Efficient memory-bounded search methods
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A pervasive computing environment consists typically of a large heterogeneous collection of networked devices which can acquire and reason on context information. Embedded devices are used extensively in pervasive environments but they face some key challenges. Common path searching algorithms like A* Search can have exponential number of node expansions. In this paper, we describe a special variant of this problem called Multiple Objective Path Search (MOPS) and propose a memory bounded solution to implement it in a pervasive environment. Experimental results show that an efficient path with 40-60 times less node expansions can be obtained with the proposed solution.