Basis Token Consistency: A Practical Mechanism for Strong Web Cache Consistency

With web caching and cache-related services like CDNs and edge services playing an increasingly significant role in the modern internet, the problem of the weak consistency and coherence provisions in current web protocols is becoming increasingly significant and drawing the attention of the standards community [LCD01]. Toward this end, we present definitions of consistency and coherence for web-like environments, that is, distributed client-server information systems where the semantics of interactions with resource are more general than the read/write operations found in memory hierarchies and distributed file systems. We then present a brief review of proposed mechanisms which strengthen the consistency of caches in the web, focusing upon their conceptual contributions and their weaknesses in real-world practice. These insights motivate a new mechanism, which we call "Basis Token Consistency" or BTC; when implemented at the server, this mechanism allows any client (independent of the presence and conformity of any intermediaries) to maintain a self-consistent view of the server's state. This is accomplished by annotating responses with additional per-resource application information which allows client caches to recognize the obsolescence of currently cached entities and identify responses from other caches which are already stale in light of what has already been seen. The mechanism requires no deviation from the existing client-server communication model, and does not require servers to maintain any additional per-client state. We discuss how our mechanism could be integrated into a fragment-assembling Content Management System (CMS), and present a simulation-driven performance comparison between the BTC algorithm and the use of the Time-To-Live (TTL) heuristic.National Science Foundation (ANI-9986397, ANI-0095988

Cluster-based network proximities for arbitrary nodal subsets

The concept of a cluster or community in a network context has been of considerable interest in a variety of settings in recent years. In this paper, employing random walks and geodesic distance, we introduce a unified measure of cluster-based proximity between nodes, relative to a given subset of interest. The inherent simplicity and informativeness of the approach could make it of value to researchers in a variety of scientific fields. Applicability is demonstrated via application to clustering for a number of existent data sets (including multipartite networks). We view community detection (i.e. when the full set of network nodes is considered) as simply the limiting instance of clustering (for arbitrary subsets). This perspective should add to the dialogue on what constitutes a cluster or community within a network. In regards to health-relevant attributes in social networks, identification of clusters of individuals with similar attributes can support targeting of collective interventions. The method performs well in comparisons with other approaches, based on comparative measures such as NMI and ARI

LIPIcs, Volume 248, ISAAC 2022, Complete Volume

LIPIcs, Volume 248, ISAAC 2022, Complete Volum

Computation and Consistent Estimation of Stationary Optimal Transport Plans

Informally, the optimal transport (OT) problem is to align, or couple, two distributions of interest as best as possible with respect to some prespecified cost. A coupling that achieves the minimum cost among all couplings is referred to as an OT plan; the cost of the OT plan is referred to as the OT cost. Researchers in statistics and machine learning have expended a great deal of effort to understand the properties of OT plans and costs. The motivation for this work stems partly from the fact that, unlike many other divergence measures and metrics between distributions, OT plans and costs describe relationships between distributions in a manner that respects the geometry of the underlying space (by way of the specified cost). However, this advantage does not necessarily carry over when standard OT techniques are applied to distributions with specific structure. In the case that the two distributions describe stationary stochastic processes, the OT problem may ignore the differences in the sequential dependence of either process. One must find a way to make the OT problem account for the stationary dependence of the marginal processes. In this thesis, we study OT for stationary processes, a field that we refer to as stationary optimal transport. Through example and theory, we argue that when applying OT to stationary processes, one should incorporate the stationarity into the problem directly -- constraining the set of allowed transport plans to those that are stationary themselves. In this way, we only consider transport plans that respect the dependence structure of the marginal processes. We study this constrained OT problem from statistical and computational perspectives, with an eye toward applications in machine learning and data science. In particular, we develop algorithms for computing stationary OT plans of Markov chains, extend these tools for Markov OT to the alignment and comparison of weighted graphs, and propose estimates of stationary OT plans based on finite sequences of observations. We build upon existing techniques in OT as well as draw from a variety of fields including Markov decision processes, graph theory, and ergodic theory. In doing this, we uncover new perspectives on OT and pave the way for additional applications and approaches in future work.Doctor of Philosoph

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

Gestural extraction from musical audio signals

Conventional exploration of gestures normally associated with musical instruments can be a costly and intrusive process. This thesis presents a novel approach to gestural extraction which overcomes these problems. The motivation behind this research is that the result of gestural input can be heard and therefore extracted from the acoustic signal produced by a musical instrument. Therefore, the guiding principles of this work are taken from the human auditory system. The concept of temporal grouping, and the fact that any sound which reaches the inner ear is conveyed to the brain, are two features of the auditory system that are mimicked by the presented system. Pertinent definitions are proposed for the sections of the note envelope and musical instrument gestures are classified according to those responsible for excitation or control. The extraction of gestural information is dependent upon successful identification of note events. A note tracking system is presented which exploits the structure of a note in order to perform preliminary note onset detection. A backtracking function is employed to regress through auditory data, providing a means of assigning individual start points to each note harmonic. The note tracking system also records the end point of each note harmonic. Note information is validated by a bespoke musical comparison system which provides a means of comparing and evaluating different note detection methods. Information provided by the note tracking system is used to extract gestural information regarding oboe key presses and excitation (articulation) methods of string instruments. System tests show that it is possible to correctly distinguish between bowed and plucked notes with an 89% success rate, using only three discriminators associated with the onset of a note. In this thesis the foundations of a multifacetted gestural extraction system are presented with useful potential for further development

Topology Reconstruction of Dynamical Networks via Constrained Lyapunov Equations

The network structure (or topology) of a dynamical network is often unavailable or uncertain. Hence, we consider the problem of network reconstruction. Network reconstruction aims at inferring the topology of a dynamical network using measurements obtained from the network. In this technical note we define the notion of solvability of the network reconstruction problem. Subsequently, we provide necessary and sufficient conditions under which the network reconstruction problem is solvable. Finally, using constrained Lyapunov equations, we establish novel network reconstruction algorithms, applicable to general dynamical networks. We also provide specialized algorithms for specific network dynamics, such as the well-known consensus and adjacency dynamics.Comment: 8 page

Open semantic hyperwikis

Wikis are lightweight, community-editable, web-based hypertext systems, which can be described as a website that anybody can edit. From this collaborative base has grown significant efforts at large-scale knowledge management such as Wikipedia. Recently, ‘semantic’ wiki systems have been developed with typed links, such that the structure of nodes and links is analogous to an RDF graph of resources and arcs: a machineprocessable representation of the relations between articles which can form part of the web of linked data. Despite this, the hypermedia side of wiki systems has so far largely been constrained to the web model of simple embedded, unidirectional links. This research considers the hypertext origins of wiki systems, asks, and answers how the technologies developed during decades of hypertext research may be applied to better manage their document, and thus knowledge, structure. We present experimental evidence supporting the hypothesis that additional hypermedia features would be useful to wiki editors on both macro- and micro-scales. Quantitative analysis of editing logs from a large-scale wiki shows that hyperstructure changes form a substantial proportion of editing effort. Conversely, qualitative user studies show that individual user editing can be better supported by classical but since overlooked hypertext features such as first-class links and transclusion. We then specify an extensive model for a ‘open semantic hyperwiki’ system which draws from these fields, based around first-class links with support for transclusion and advanced functional link types, with defined semantics for the role of versioning and parametric nodes in the linked data world, while mindful to preserve the core simplicity that allows non-expert users to contribute. This is followed by a practical approach to its implementation in terms of an existing experimental modular wiki foundation, and the actual prototype implementation, which has been made available as open source software. Finally, we work through applying the system to a set of real-world use cases which are currently employing classic, non-semantic wiki software, and evaluate the implementation in comparison to a conventional semantic wiki in a user study.EThOS - Electronic Theses Online ServiceGBUnited Kingdo