The purpose of fast handover for MIPv6 is to eliminate the latency. Unfortunately, anticipation of fast handover does not guarantee that mobile nodes can always have enough time to exchange messages for fast handover if those mobile nodes move with high speed, such as mobile IP TV with more than 80Km/h speed. Most previous works to improve the fast handover for MIPv6 have been focused on how to make a reliable anticipation. In this paper, we propose an early binding fast handover (EBFH) that considers high-speed moving mobile nodes. The proposed EBFH can remarkably reduce unreliability of the anticipation for highspeed mobile nodes.

A new parallel annealing scheme, stepwise-overlapped parallel annealing, is proposed. This can provide a massive speedup using a multiprocessor system with a large number of processors. It decomposes the annealing process by means of Markov chains. The annealing scheme of the systolic algorithm proposed by Aart et al. is improved. The improved annealing schedule keeps a good temperature profile even when a large number of processors are used. The communication pattern is also enhanced. The new parallel annealing algorithm is applied to floorplan design problems. Experimental results show that the new parallel annealing algorithm is highly effective for a large number of processors. The experimental results of the proposed algorithm are compared with those of other parallel annealing algorithms and the distributed genetic algorithm.

Abstract This paper proposes a parallel annealing algorithm, called step‐wise‐overlapped parallel annealing, that can provide a massive speed‐up utilizing a multiprocessor system with a large number of processors. We improve the parallel annealing scheme of the systolic algorithm that was proposed by Aart et al. Instead of the temperature decrement at each subchain, it decides the decrement ratio at the start of each Markov chain using the standard deviation of the cost distribution in the previous Markov chain of the full length. Thus the improved annealing schedule keeps a good temperature profile even with a large number of processors. We also enhance the communication pattern. The new parallel annealing algorithm has a simple communication pattern and thus less communication overheads. The decomposition strategy of this parallel annealing algorithm is independent of application problems. Experimental results of the step‐wise‐overlapped parallel annealing algorthm for the travelling salesman problems show high efficiencies even when a large number of processors are used; it produces near optimal solutions with a speedup of 70.8 by using 128 processors. It can be implemented efficiently on a message‐passing multiprocessor system with a large number of processors, such as a hypercube computer.