In this paper we propose MARBLE, a distributed framework based on multi-player multi-armed bandit algorithms that aims to support job offloading procedures in FANETs to comply with strict job latency requirements whil...
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ISBN:
(纸本)9781728190549
In this paper we propose MARBLE, a distributed framework based on multi-player multi-armed bandit algorithms that aims to support job offloading procedures in FANETs to comply with strict job latency requirements while also minimizing the energy consumption of the system, thus also increasing the Unmanned Aerial Vehicles (UAVs) flight duration. To demonstrate the effectiveness of the framework, we conduct an extensive evaluation campaign and compare MARBLE with several baselines, including a centralized, oracle-based approach. Our results show that MARBLE outperforms the baselines and quickly converges to the performance of the centralized approach in a fully-distributed manner, in compliance with the latency and energy efficiency requirements. Most notably, MARBLE also improves the FANETs flight duration of up to 69% as compared to the baselines.
Blockchain-as-a-service (BaaS) in cloud datacenters is gaining widespread attention due to its high performance and privacy. However, existing BaaS solutions lack a method for deciding the proper placement of blockcha...
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ISBN:
(纸本)9798350368543;9798350368536
Blockchain-as-a-service (BaaS) in cloud datacenters is gaining widespread attention due to its high performance and privacy. However, existing BaaS solutions lack a method for deciding the proper placement of blockchain nodes across virtual machines in worldwide datacenters to achieve desired performance. Our motivating experiments show that transaction processing performance (TPS) varies similar to 31.6% depending on the placements. To provide an automatic placement solution for BaaS, we propose Cyan that predicts the TPS for blockchain node placements. Our evaluations on Google Cloud Platform demonstrate that Cyan improves the TPS guarantee similar to 2.39x compared to existing techniques.
This paper presents a novel in-memory computing unit (IMCU) architecture that utilizes a fully analog capacitor-based design to perform vector-matrix multiplications using only the energy from the input. The architect...
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ISBN:
(纸本)9798350377217;9798350377200
This paper presents a novel in-memory computing unit (IMCU) architecture that utilizes a fully analog capacitor-based design to perform vector-matrix multiplications using only the energy from the input. The architecture requires no additional circuitry apart from switches to carry out multiply and accumulate operations. To achieve the resolution of the synaptic weights, a configurable capacitor circuit has been used. We evaluate the speed limitations, as well as attainable input and weight resolutions for this architecture using a 130nm CMOS technology. The designed in-memory computing unit demonstrates 6-bit input and 6-bit weight resolution, while consuming an average of only 80.9 fJ of energy per multiplication element. The proposed IMCU architecture is fully compatible with any kind of standard commercial CMOS process.
Service placement in cloud-edge environments is complex because workloads must be placed on constrained nodes based on particular objectives, like response time, energy, or cost. Many advanced techniques emerged over ...
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ISBN:
(纸本)9798331539580
Service placement in cloud-edge environments is complex because workloads must be placed on constrained nodes based on particular objectives, like response time, energy, or cost. Many advanced techniques emerged over time to tackle this issue. However, real-world experiments are the minority. Theoretical and simulation-based evaluations are prevalent. We present a Platform for Universal and Lightweight Cloud-Edge Orchestration (PULCEO) to foster real-world evaluations. It supports creating, operating, monitoring, evaluating, and documenting orchestration solutions via a RESTful API. For evaluation, we performed a case study. We used PULCEO to reproduce a representative and theoretically designed solution for service placement in a real-world environment. Our platform can transfer theoretical orchestration solutions to real-world environments. Consequently, our platform simplifies realworld experiments with topology creation, dynamic link quality measurement, evaluation, and documentation automation.
This study is dedicated to the integration of big data analytics with edge computing, a critical need driven by the exponential growth of Internet of Things (IoT) technologies and smart device data. We introduce an op...
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Web 3.0 and Edge computing are inherently compatible, making them an ideal combination for building a secure and efficient distributed service platform to support decentralized applications (DApps). This paper investi...
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ISBN:
(纸本)9781728190549
Web 3.0 and Edge computing are inherently compatible, making them an ideal combination for building a secure and efficient distributed service platform to support decentralized applications (DApps). This paper investigates an elastic hybrid computing architecture in Edge Web 3.0, allowing DApp tasks to be executed in a hybrid manner by integrating on-chain and off-chain execution. The principle is to transfer a portion of DApp to an off-chain execution environment, along with an appropriate result verification process, to enhance computing efficiency and reduce blockchain overhead. We formulate a DApp task scheduling problem that jointly optimizes the execution pattern and offloading decision of user tasks. A learning-based DApp task scheduling scheme is designed based on Proximal Policy Optimization (PPO) to minimize the gas cost and service delay of DApps. Particularly, we tailor PPO to handle the hard constraints of service delay, gas consumption, and computing capacity in Edge Web 3.0 by adding regularization terms in the learning objective function. We establish an Edge Web 3.0 testbed based on Goerli, ZkSync, and Ethereum to evaluate the proposed method. The experimental results show that our method outperforms state-of-the-art benchmarks.
In the last decade, there has been a significant upsurge in the demand for artificial intelligence. This remarkable growth can be attributed to the advancements in machine and deep learning techniques, coupled with th...
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distributed control over networks in modern power systems poses several challenges in terms of communication resources and validation in a high-fidelity cyber-physical environment. To this aim, this paper shows an ass...
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ISBN:
(纸本)9798350386509;9798350386493
distributed control over networks in modern power systems poses several challenges in terms of communication resources and validation in a high-fidelity cyber-physical environment. To this aim, this paper shows an assessment analysis of a novel distributed Dynamic Event-Triggered control strategy, recently introduced in the technical literature, for voltage regulation in inverter-based islanded Microgrids on a high-fidelity real-time simulation platform, accurately implemented via MATLAB/SimPowersystems environment and Speedgoat Real-Time Target Machine, thus providing insights into its real-world applicability and performance. Moreover, a wide range of off-normal conditions for the islanded Microgrids are emulated, to validate the effectiveness and the resilience of the control strategy. Finally, the latin hypercube sampling approach is exploited for the assessment of the control performance under several systems parameters uncertainties/variations, as well as for all the possible combinations of them.
The development of cloud computing has led to the explosion of network traffic. The switches of cloud computing make it hard to process large-scale network traffic. Prior approaches proposed flow rules compression met...
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The research and application of big data processing and analysis have been quite mature, but more and more fields have put forward demands for real-time analysis and rapid response of fast and massive distributed big ...
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