Today, most database-backed web applications depend on the database to handle deadlocks. At runtime, the database monitors the progress of transaction execution to detect deadlocks and abort affected transactions. How...
Today, most database-backed web applications depend on the database to handle deadlocks. At runtime, the database monitors the progress of transaction execution to detect deadlocks and abort affected transactions. However, this common detect-and-recover strategy is costly to performance as aborted transactions waste CPU *** avoid deadlock-induced performance degradation, developers aim to reorganize the application code to remove deadlocks. Unfortunately, doing so is difficult for web applications. Not only do their implementations include hundreds of thousands of LoCs, but they also use third-party object-relational mapping (ORM) frameworks which hide database access details. Consequently, it is hard for developers to accurately diagnose *** propose WeSEER, a deadlock diagnosis tool for web applications. To overcome the opacity of ORMs, WeSEER performs concolic execution on unit tests to extract a web application’s transactions as a sequence of template statements with symbolic inputs as well as path conditions that enable the sequence. WeSEER then analyzes the extracted transactions based on fine-grained lock modeling to identify potential deadlocks and report the code locations that cause them. We implement WeSEER for Java-based (OpenJDK) web applications, and use it to analyze two popular open-source e-commerce applications, Broadleaf and Shopizer. WeSEER has successfully identified 18 potential deadlocks in Broadleaf and Shopizer. Eliminating these identified deadlocks can result in up to 39.5× and 4.5× throughput improvement for Broadleaf and Shopizer, respectively.
Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested on unseen domains. Federated Domain Gener-alization (FedDG) attempts to train a global mode...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013
Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested on unseen domains. Federated Domain Gener-alization (FedDG) attempts to train a global model using collaborative clients in a privacy-preserving manner that can generalize well to unseen clients possibly with domain shift. However, most existing FedDG methods either cause additional privacy risks of data leakage or induce signifi-cant costs in client communication and computation, which are major concerns in the Federated Learning paradigm. To circumvent these challenges, here we introduce a novel architectural method for FedDG, namely gPerXAN
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https://***/lhkhiem28/gPerXAN, which relies on a normalization scheme working with a guiding regularizer: In particular, we carefully design Personalized eXplicitly Assembled Normalization to enforce client mod-els selectively filtering domain-specific features that are bi-ased towards local data while retaining discrimination of those features. Then, we incorporate a simple yet effec-tive regularizer to guide these models in directly capturing domain-invariant representations that the global model's classifier can leverage. Extensive experimental results on two benchmark datasets, i.e., PACS and Office-Home, and a real-world medical dataset, Camelyon17, indicate that our proposed method outperforms other existing methods in ad-dressing this particular problem.
Because of their development and success, MANETs are now preferred alternatives in many fields of study and application. The IEEE 802.11 standard is the basis of most wireless technologies. To treat collisions in wire...
Because of their development and success, MANETs are now preferred alternatives in many fields of study and application. The IEEE 802.11 standard is the basis of most wireless technologies. To treat collisions in wireless networks, IEEE 802.11 distributed Coordination Function (DCF) MAC layer employs Binary Exponential Backoff (BEB) algorithm, that is helpful in decreasing the potential of collision, but comes at the expense of several network performance metrics, such as medium access delay, bandwidth management, power use, and fairness. A Deep Learning technique called Deep Reinforcement Learning (DRL) allows an agent to communicate with the environment in order to accomplish a goal. In the present paper, we suggest Q-learning (QL), one of the DRL approaches to improve the Binary Exponential Backoff (BEB) in MANETs. The intelligently designed Int-BEB aims for better CW selection; this selection strikes to reduce collisions as much as possible and to give more chances to nodes that make collisions to access the channel by taking into consideration their residual energy. In-depth simulations are performed to evaluate the performance of the proposed mechanism. The performance of Int-BEB is evaluated in diverse networks with several criteria such as packet successful transmission, packet loss and energy.
Solving sparse linear systems lies at the core of numerous computational applications. Consequently, understanding the performance of recently proposed alternatives to the established IEEE 754 floating-point numbers, ...
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This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by these environments. Through AI agent...
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This paper presents a unified approach for repre-senting multiple domains alongside production in cyber-physical production systems (CPPSs) through domain-specific languages (DSLs). The approach is illustrated using m...
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ISBN:
(数字)9798350361230
ISBN:
(纸本)9798350361247
This paper presents a unified approach for repre-senting multiple domains alongside production in cyber-physical production systems (CPPSs) through domain-specific languages (DSLs). The approach is illustrated using material flows (MFs) as an example. The paper identifies requirements for DSLs in CPPSs and MFs, including concurrency, synchronization, constraints, and heterogeneity support. Subsequently, a plugin system is in-troduced for the existing Production Flow Description Language (PFDL), which allows users to incorporate additional domain-specific functionality in the form of plugins. To demonstrate this approach, we present the MF plugin, resulting in the combined PFDLMF. This showcases the reusability of such an approach and the easy integration of new CPPS domains. We envision the convergence of the PFDL with plugins towards a unified flow description language for CPPSs. A practical CPPS use-case demonstrates the expressiveness of the PFDLMF in modeling and executing complex MFs in an agent-based architecture.
Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into com...
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Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computerscience education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computerscience programs, (2) construct level-appropriate examples that could be included midway into one’s undergraduate studies, (3) demonstrate how to address successive "failures" through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and
Nowadays, increasing use of Internet connection, security becomes a huge challenge for individuals as well as governments and organizations. Therefore, in the last decade, the world is moving towards green computing i...
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As a cutting-edge technology of low-altitude Artificial Intelligence of Things (AIoT), autonomous aerial vehicle object detection significantly enhances the surveillance services capabilities of low-altitude AIoT. How...
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Internet of things (IoT) gadgets have transformed several industries, including engineering, medicine, and more, thanks to the meteoric rise in the number of connected smart devices. The core principle of using the In...
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ISBN:
(纸本)9798350375442
Internet of things (IoT) gadgets have transformed several industries, including engineering, medicine, and more, thanks to the meteoric rise in the number of connected smart devices. The core principle of using the Internet of Things is that it expedites the delivery of information while consuming very little energy. In a nutshell, the Internet of Things (IoT) is a system of interconnected computing devices, services, and data that allows everyday objects to communicate with one another and with their physical environments. Prior to being saved on the server, all data sent across the IoT network must first be aggregated in the Queuing Telemetry Transport protocol (QTTP) broker. Access control, authorization, data storage, secrecy, authentication, system construction, and organization are some of the primary security concerns surrounding the Internet of Things (IoT). Three innovative security frameworks - RSA, Advanced Encryption Standard, and Elliptical Curve Cryptography - are created to enhance the protection of data in powered IoT devices. The security of IoT data is ensured by integrating all cryptic algorithms with the Constrained Queue Telemetry Transport Protocol (CQTTP). Data transmission from each IoT node undergoes cryptographic processes before being aggregated in the CQTTP. Exchange of key approvals, confirmation, and preservation of application data contrast are all accomplished by this cryptic action. Encryption keys are crucial to the safety of the data ix. The primary security component that reveals how many distinct key values a key in a protocol may take is the key's size. As a result, this study uses a new random key size method to give keys of varying sizes to the data sent by each node. Cryptography is harder when key sizes are set to be variable and random. In order to prevent script XSS commands and incorrect characteristics, all communications are encrypted using a technology that often permits employing TLS instead of plain TCP. Consequently
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