Khaireel A. Mohamed

Versioning Tree Structures by Path-Merging

We propose path-merging as a refinement of techniques used to make linked data structures partially persistent. Path-merging supports bursts of operations between any two adjacent versions in contrast to only one operation in the original variant. The superiority of the method is shown both theoretically and experimentally. Details of the technique are explained for the case of binary search trees. Path-merging is particularly useful for the implementation of scan-line algorithms where many update operations on the sweep status structure have to be performed at the same event points. Examples are algorithms for planar point location, for answering intersection queries for sets of horizontal line segments, and for detecting conflicts in sets of 1-dim IP packet filters. Subject Classifications: E.1 [ Data ]: Data Structures --- trees; E.2 [ Data ]: Data Storage Representations --- linked representations; F.2.2 [ Analysis of Algorithms and Problem Complexity ] Nonnumerical Algorithms and Problems --- Geometrical problems and computations.

A New Output-Sensitive Algorithm to Detect and Resolve Conflicts in Internet Router Tables

Packet Alters are rules for classifying packets based on their header fields. In order to avoid ambiguities in packet classification, the set of filters in a router table must be conflict-free, i.e. for any incoming packet p, there must be a unique best matching filter which applies to p. We present the first output-sensitive solution for the offline version of the conflict detection and resolving problem for 1-dimensional arbitrary range filters under the most-specific tie breaking rule. The algorithm achieves a worst case time complexity of O(n log n) and uses space O(n). Instead of reporting and resolving all pairs of conflicting filters, we straight away report those resolve filters that are necessary to make the set conflict-free.

A knowledge-based technique for constraints satisfaction in manpower allocation

We show that knowledge-based techniques are as effective as mathematical techniques when satisfying constraints for solving manpower allocation problems. These techniques can be used to fulfill the corresponding local and global constraints based on the dynamic programming algorithm. It uses tools borrowed from genetic and simulated annealing algorithms, and fuzzy logic methodologies. The schedules produced by our algorithm match the best schedules produced by human experts.

Knowledge-Based Techniques for Constraints Satisfaction in Resource Allocation Problems

Knowledge-based techniques are as effective as mathematical techniques for satisfying constraints in manpower resource allocation (MRA) problems. Our knowledge-based techniques allow direct implementation for logical reasoning, reduce efforts in setting up and interpreting rules of constraints, fair well in giving correct solutions, and are adaptable to human rules. This class of problems arises in the management of manpower for organisations that provide round-the-clock services, requiring special expertise and experience to ensure that resultant rosters optimally match the skills of the available manpower resources to the various conditions and requisites of the deployment posts.