the Internet of things (loT) has become an important aspect in various domains such as smart cities, healthcare and industrial revolution. there are various concerns of energy consumption ever since the widespread of ...
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In this paper, an architecture of a photonic neural network chip withdistributed multi-scenarios is presented. the distributedcomputing chip has five computing modules, which are characterized by three-dimensional i...
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this paper studies the network based distributed mobile cloud cooperation architecture and QoS guarantee mechanism of end-to-end computing and control. By implanting cloud computing resources in the mobile communicati...
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this research investigates the challenges of malicious node detection in Wireless sensor Networks (WSNs). the study provides a comparative analysis of various detection techniques, including Trust-Based Mechanisms, An...
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this study focuses on the design and implementation of a distributed online video management system based on cloud computing. First, this study introduces the basic concepts and development history of distributed syst...
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Federated Learning (FL) has emerged as a novel distributed Machine Learning (ML) approach, to tackle the challenges associated with data privacy and overload in ML-based intrusion detection systems (IDSs). Drawing ins...
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ISBN:
(纸本)9798350361261;9798350361278
Federated Learning (FL) has emerged as a novel distributed Machine Learning (ML) approach, to tackle the challenges associated with data privacy and overload in ML-based intrusion detection systems (IDSs). Drawing inspiration from the FL architecture, we have introduced a hybrid ML IDS tailored for Wireless sensor Networks (WSNs). this system is crafted to leverage ML for achieving a two-layer intrusion detection mechanism in WSNs free from constraints posed by specific attack types. the architecture follows a server-client model compatible withthe configuration of sensor nodes, sink nodes, and gateways in WSNs. In this setup, client models located at sink nodes undergo training using sensing data while the server model at the gateway is trained using network traffic data. this two-layer training approach amplifies the efficiency of intrusion detection and ensures comprehensive network coverage. the results derived from our simulation experiments corroborate the effectiveness of the proposed hybrid ML IDS. It generates precise aggregation predictions and leads to a substantial reduction in redundant data transmissions. Furthermore, the system exhibits efficacy in detecting intrusions through a dual validation process.
Nowadays, load balancing is more and more important for huge data centers. Most data centers usually adopt a software-based load balancer (LB), which consumes too many server resources and does not scale withthe incr...
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ISBN:
(纸本)9798350386066;9798350386059
Nowadays, load balancing is more and more important for huge data centers. Most data centers usually adopt a software-based load balancer (LB), which consumes too many server resources and does not scale withthe increasing traffic volume. However, there is an increased demand for layer-4 load balancers, which need to check more bits in packet headers. Although hardware-based load balancers can meet the requirements, they are much more expensive. During the past years, data centers frequently update their devices, including kinds of switches. thus, there exists a huge number of obsolete switches, some of which are in good condition and equipped with high-performance storage like SRAM (Static Random Access Memory). In this paper, we proposed BCLB (Bit-based Collaborative Load Balancer), a new cooperative LB, which builds more powerful load balancing based on existing switches. Different with previous cooperative mechanisms that distribute rules to different LBs, BCLB lets switches cooperate based on bits. Many switches along the data path check different bits, and cooperatively check all bits in 5-tuple (which would be 296 bits in IPv6) for layer-4 packet header. In this way, rule updating will not influence the load balancing in BCLB. To optimize the performance of BCLB, we formulate the problem as an optimization problem, then we propose a dynamic programming algorithm to solve it. Finally, we conduct comprehensive simulations using both real-world traffic datasets and a P4-based prototype, the results show that BCLB performs much better than previous rule-based cooperative schemes.
the energy efficient routing in wireless sensor network (WSN) is crucial for enhancing the network longevity. For this, energy efficient routing protocol is introduced with cluster based routing. Initially, the sensor...
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this study explores the economics of the interaction between distributed photovoltaic and energy storage systems based on a full life cycle analysis. By calculating the internal rate of return, this study evaluates th...
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the proceedings contain 6 papers. the topics discussed include: scheduling across multiple applications using task-based programming models;DEMAC: a modular platform for HW-SW co-design;CODIR: towards an MLIR codelet ...
ISBN:
(纸本)9781665422765
the proceedings contain 6 papers. the topics discussed include: scheduling across multiple applications using task-based programming models;DEMAC: a modular platform for HW-SW co-design;CODIR: towards an MLIR codelet model dialect;MENPS: a decentralized distributed shared memory exploiting RDMA;RaDD runtimes: radical and different distributed runtimes with SmartNICs;DEMAC: a modular platform for HW-SW co-design;and CODIR: towards an MLIR Codelet model dialect.
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