This article delves into heterogeneous computingsystems, which employ multi-core processors (CPUs) and graphics processing units (GPUs) concurrently, facilitating efficient handling of resource-intensive tasks demand...
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Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource...
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ISBN:
(纸本)9798350361261;9798350361278
Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributedcomputing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery's energy content and to estimate the mean and variance of the device's lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energysaving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node's lifetime.
作者：
Weakley, Le MaiRobinson, TimIndiana Univ
Reproducibil Initiat Special Issue Chair SC22 Res Cloud Serv Bloomington IN 47404 USA Swiss Fed Inst Technol
Reproducibil Initiat Special Issue Vice Chair SC22 Swiss Natl Comp Ctr CH-6900 Lugano Switzerland
Welcome to our special section on reproducibility in large-scale computational science. Reproducibility is one of the foundations of science, ensuring not only the transparency and rigor of the methods utilized for di...
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Welcome to our special section on reproducibility in large-scale computational science. Reproducibility is one of the foundations of science, ensuring not only the transparency and rigor of the methods utilized for discovery but also that the research involved can be built upon. In order to enable research and to support open science, it is crucial that the computational work performed on high performance computing (HPC) systems is also reproducible.
Fog and edge computing bring computing, network, and storage services closer to the source of data, effectively bridging the gap between cloud infrastructure and end devices. By shifting data processing, analytics, st...
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Next-generation AI applications benefit from executing close to the network edge to better exploit co-locality to datasources and controlled actuators, and to meet stringent latency requirements. In the edge-enabled c...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
Next-generation AI applications benefit from executing close to the network edge to better exploit co-locality to datasources and controlled actuators, and to meet stringent latency requirements. In the edge-enabled cloud continuum, time and safety-critical traffic coexists with best-effort flows, resulting in heterogeneous requirements that current networking middleware and frameworks struggle to support. This paper proposes INSANE, INtegrated Selective Acceleration at the Network Edge, the first edge-oriented middleware that integrates different network acceleration techniques (XDP, DPDK, RDMA, and TSN) within the same data distribution service. INSANE offers a uniform and simple interface, useful to support common data distribution patterns, that allow developers to exploit at runtime the most suitable network technology available in the dynamically determined deployment environment.
The emerging of Digital Twin (DT) technology facilitates the further development of industrial automation. However, real-time and accurate DTs modeling and updating require massive communication and computing resource...
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ISBN:
(纸本)9798350358513;9798350358520
The emerging of Digital Twin (DT) technology facilitates the further development of industrial automation. However, real-time and accurate DTs modeling and updating require massive communication and computing resources, which poses a challenge to limited resources. Edge computing as a distributedcomputing architecture offers the possibility of high-efficient resource scheduling in DTs. Motivated by this gap, this paper aim to solve the problem of real-time and high fidelity DTs modeling and updating. First, we represent the computing tasks of DTs in the form of Heterogeneous computing Task Graph (HCTG). Then, a Hierarchical Attention Mechanism (HAT) is proposed to obtain the latent representation vectors of the HCTG. Finally, we design Markov Decision Process (MDP), and propose Deep Reinforcement Learning (DRL)-based computing task scheduling approach (HAT-DRL) to satisfy the minimum total completion time requirement of different DTs. Experimental results demonstrate that the proposed algorithm has promising scheduling performance and outperforms other task scheduling algorithms.
The increasing demand for computational resources keeps outpacing available User Equipment (UE). To overcome intrinsic hardware limitations of UEs, computational offloading was proposed. The combination of UE and seem...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
The increasing demand for computational resources keeps outpacing available User Equipment (UE). To overcome intrinsic hardware limitations of UEs, computational offloading was proposed. The combination of UE and seemingly endless computational capacity in the cloud aims to cope with those limitations. Numerous frameworks leverage Edge computing (EC) but a significant drawback of this is the required infrastructure. Some use cases however, do not benefit from lower response time and can remain in the cloud, where more potent resources are at one's disposal. Main contributions are to determine computational demands, allocate serverless resources, partition code and integrate computational offloading into a modern software deployment process. By focusing on non-time-critical use cases, drawbacks of EC can be neglected to create a more developerfriendly approach. Originality lies in the resource allocation of serverless resources for such endeavours, appropriate deployment of partitions and integration into CI/CD pipelines. Methodology used will be Design Science Research. Thus, many iterations and proof-of-concept implementations yield knowledge and artefacts.
This paper proposes a design pattern for implementing Commercial Bank Digital Currency which consists of two main layers - distribution and user constructed on top of a permissioned blockchain network based on Hyperle...
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In distributed file systems (DFS), deadlocks present significant challenges that adversely affect both performance and reliability. Conventional methods for deadlock detection and resolution are typically resource-int...
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Vehicle-to-everything (V2X) communications over cellular networks have a great potential for enabling intelligent transportation systems (ITSs), and supporting advanced services such as autonomous driving. However, su...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
Vehicle-to-everything (V2X) communications over cellular networks have a great potential for enabling intelligent transportation systems (ITSs), and supporting advanced services such as autonomous driving. However, such services have stringent QoS and security/privacy requirements. Even though the use of blockchain can ensure security and privacy for V2X services, blockchain-based solutions suffer from the issues of high latency, low scalability, and high computation power for mining. To overcome these challenges, we propose a lightweight and secure vehicular edge computing framework. The LS-VEC framework leverages directed acyclic graphs (DAGs) for recording transactions for edge resource allocation and micro-transactions for pricing VEC resources. In addition, an auction theory-based game-theoretic approach is proposed for allocation and pricing of edge resources used for supporting computation offloading.
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