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Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds

A comprehensive unifying view is provided and it is shown that both existing and novel algorithms can be derived from the MEP theory, encompassing both previously discovered bounds and new ones.
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On the Properties of All-Pair Heuristics

This work introduces a new property for heuristics called Δ-consistency, requiring adherence to the triangle inequality, and presents a method for transforming standard consistent heuristics to be Δ-consistent, showcasing its benefits through a synthetic example.
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On Parallel External-Memory Bidirectional Search (Extended Abstract)

This work presents a versatile PEM framework that integrates both uni- and bi-directional best-first search algorithms, and significantly enhances the capabilities of search algorithms for solving large-scale problems.
arXiv (opens in a new tab)

Bidirectional Bounded-Suboptimal Heuristic Search with Consistent Heuristics

This paper builds upon the state-of-the-art optimal bidirectional search algorithm, BAE*, designed for consistent heuristics, and introduces several variants of BAE* specifically tailored for the bounded-suboptimal context.
arXiv (opens in a new tab)

Anchor Search: A Unified Framework for Suboptimal Bidirectional Search

This work introduces a framework for suboptimal BiHS, called anchor search, and uses it to derive a parameterized family of algorithms, using pattern databases as differential heuristics (DHs) to construct F2F heuristics.
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HERO vs Zombie: Destroying Zombie Guests in Virtual Machine Environments

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Comparing Front-to-Front and Front-to-End Heuristics in Bidirectional Search

This paper theoretically and experimentally demonstrates that there is a great potential in using F2F heuristics implying that F1F BiHS is a promising area of future research.
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HERO vs. Zombie: Identifying Zombie Guests in a Virtual Machine Environment

A novel tool to optimize resource use by tracking down zombie machines: HERO (Host Environment Resource Optimization), which leverages multiple testing approaches and machine learning to assist system administrators in locating “zombie” machines.
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Bridging theory and practice in bidirectional heuristic search with front-to-end consistent heuristics

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Characterization and Prediction of QUIC's Performance Under Different Network Conditions

This work characterizes QU IC's performance and develops a predictive model, providing insights into the main parameters affecting QUIC's performance, such as loss, packet reordering, and latency.
IEEE (opens in a new tab)
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