this paper proposes a unique approach to refining self-sufficient network retailers inside distributed and cooperative networks. A dispensed reinforcement gaining knowledge of community (DRLN) architecture is proposed...
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Wireless sensors are regarded as critical components in allowing effective IoT networking that has spread into a variety of real-time applications. One of the primary goals in constructing a wireless sensor network (W...
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作者:
Pizzuti, Clara
Via Pietro Bucci 8-9C CS Rende87036 Italy
Rising quantum technologies undertake to provide new strategies for solving hard combinatorial problems. Community detection is a fundamental issue in network studies with applications in various complex systems. A re...
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Serverless computing and, in particular, Function-as-a-Service (FaaS) have emerged as valuable paradigms to deploy applications without the burden of managing the computing infrastructure. While initially limited to t...
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ISBN:
(纸本)9798400704444
Serverless computing and, in particular, Function-as-a-Service (FaaS) have emerged as valuable paradigms to deploy applications without the burden of managing the computing infrastructure. While initially limited to the execution of stateless functions in the cloud, serverless computing is steadily evolving. the paradigm has been increasingly adopted at the edge of the network to support latency-sensitive services. Moreover, it is not limited to stateless applications, with functions often recurring to external data stores to exchange partial computation outcomes or to persist their internal state. To the best of our knowledge, several policies to schedule function instances to distributed hosts have been proposed, but they do not explicitly model the data dependency of functions and its impact on performance. In this paper, we study the allocation of functions and associated key-value state in geographically distributed environments. Our contribution is twofold. First, we design a heuristic for function offloading that satisfies performance requirements. then, we formulate the state migration problem via Integer Linear Programming, taking into account the heterogeneity of data, its access patterns by functions, and the network resources. Extensive simulations demonstrate that our policies allow FaaS providers to effectively support stateful functions and also lead to improved response times.
the continuously ongoing evolution of complexity and scale of web and mobile applications necessitates the adoption and implementation of robust mechanisms for managing application state to ensure consistency, perform...
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ISBN:
(纸本)9798331540913;9798331540906
the continuously ongoing evolution of complexity and scale of web and mobile applications necessitates the adoption and implementation of robust mechanisms for managing application state to ensure consistency, performance, scalability, and user-friendliness across the frontend and backend systems. this paper provides a coherent review of end-to-end Client and Server State Management (ASM) techniques, categorized into Local State Management, State Management Libraries, and Server-Side State Management. the paper provides a thorough analysis of popular front end frameworks, local state management mechanisms, front end management libraries, highlighting their implementations, benefits, and limitations. the paper also covers various server-side state management techniques, highlighting their pros and cons around latency, performance, and scale aspects. this paper offers actionable insights for full-stack developers to build scalable, fault-tolerant, and responsive applications, aiming to bridge the gap between theoretical knowledge and practical application. this study's critical analysis and recommendations aim to guide future research and development in ASM, contributing to the advancement of modern application architecture.
the AC/DC distributed network's power converters make it complex, but necessary, to establish a power flow methodology. the representation of the Backward-Forward Sweep technique to address the load flow for a rad...
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Formal methods were historically implemented in regions, which include device layout, hardware/software code sign, and verification to automate complex architecture layouts for embedded computingsystems. this paper g...
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Adopting Digital Twin (DT) technology in vehicular edge computing (VEC) enables efficient capture of real-time state information of applications, thereby addressing complex task scheduling problems. Existing literatur...
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ISBN:
(纸本)9798350369458;9798350369441
Adopting Digital Twin (DT) technology in vehicular edge computing (VEC) enables efficient capture of real-time state information of applications, thereby addressing complex task scheduling problems. Existing literature studies considered only minimizing service latency for task offloading;however, there is room for exploring strategies to enhance user Quality of Experience (QoE) in timeliness and reliability domains. In this paper, we have developed an optimization framework using Mixed Integer Linear Programming (MILP), namely QuETOD, which minimizes service latency by allocating task execution responsibility to highly reliable and reputed vehicles in a DT-enabled VEC environment. the developed QuETOD framework clusters the vehicles based on the demand-supply theory of economics by considering computing resources and utilizing the multi-weighted subjective logic for getting the proper reputation update of the vehicles. the experimental results of the developed QuETOD system depict significant performance improvement in terms of QoE and reliability compared to the state-of-the-art works as high as 15% and 25%, respectively.
As software systems become increasingly complex, it is crucial to analyze code similarity and replication patterns. this study investigates how such patterns impact software quality, maintainability, and development p...
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Fog computing, an evolution of cloud computing, has become increasingly popular for its ability to lessen the burden of such a centralized computing paradigm by distributing tasks generated by IoT across fog layers. E...
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ISBN:
(纸本)9798350369458;9798350369441
Fog computing, an evolution of cloud computing, has become increasingly popular for its ability to lessen the burden of such a centralized computing paradigm by distributing tasks generated by IoT across fog layers. Effectively managing real-time, delay-sensitive, and diverse IoT applications to enhance the Quality-of-Experience (QoE) presents significant challenges due to the dispersed nature and limited resources of fog nodes. Previous studies in fog computing task offloading have typically focused on either energy consumption or service delay. this paper introduces an optimization framework for task offloading within fog computing environments that aims to balance improved user QoE with reduced energy consumption, employing Mixed-Integer Linear Programming (MILP). Given the NP-hard nature of this framework, we have devised a Deep Q-Learning (DQL) based model for task offloading, termed ELTO-DQL, which aims for near-optimal solutions in polynomial time. Experimental results indicate that the ELTO-DQL model enhances energy efficiency and QoE by up to 19% and 15% respectively, outperforming contemporary benchmarks.
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