the proceedings contain 96 papers. the topics discussed include: distributed MQTT brokers at network edges: a study on message dissemination;multi-stage low error localization based on krill herd optimization algorith...
ISBN:
(纸本)9781665454179
the proceedings contain 96 papers. the topics discussed include: distributed MQTT brokers at network edges: a study on message dissemination;multi-stage low error localization based on krill herd optimization algorithm in WSNs;a decentralized framework with dynamic and event-driven container orchestration at the edge;a novel harmony search cat swarm optimization algorithm for optimal bridge sensor placement;on-ramp merging for connected autonomous vehicles using deep reinforcement learning;on-device training of deep learning models on edge microcontrollers;user position-based wireless sensor network deployment algorithm;edge-cloud cooperation for DNN inference via reinforcement learning and supervised learning;node deployment and confident information coverage for WSN-based air quality monitoring;and demand-oriented allocation with fairness in multi-operator dynamic spectrum sharing systems.
Demand-side flexibility is defined as the capacity to increase, decrease, or shift a fraction of the electricity consumption in a power system. this type of load management could increase the use of renewable energy s...
详细信息
When considering the implementation of smart diagnostic and online monitoring for a predictive maintenance approach in industrial environments, and for rotating machinery in particular, most approaches focus on adding...
详细信息
this paper starts from the observation that mobile and edge devices are powerful enough to execute Machine Learning (ML) application components, which in turn creates opportunities to keep privacy-sensitive data close...
详细信息
ISBN:
(纸本)9781665439299
this paper starts from the observation that mobile and edge devices are powerful enough to execute Machine Learning (ML) application components, which in turn creates opportunities to keep privacy-sensitive data close to its source. Composing and deploying a distributed ML application is far from trivial because the optimal configuration depends on the application's goals and execution context, both of which may change throughout its lifetime. Prior research on context-aware reconfigurations in ML based applications offer limited capabilities for dynamically migrating software components between mobile, edge and cloud devices. In this paper, we propose a context-aware middleware that enables automated optimizations of the application deployment in order to satisfy the application's functional goals while the execution context changes in terms of available computation, memory and network resources. We use finite state machines to model the reconfiguration of the application based on contextual triggers and facilitate system design through the abstraction of system states. We illustrate the benefits of our approach with an image recognition application with well-defined performance goals that is deployed in a three-tier mobile-edge-cloud architecture.
Tiny sensor nodes are used to configure the wireless sensor networks. Such a network has faced the problem of limited resources, mainly energy. Here, energy-efficient clustering and routing (EECR) is an attractive and...
详细信息
In past few years, wireless multimedia sensor network (WMS N) experiences a persisting mark on the lives of everyone by facilitating in diverse domains namely agriculture, manufacturing, medical, educational as well a...
详细信息
Swarm robotics is a network based multi-device system designed to achieve shared objectives in a synchronized way. this system is widely used in industries like farming, manufacturing, and defense applications. In rec...
详细信息
the proliferation of renewable energy sources distributed generation (RES-DG) into the grid, constant change in grid load levels and occurrences of contingencies result in varying critical clearing times (CCT). To ens...
详细信息
ISBN:
(纸本)9781665489577
the proliferation of renewable energy sources distributed generation (RES-DG) into the grid, constant change in grid load levels and occurrences of contingencies result in varying critical clearing times (CCT). To ensure the grid's security, considering the high penetration of RES-DG units into the modern grids, CCT prediction using varying grid features is crucial. therefore, this paper proposes an effective CCT monitoring model that includes CCT and additional RES-DG predictions. the grid attributes considered in this paper are the load level, power dispatched from the RES-DG units, and the security reserve (SR). An instance-based K-nearest (IBK) algorithm is applied to the training dataset developed from the CCTs obtained through the fault screening technique for each grid operating scenario. A Kmeans-Fuzzy process model is proposed to estimate the additional RES-DG that can be added to the grid without compromising security. the proposed approach was tested on the ieee 14 bus network. Prediction accuracy of 97% and 95% were obtained for the batch-trained IBK and Kmeans-Fuzzy models, respectively. the result shows that the proposed model can predict the CCT of the emerging grid and estimate the additional amount of RES-DG that can be securely penetrated into the grid.
A large number of hubs are used in a Wireless sensor Network to keep tabs on the physical and territorial conditions of a certain region. It's safe to say that most of them are self-employed. In the past, WSN has ...
详细信息
暂无评论