Distributed Memory Bounded Path Search Algorithms for Pervasive Computing Environments

被引：0

作者：

Sundar, Ancj Ramasamy ^{[1
]}

Tan, Colin Keng-Yan ^{[1
]}

机构：

[1] Natl Univ Singapore, Sch Comp, Dept Comp Sci, Singapore 119077, Singapore

来源：

PRICAI 2008: TRENDS IN ARTIFICIAL INTELLIGENCE | 2008年 / 5351卷

关键词：

Pervasive computing; context-aware services; network services; context reasoning; path finding; memory bounded search;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：394 / 404

页数：11