) Liang Chen and Naoyuki Tokuda Computer Science Department, Utsunomiya University, Utsunomiya, Japan 321-8505 lchen@alfin.mine.utsunomiya-u.ac.jp, tokuda@cc.utsunomiya-u.ac.jp Abstract Exploiting a new distributed cooperative processing scheme where multiple processors cooperate in finding a global minimum, we have developed a new efficient maximum likelihood-based calculation method for multitarget motion analysis under a fixed networked multisensor environment. The marked improvement in computational efficiency and also in stability is achieved by replacing the well known Hungarian assignment algorithm [13, 11] with a much simpler sorting algorithm of O(N log N) and fusing the result with locally minimized average square errors. We have proved a theorem which asserts that an optimal data assignment matrices can best be given in terms of sorted bearing measurement data of targets. Embedding an optimal data association algorithm of O(N log N) into each of GausNewtons 's downhill ...

Efficient mechanisms for information sharing are important for parallel and distributed systems. In parallel cluster systems and distributed systems where communication overhead is high, reducing communication is crucial to get high performance. In open and changing environments, dynamic adaptation is crucial to achieve good performance. We proposed a dynamic adaptation scheme for distributed information sharing. The system monitors the access pattern to a shared data, and accordingly adjusts itself in an adaptive manner. This paper describes an improvement of the scheme. The server monitors the work load in the whole system, and divides itself (or merges itself with another server replica) dynamically to distribute and balance the managing load accordingly, so that the system reorganizes and reconfigures itself dynamically. The results of experiments proved that our reconfiguration scheme is indeed effective. Keywords: Distributed Information Sharing, Distributed Shared Memory, Dynam...