensor nodes each having a traveling function forms an ad-hoc network topology by operating in the self-directive state and dispersive state without using positional information, a radio communication device, a radio communication method, and a computer program for the same.
  A network is formed by connecting a plurality of communication terminals via a communication line. For instance, on a computer network formed by connecting computers to each other, utilization of informational resources such as shared use, distribution, and distribution of information. Recently in association with technological development in the Internet or broad band networks, convenience in use of information and communication systems has substantially been improved. Further with distribution of mobile communication devices capable of being connected to the Internet such as a PDA (Personal Digital Assistance) or a mobile telephone, the ubiquitous network or ubiquitous computing capable of being used anywhere and allowing for access from a global space attracts social attentions.
  It is generally said, on the other hand, that there are still several unsolved problems in relation to acquisition or distribution of information concerning the real world such as acquisition of information concerning an environment dynamically changing from time to time or simultaneous acquisition of information in a wide area. To solve the problems, there are active research activities for development of the “sensor network” for dealing with various types of information concerning the real world.
  The sensor network is built by distributing a number of sensor nodes each having a sensor, a processing function and a radio communication function in a relatively wide area in the dispersive state. With the sensor network built as described above, data acquired by each sensor can be collected. Each of the sensor nodes operates basically in the self-directive and dispersive state, and therefore the sensor network is an ad-hoc communication system. Information acquired by one node is transferred, for instance, by means of the multi-hop transfer to a remote node. Therefore, if a network topology can be formed so that a larger communication area is provided by the same number of nodes, it would be efficient.
  Further, because the sensor node has the traveling function, the plurality of sensor nodes form a network topology in the self-directive and dispersive state, which enables provision of sensing information to users. For instance, in the COTS-BOTS (Refer to, for instance, http://www-bsac.eecs.berkeley.edu/projects/cotsbots) developed in University of California at Barkley, a sensor node is built in the state where the sensor node is integrated with a wheel-type of robot.
  As described above, if a network topology can be formed so that a larger communication area is provided by the same number of nodes, it would be efficient. Therefore, in the sensor network system in which a plurality of nodes each having the traveling function operate in the self-directive state, it is important to provide the technique for forming a dynamic network topology.
  For building a sensor network, initial setting is generally performed according to the following procedure:
  (1) installation of nodes
  (2) time synchronization among nodes
  (3) position measurement for each node
  A key point in the procedure is that position measurement is performed after sensor nodes are installed.
  In the field of ubiquitous computing, the technique for position measurement requiring a specific infrastructure is available, and this technique is referred to as the “Range Based” technique. In contrast, the technique for position measurement used in the sensor network is different from the above and is referred to as the “Range Free” technique.
  In the range-free position measurement technique, based on the assumption that some sensor nodes identify positional information thereof function as land marks respectively, each node measures a distance from each of the land marks. For instance, a node functioning as a land mark incorporates therein a positioning device such as a GPS (Global Positioning System). Other nodes can compute positions thereof by computing a distance to the land mark by using the number of hops or amplitude of electric wave to obtain more precise positional data. It is to be remarked that completion of installation of nodes is a presupposition of execution of position measurement.
  In the sensor network system, if a network topology can be formed so that a larger communication area is provided by the same number of nodes, it would be efficient. The term of “topology” as used herein indicates the state where all nodes can be connected to each other by means of the communication procedure such as multi-hopping. Namely the topology indicates the single connected network.
  The method of forming a network topology insuring connectivity between sensor nodes is largely classified to the static topology forming method based on the preposition that each sensor node does not travel, and to the dynamic topology forming method based on traveling of each sensor node having a traveling function.
  The static topology forming method includes a method in which sensor nodes are scattered at a high density, a method in which sensor nodes are manually installed, and the like.
  For instance, when position measurement is performed in an area not allowing for easy access by a man such as a mountain or a wood, sensors are scattered in the object field (for instance, several tens of thousands of inexpensive and minute sensor nodes are scattered from a flying airplane), and each of the sensors are used as a node for a network to treat sensing data (Refer to FIG. 14). Sensing data detected by each discrete node is extracted via an ad-hoc network formed by the nodes by means of the multi-hop transfer.
  As one of the most sophisticated sensor networks belonging to the type as described above, the University of California at Berkley has proposed the “SmartDust” (Refer to, for instance, http://www-bsac.eecs.berkley.edu/˜warneke/SmartDust/index.html). In the research and development trend which started from the “SmartDust” project, most of the research projects for the sensor network currently being conducted assume an environment in which a density of sensor nodes is high. In an environment in which nodes are sufficiently close to each other, it is not necessary to take into considerations the connectivity between the nodes.
  However, most of applications for sensor networks actually used are not as described above, and a density of nodes is rather low in the networks. In addition, various restrictions are conceivable when it is actually tried to scatter sensor nodes at a high density in the real society. For instance, it is impossible to scatter sensor nodes from a flying airplane in an area where there are many buildings and residences close to each other. Further even if it is tried to scatter a number of sensor nodes, it is impossible to scatter the sensor nodes manually.
  In most of sensor networks currently used for monitoring environmental conditions, sensor nodes are installed manually. In this case, it is required to provide each sensor node checking the connectivity, so that the work load is very large. This method may be best suited when there are only several nodes, but in a case where there are several hundreds, several thousands sensor nodes or more in all, it is impossible to manually install the sensor nodes. It is not realistic to select an area not allowing for easy access by men as a target field. Further to improve the efficiency of a topology, it is required to install sensor nodes grasping the topological feature of the field as a whole, and this is also difficult.
  There have been filed several patent applications relating to a sensor network or a sensor collection system in which a topology is formed statically (Refer to, for instance, Japanese Patent Laid-open No. 2004-260526 and Japanese Patent Laid-open No. 2003-4497).
  On the other hand, attentions to a method for dynamically forming a network topology using nodes each having a traveling means are still not so high in the field of network designing, but there are several examples of research and development activities in the field of robotics.
  In most of the techniques for dynamically forming a network topology, generally it is assumed that a radio wave area is sufficiently larger as compared to the sensing area, so that the most important desire in the techniques is optimization of the sensing area. The connectivity is the so-called life line for a traveling node in remote operations, and therefore it is required to form a topology taking into consideration not only the sensing area but also the connection area. For instance, in sensing environmental information or the like, sometimes it is required to acquire samples in a certain area providing credible data in place of performing sampling in the entire area.
  Further there is a study as to which node is to be activated in a sensor network with the high density in consideration to the connectivity and the sensing area (Refer to, for instance: “The Coverage Problem in a Wireless Sensor Network”, C. -F. Huang and Y. -C. Tseng (In Second Workshop on Sensor Networks and Applications (WSNA), September 2003) “Unreliable Sensor Grids: Coverage, Connectivity and Diameter”, Shakkottari S, R. Srikant, and N. Shroff (In Proceesings of the IEEE Infocom, March 2003) “Integrated Coverage and Connectivity Configuration in Wireless Sensor Networks”, X. Wang, G. Xing, Z. Zhang, C. Lu, R. Pless, and C. Gill (In Proceedings of the ACM Symposium on Networked Embedded Systems (SenSys, 03), November 2003)).
  In the techniques, it is assumed that each node previously identifies positional information thereof. As described above, most of the position measurement techniques are based on the premise that the techniques are used in the state where a topology has been established, so that compatibility of the techniques with the established topologies is rather poor. Further with the technique based on the premise that positional information is available, it is extremely difficult to generate a topology ensuring the connectivity. For, in the actual society, an expensive system such as the GPS is required for acquiring positional information with high precision. Further there are many objects interfering radio wave, and further such a system assumes an idealistic environment in a two-dimensional space, so that formation of a topology in a three-dimensional space is further difficult.
  In other words, in the sensor network system in which a topology is formed statically, there is the problem relating to installation of sensor nodes. On the other hand, in a case where a topology is formed dynamically, it is possible to overcome the problem relating to installation of sensor nodes because each of the sensor nodes used in the system has a traveling function, but there is still a program in a process of position measurement. It is desired that each sensor node has a device for acquiring positional information such as a GPS, but in that case the cost for the system is very high. For the reasons described above, we consider that the method, in which a network topology is dynamically formed without requiring each sensor node having the traveling function to have any positional information, is more preferable.