A binary complete decision table with many-valued decisions is a table with n attributes and 2^(n) pairwise distinct rows filled with numbers from the set{0,1}.Each row of this table is labeled with a nonempty finite ...A binary complete decision table with many-valued decisions is a table with n attributes and 2^(n) pairwise distinct rows filled with numbers from the set{0,1}.Each row of this table is labeled with a nonempty finite set of decisions.For a given row of the table,the task is to find a decision from the set of decisions attached to the row.Such tables are generalizations of Boolean functions.They can also be viewed as representations of various problems related to systems of decision rules.In this paper,we consider three types of classes of binary complete decision tables with many-valued decisions,closed with respect to removal of columns and changing of decisions.For tables from these classes,we study the relationships between the minimum weighted depth of deterministic,nondeterministic,and(for one type of classes)strongly nondeterministic decision trees and the total weight of attributes attached to columns.Note that nondeterministic decision trees and strongly nondeterministic decision trees for decision tables can be interpreted as a way of representing the two types of systems of decision rules for these tables.展开更多
For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper leng...For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper length-detecting is a straightforward yet efficient solution. Binary search strategy can reduce the number of required hash detecting in the worst case. However, to assure the searching path correct in such a schema, either backtrack searching or redundantly storing some prefixes is required, leading to performance or memory issues as a result. In this paper, we make a deep study on the binary search, and propose a novel mechanism to ensure correct searching path without neither additional backtrack costs nor redundant memory consumptions. Along any binary search path, a bloom filter is employed at each branching point to verify whether a said prefix is present, instead of storing that prefix here. By this means, we can gain significantly optimization on memory efficiency, at the cost of bloom checking before each detecting. Our evaluation experiments on both real-world and randomly synthesized data sets demonstrate our superiorities clearly展开更多
基金supported by King Abdullah University of Science and Technology(KAUST).
文摘A binary complete decision table with many-valued decisions is a table with n attributes and 2^(n) pairwise distinct rows filled with numbers from the set{0,1}.Each row of this table is labeled with a nonempty finite set of decisions.For a given row of the table,the task is to find a decision from the set of decisions attached to the row.Such tables are generalizations of Boolean functions.They can also be viewed as representations of various problems related to systems of decision rules.In this paper,we consider three types of classes of binary complete decision tables with many-valued decisions,closed with respect to removal of columns and changing of decisions.For tables from these classes,we study the relationships between the minimum weighted depth of deterministic,nondeterministic,and(for one type of classes)strongly nondeterministic decision trees and the total weight of attributes attached to columns.Note that nondeterministic decision trees and strongly nondeterministic decision trees for decision tables can be interpreted as a way of representing the two types of systems of decision rules for these tables.
基金supported by the National Natural Science Foundation of China (Grant No. 61472130 and 61702174)the China Postdoctoral Science Foundation funded project
文摘For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper length-detecting is a straightforward yet efficient solution. Binary search strategy can reduce the number of required hash detecting in the worst case. However, to assure the searching path correct in such a schema, either backtrack searching or redundantly storing some prefixes is required, leading to performance or memory issues as a result. In this paper, we make a deep study on the binary search, and propose a novel mechanism to ensure correct searching path without neither additional backtrack costs nor redundant memory consumptions. Along any binary search path, a bloom filter is employed at each branching point to verify whether a said prefix is present, instead of storing that prefix here. By this means, we can gain significantly optimization on memory efficiency, at the cost of bloom checking before each detecting. Our evaluation experiments on both real-world and randomly synthesized data sets demonstrate our superiorities clearly
