Munenori Kai

AgentSphere is a platform for an autonomous parallel distributed processing system based on strong migration mobile agent system. In general, it is very difficult to manage load balance and effectiveness of total processing performance on parallel distributed processing system. Our approach is that mobile agents help us to perform effective parallel distributed processing by agents' autonomy. In our conventional AgentSphere, one has to describe all of agent's code necessary to functions of it by oneself. In this paper, we propose a mechanism for creating a new agent by using various functional agents, which have been prepared on the AgentSphere network a priori. According to this mechanism, when a user describe an agent's source code, one can write it easily and effectively without writing all of its code by means of selecting existing functional agents and delegating them to process the parts of functions.

Recently, the necessity for parallel programming has been increased with the rapid spread of multicore/multiprocessor systems. However, it is difficult for a programmer to create a highly-effective and high-performance parallel program. So, we are developing the automatic translator from C programs to parallel programs using MPI(Message Passing Interface). In our conventional automatic parallelism analysis of C program with pointer variables, it was able to analyze the data dependencies of only the pointer variables declared explicitly in the code. In this research, we have first applied the Shape analysis to C programs with pointer variables for getting to know the form of the recursive data structures which will be allocated and constructed dynamically at the time of execution. Then, using the result of the analysis, we can analyze the data dependencies of recursive data structures, such as linked list or binary tree structures, and detect more parallelism from C program.

In development of software which become larger-scale and more complicated every year, the importance of software test grows more and more. However, some domains where it is difficult to apply any software test exist. One of such domains is a GUI test. In order to conduct a GUI test, the method of "preparation of the complicated test code in con-sideration of various states", "the software test in manual operation", and "automating using expensive software" is taken. Since those methods are very high-cost, the method of describing a software test easily is desired. However, it is generally difficult to test to all the software containing GUI at the runtime. Then, in this paper, we propose runtime test approach for scenario branch applications with screen transitions like ATM screen or software installers. Proposed method can conduct software test for such specific applications easily and at low cost. It is also shown that most performance degradation by applying the proposed method to actual applications cannot be found.

In the AgentSphere network where a network situation is always changed, it becomes an important subject to perform parallel distributed processing using a number suitable for efficient behavior of the whole system of agents. In order that AgentSphere might make the cooperative behavior by agents efficient, a set of agents were generated by using AgentPool. In AgentPool, the user had to specify the number of agents to be generated, and it is fixed under their execution period. So, in this paper, the control mechanism of AgentPool was improved to change the number of agents dynamically, such that as the resource with which agents can work increased, the number of agents increased, and as the resource decreased, the number of agents decreased. Our proposed method not only makes resource requirements reasonable, but is useful for power consumption reduction of the whole system.

In recent years, since it seems that speed up of single processor or single core has been going up to the utmost physical limit, parallel processing by multicore or multiprocessor becomes the mainstream to make the processing speed much higher. On the other hand, developing the effectively parallelized programs is very difficult for software developers. So, it is expected that automatic parallelization of existing sequential programs is accomplished. In this paper, we propose a parallelism analysis method to find parallel structures from original sequential programs, and implement its dynamic parallel execution method for automatically parallelized C programs.

Since the task scheduling problems in the multiprocessor environments belong to the class of strong NP hard combinatorial optimization problem, the depth first search algorithms based on branch and bound(B&B) method are most effective to find an optimal solution. In order to reduce the search time with B&B method, it is the most important key to construct search algorithms with the way to bound many branches in the search space by more accurate lower bounds. However, it seems that there are no algorithms to create such lower bounds with consideration of processing system environments. In this paper, we propose three algorithms to create the lower bounds with consideration of number of processors, the lower bounds with consideration of processing time of successive tasks, and the lower bounds re-calculated in search process. Our experiments show that these algorithms give more accurate lower bounds and improve efficiency of search.

AgentSphere has been developed as an autonomous application framework for the heterogeneous parallel and distributed processing environment. AgentSphere runs on each machine, and provides a work field to mobile agents. As both AgentSpere and mobile agent are written in Java, there is a multithreading overhead problem in the case that application with very high parallelism is distributed onto fewer physical processing elements. So JavaVM has introduced Concurrent Utilities and ThreadPool for this problem, but they can work on only one JavaVM. In our research, we have developed AgentPool, which is similar to ThreadPool but available on multiple JavaVMs. We also report results of parallel processing of solving NQueens problem to show the performance of Agentpool.

Task scheduling is one of core technologies to improve the efficiency of parallel processing. A schedule is a solution of task scheduling problem, and make to cooperate the performance of parallel machines. The shorter length of schedule (makespan) is reduced, the more efficient parallel machines run. But, task scheduling problem is combinatorial optimization problem that has strongly NP hard computational complexity. Accordingly, it is necessary that to design algorithm taking account of more unforeseeable disposition in order to reduce makespan. Concerning to solve the problem, the disposition is considered with communication overhead between machines. In this paper, the authors propose new heuristic algorithms to optimize communication overhead. These are applied the focus to critical path of dependences and earliest allocation pattern of communications. The authors describe characteristics and processes of these algorithms, and our experiments show the effectiveness of them

When novice students learn programming, they usually start from basic notions and proceed to higher-level concepts. Teachers should provide materials adapted for students' progress: first, they should provide simple and easy programming language environment, then, shift to a practical one such as of Java, which can handle more sophisticated concepts. We developed a programming language Nigari and its environment. It is designed as a workbench at the first stage of programming lessons. The language specification of Nigari is a subset of Java: control structures are almost equal to Java, but no class declarations and no method declarations are required to write. It is intended that students can shift to Java ultimately without confusion. Moreover, the environment of Nigari has visualization feature that shows objects on a screen automatically. This feature fuels students' motivations to learn programming and helps their grasping basic concepts of "Objects". We applied Nigari, as an experiment, in a lesson of programming in Department of Computer Science, Waseda University. The course had been designed to use Java originally. We provided Nigari to students as their startup environment. Questionnaire in and after the course showed that many students favored its object visualization feature and some appreciated its language simplicity.