Miracle-dz/UniFAR-FTUs huggingface dataset:
Protocols for End-To-End Reliability in Multi-Tier Systems

Modern Internet services exhibit the strong trend to be structured according to a three-tier, and in general multi-tier, system organization, which allows reflecting at both the software and hardware level the logical decomposition of applications. Even though the partitioning of the application into multiple tiers provides the potentialities to achieve high modularity and flexibility, the multiplicity and diversity of the employed components, and their interdependencies, make reliability a complex issue to tackle. As an example, in classical client-server environments, database systems represented the reliability backbone of mission critical services, ensuring consistent evolution of the state trajectory of business applications through the notion of atomic transactions. However, the fault-tolerance capabilities provided by transactional components, and, in broader sense, by traditional approaches to reliability, address issues restricted to specific subsystems involved in the end-to-end interaction. Hence, they are unable to tackle the wide spectrum of failure scenarios that can arise along the whole chain of components constituting a multi-tier system. The design of reliability solutions for Internet services is made even more challenging by the open, heterogeneous and inherently asynchronous nature of the Internet itself, which dramatically reduces the possibility to monitor and control the distributed components involved in a multi-tier application. Further, coupled with global access enabled by the Internet and with widespread diffusion of complex services, the urge for achieving high scalability and minimizing response times has accordingly grown. This has imposed stringent performance requirements on the underlying reliability mechanisms. This is precisely the focus of this thesis. Specifically, we introduce innovative protocols ensuring the e-Transaction (exactly-once Transaction) guarantees, namely a recent formalization of desirable end-to-end reliability properties for multi-tier systems in presence of crash failures. These protocols advance the state of the art in a twofold direction. From a practical perspective, they achieve unparalleled scalability levels, exhibit very limited overhead, thus revealing particularly attractive in the context of emerging large scale service delivery platforms. From a theoretical standpoint, our solutions can cope with purely asynchronous systems, where no assumption on the accuracy of
The spatial structure of genetic diversity under natural selection and in heterogeneous environments

This thesis deals with the spatial structure of genetic diversity. We first study a measure-valued process describing the evolution of the genetic composition of a population subject to natural selection. We show that this process satisfies a central limit theorem and that its fluctuations are given by the solution to a stochastic partial differential equation. We then use this result to obtain an estimate of the drift load in spatially structured populations.Next we investigate the genetic composition of a populations whose individuals move more freely in one part of space than in the other (a situation called dispersal heterogeneity). We show in this case the convergence of allele frequencies via the convergence of ancestral lineages to a system of skew Brownian motions.We then detail the effect of a barrier to gene flow dividing the habitat of a population. We show that ancestral lineages follow partially reflected Brownian motions, of whom we give several constructions.To apply these results, we adapt a method for demographic inference to the setting of dispersal heterogeneity. This method makes use of long blocks of genome along which pairs of individuals share a common ancestry, and allows to estimate several demographic parameters when they vary accross space. To conclude, we demonstrate the accuracy of our method on simulated datasets.
Exploring the role of peer feedback in teaching and learning

14 Introduction . 15 Theoretical Foundations of Peer Feedback . 16 A Conceptual Framework for Peer Feedback . 21 Key Factors Influencing Peer Feedback Practices . 24 Instructional Guidelines & Practical Implications . 32 Conclusion . 36 References . 38
Big Data Security Architecture using Split and Merge Method

Due to rapid growth of unstructured data in contemporary information world, there is an essence of big data infrastructure for many applications spread across domains, due to the different source information type and huge volume, data ingestion and data retrieval is important activity during this process data security is a vital to protect user data, in connection with this, authors proposed a big data security architecture using split and merge security method in big data environment using hadoop.This work will help Data security professionals and organizations implementing big data projects.
Ground and satellite-based radar observation comparisons: propagation of space-based radar signals

Propagation effects in rainfall are examined for a high-frequency space-based weather radar system via comparison with polarimetric ground radar observations. Simultaneous measurements were collected from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the National Center for Atmospheric Research (NCAR) S-band polarimetric radar (SPOL). Ground radar data was collected during the TExas and FLorida UNderflights (TEFLUN-B) experiment in August 1998 and the Large Biosphere-Atmosphere Experiment in Amazonia (LBA) in February 1999. A theoretical model is developed to estimate specific attenuation (/spl alpha/) in the vertical direction from specific differential phase (K/sub DP/) in the horizontal propagation direction. From this model PR attenuation is derived from ground-measured K/sub DP/ along the space radar beam. The total two-way path-integrated-attenuation (PIA) along the beam is then calculated which can also be used to determine an /spl alpha/-corrected PR return. Results indicate a significant level of attenuation in the space-radar during high rainfall events-as much as 12 dB when storm levels reach 50 dBZ near the surface. A comparison is also made between the /spl alpha/-corrected reflectivity and the PR corrected reflectivity found in the level 2 data products.
On the Consistency, Characterization, Adaptability and Integrity of Database Replication Systems

Since the appearance of the first distributed databases until the current modern replication systems, the research community has proposed multiple protocols to manage data distribution and replication, along with concurrency control algorithms to handle transactions running at every system node. Many protocols are thus available, each one with different features and performance, and guaranteeing different consistency levels. To know which replication protocol is the most appropriate, two aspects must be considered: the required level of consistency and isolation (i.e., the correctness criterion), and the properties of the system (i.e., the scenario), which will determine the achievable performance. Regarding correctness criteria, one-copy serializability is broadly accepted as the highest level of correctness. However, its definition allows different interpretations regarding replica consistency. In this thesis, we establish a correspondence between memory consistency models, as defined in the scope of distributed shared memory, and possible levels of replica consistency, thus defining new correctness criteria that correspond to the identified interpretations of one-copy serializability. Once selected the correctness criterion, the achievable performance of a system heavily depends on the scenario, i.e., the sum of both the system environment and the applications running on it. In order for the administrator to select a proper replication protocol, the available protocols must be fully and deeply known. A good description of each candidate is fundamental, but a common ground is mandatory to compare the different options and to estimate their performance in the given scenario. This thesis proposes a precise characterization model that allows us to decompose algorithms into individual interactions between significant system elements, as well as to define some underlying properties, and to associate each interaction with a specific policy that governs it. We later use this model as basis for a historical study of the evolution of database replication techniques, thus providing an exhaustive survey of the principal existing systems. Although a specific replication protocol may be the best option for certain scenario, as systems are dynamic and heterogeneous, it is difficult for a single protocol to continuously be the proper choice, as it may degrade or be unable to meet all requirements. In this thesis we propose a metaprotocol that supports several replication protocols which follow different replication techniques and may provide different isolation levels. With this metaprotocol, replication protocols can either work concurrently with the same data or be sequenced for adapting to dynamic environments. Finally we consider integrity constraints, which are extensively used in databases to define semantic properties of data but are often forgotten in replicated databases. We analyze the potential problems this may involve and provide simple guidelines to extend a protocol so that it notices and properly manages abortions due to integrity violations.
Estimating links of a network from time to event data

In this paper we develop a statistical method for identifying links of a network from time to event data. This method models the hazard function of a node conditional on event time of other nodes, parameterizing the conditional hazard function with the links of the network. It then estimates the hazard function by maximizing a pseudo partial likelihood function with parameters subject to a user-speciﬁed penalty function and additional constraints. To make such estimation robust, it adopts a pre-speciﬁed risk control on the number of false discovered links by using the Stability Selection method. Simulation study shows that under this hybrid procedure, the number of false discovered links is tightly controlled while the true links are well recovered. We apply our method to estimate a political cohesion network that drives donation behavior of 146 ﬁrms from the data collected during the 2008 Tai-wanese legislative election. The results show that ﬁrms afﬁliated with elite organizations or ﬁrms of monopoly are more likely to diffuse donation behavior. In contrast, ﬁrms belonging to technology industry are more likely to act independently on donation.
On the conceptualisation of the query refinement task

Purpose – To resolve the drawback in the existing methods for query refinement by using semantic technologies. Design/methodology/approach – The article introduces a conceptual space (ontology) in which a query refinement problem will be treated. In that space a query is modeled as a set of logic formulas, query refinement process is modeled as an inferencing process. The approach is focused on the positive conjunctive queries.Findings – This (re)opens a question about a need for a more semantic‐based indexing of documents in the traditional information retrieval in order to improve the overall retrieval performances. This experimental study has shown that the semantics arisen (emerged) from row documents has enough quality to enable building query refinement methods that outperform the most advanced syntactic‐driven methods. Consequently, one can imagine a more emergent‐semantic based indexing process that will retain the autonomy of web data, but will significantly increase the precision of the retrieva.
Ontology Population from Textual Document Sources for Environmental Management Domain based Lexical Patterns Technique

This study focuses on the approach of identifying semantic relationships from unstructured textual documents related to river water pollution from websites and proposes a lexical pattern technique to acquire the instances. This study has identified 10 types of concepts (entities), 10 object properties (or semantic relations) and twenty lexico-syntactic patterns have been identified manually, including one from the Hearst hyponym rules. The lexical patterns have linked 45 terms that have the potential as instances. Based on this study, it is believed that determining the lexical pattern at an early stage is helpful in selecting relevant term from a wide collection of terms from the corpus. However, the relations and lexico-syntactic patterns or rules have to be verified by domain expert before employing the rules to the wider collection in an attempt to find more possible rules. This study shows that background knowledge about the domain is essential to develop the TBox ontology diagram that serve as backbone of the domain ontology. This diagram is essential as guideline in discovering lexico-syntactic patterns therefore expedite the knowledge extraction process.
Optimizing Communication Cost in Distributed Query Processing

In this thesis, we take a complementary look to the problem of optimizing the time for communicating query results in distributed query processing, by investigating the relationship between the communication time and the middleware configuration. Indeed, the middleware determines, among others, how data is divided into batches and messages before being communicated over the network. Concretely, we focus on the research question: given a query Q and a network environment, what is the best middleware configuration that minimizes the time for transferring the query result over the network? To the best of our knowledge, the database research community does not have well-established strategies for middleware tuning. We present first an intensive experimental study that emphasizes the crucial impact of middleware configuration on the time for communicating query results. We focus on two middleware parameters that we empirically identified as having an important influence on the communication time: (i) the fetch size F (i.e., the number of tuples in a batch that is communicated at once to an application consuming the data) and (ii) the message size M (i.e., the size in bytes of the middleware buffer, which corresponds to the amount of data that can be communicated at once from the middleware to the network layer; a batch of F tuples can be communicated via one or several messages of M bytes). Then, we describe a cost model for estimating the communication time, which is based on how data is communicated between computation nodes. Precisely, our cost model is based on two crucial observations: (i) batches and messages are communicated differently over the network: batches are communicated synchronously, whereas messages in a batch are communicated in pipeline (asynchronously), and (ii) due to network latency, it is more expensive to communicate the first message in a batch compared to any other message that is not the first in its batch. We propose an effective strategy for calibrating the network-dependent parameters of the communication time estimation function i.e, the costs of first message and non first message in their batch. Finally, we develop an optimization algorithm to effectively compute the values of the middleware parameters F and M that minimize the communication time. The proposed algorithm allows to quickly find (in small fraction of a second) the values of the middleware parameters F and M that translate a good trade-off between low resource consumption and low communication time. The proposed approach has been evaluated using a dataset issued from application in Astronomy.
Wordnet.Br: An Exercise of Human Language Technology Research

This paper reports the ongoing project (since 2002) of developing a wordnet for Brazilian Portuguese (Wordnet.Br) from scratch. In particular, it describes the process of constructing the Wordnet.Br core database, which has 44,000 words organized in 18,500 synsets Accordingly, it briefly sketches the project overall methodology, its lexical resourses, the synset compilation process, and the Wordnet.Br editor, a GUI (graphical user interface) which aids the linguist in the compilation and maintenance of the Wordnet.Br. It concludes with the planned further work.
Migration Modeling and Learning Algorithms for Containers in Fog Computing

Fog Computing (FC) is a flexible architecture to support distributed domain-specific applications with cloud-like quality of service. However, current FC still lacks the mobility support mechanism when facing many mobile users with diversified application quality requirements. Such mobility support mechanism can be critical such as in the industrial internet where human, products, and devices are moveable. To fill in such gaps, in this paper we propose novel container migration algorithms and architecture to support mobility tasks with various application requirements. Our algorithms are realized from three aspects: 1) We consider mobile application tasks can be hosted in a container of a corresponding fog node that can be migrated, taking the communication delay and computational power consumption into consideration; 2) We further model such container migration strategy as multiple dimensional Markov Decision Process (MDP) spaces. To effectively reduce the large MDP spaces, efficient deep reinforcement learning algorithms are devised to achieve fast decision-making and 3) We implement the model and algorithms as a container migration prototype system and test its feasibility and performance. Extensive experiments show that our strategy outperforms the existing baseline approaches 2.9, 48.5 and 58.4 percent on average in terms of delay, power consumption, and migration cost, respectively.
Selectivity Estimation of Approximate Predicates on Text

This dissertation studies selectivity estimation of approximate predicates on text. Intuitively, we aim to count the number of strings that are similar to a given query string. This type of problem is crucial in handling text in RDBMSs in an error-tolerant way. A common difficulty in handling textual data is that they may contain typographical errors, or use similar but different textual representations for the same real-world entity. To handle such data in databases, approximate text processing has gained extensive interest and commercial databases have begun to incorporate such functionalities. One of the key components in successful integration of approximate text processing in RDBMSs is the selectivity estimation module, which is central in optimizing queries involving such predicates. However, these developments are relatively new and ad-hoc approaches, e.g., using a constant, have been employed. This dissertation studies reliable selectivity estimation techniques for approximate predicates on text. Among many possible predicates, we focus on two types of predicates which are fundamental building blocks of SQL queries: selections and joins. We study two different semantics for each type of operator. We propose a set of related summary structures and algorithms to estimate selectivity of selection and join operators with approximate matching. A common challenge is that there can be a huge number of variants to consider. The proposed data structures enable efficient counting by considering a group of similar variants together rather than each and every one separately. A lattice-based framework is proposed to consider overlapping counts among the groups. We performed extensive evaluation of proposed techniques using real-world and synthetic data sets. Our techniques support popular similarity measures including edit distance, Jaccard similarity and cosine similarity and show how to extend the techniques to other measures. Proposed solutions are compared with state-of-the-arts and baseline methods. Experimental results show that the proposed techniques are able to deliver accurate estimates with small space overhead.
FriendlyMail: Confidential and Verified Emails among Friends

Despite being one of the most basic and popular Internet applications, email still largely lacks user-to-user cryptographic protections. From a research perspective, designing privacy-preserving techniques for email services is complicated by the requirement of balancing security and ease-of-use needs of everyday users. For example, users cannot be expected to manage long-term keys (e.g., PGP key-pair), or understand crypto primitives. To enable intuitive email protections for a large number of users, we design FriendlyMail by leveraging existing relationships between a sender and receiver on an online social networking (OSN) site. FriendlyMail can provide integrity, authentication and confidentiality guarantees for user-selected messages among OSN friends. A confidentiality-protected email is encrypted by a randomly-generated key, and the key and hash of the encrypted content are privately shared with the receiver via the OSN site. Our implementation consists of a Firefox addon and a Facebook app, and can secure the web-based Gmail service using Facebook as the OSN site; the addon is available at: https://madiba.encs. concordia.ca/software/friendlymail/. However, the design can be implemented for preferred email/OSN services as long as the email and OSN providers are non-colluding parties. FriendlyMail is a client-end solution and does not require changes to email or OSN servers. In contrast to most other solutions, we limit our target user base to existing OSN users, to facilitate ease of adoption. In this paper, the focus of our discussion includes: the design, implementation and security analysis of the proposed solution. We acknowledge that a user study will be required to validate usability-related features of FriendlyMail. We are currently considering a comprehensive user study as separate future work; cf. past such studies of PGP (Whitten and Tygar, USENIX Security 1999), S/MIME (Garfinkel and Miller, SOUPS 2005).
Data Flow and Communication Framework Supporting Digital Twin for Geometry Assurance

Faster optimization algorithms, increased computer power and amount of available data, can leverage the area of simulation towards real-time control and optimization of products and production systems. This concept — often referred to as Digital Twin — enables real-time geometry assurance and allows moving from mass production to more individualized production. To master the challenges of a Digital Twin for Geometry Assurance the project Smart Assembly 4.0 gathers Swedish researchers within product development, automation, virtual manufacturing, control theory, data analysis and machine learning. The vision of Smart Assembly 4.0 is the autonomous, self-optimizing robotized assembly factory, which maximizes quality and throughput, while keeping flexibility and reducing cost, by a sensing, thinking and acting strategy. The concept is based on active part matching and self-adjusting equipment which improves geometric quality without tightening the tolerances of incoming parts. The goal is to assemble products with higher quality than the incoming parts. The concept utilizes information about individual parts to be joined (sensing), selects the best combination of parts (thinking) and adjust locator positions, clamps, weld/rivet positions and sequences (acting). The project is ongoing, and this paper specifies and highlights the infrastructure, components and data flows necessary in the Digital Twin in order to realize Smart Assembly 4.0. The framework is generic, but the paper focuses on a spot weld station where two robots join two sheet metal parts in an adjustable fixture.