IEEE International Conference on Smart Internet of Things (SmartIoT)
2019 IEEE International Conference on Smart Internet of Things (SmartIoT)
9-11 Aug. 2019
Showing 1-25 of 95
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The proceedings of this conference will be available for purchase through Curran Associates.
Smart Internet of Things (SmartIoT), 2019 IEEE International Conference on
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Table of contents
Provides an abstract for each of the keynote presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.Show More
A New Method of Mobile Ad Hoc Network Routing Based on Improved GF Strategy
Publication Year: 2019,Page(s):1 - 7
Cited by: Papers (1)
We propose a new mobile ad hoc network routing method based on improved GF (greedy forwarding) strategy in this paper. In the greedy forwarding phase, the reliable communication area is calculated, and then the quality of the link is evaluated according to the relative displacement between the nodes and the maintenance time of the link. Then, according to the quality of the link, the distance from...Show More
Flow-Based Channel and Timeslot Co-Scheduling for Real-Time Data Aggregation in MWSNs
Publication Year: 2019,Page(s):8 - 13
Wireless Sensor Networks have been applied in many fields such as environment monitoring, health care and smart home, but interference between concurrent transmissions may have impact on network performance. To reduce interference and enhance spatial reuse, multi-channel design is considered and appropriate scheduling algorithms is used. Most of previous works aim at reduce network latency and hei...Show More
Energy-Efficiency-Aimed Radio Resource Scheduling for D2D Communications Underlaying Cellular Network
Publication Year: 2019,Page(s):14 - 21
Cited by: Papers (1)
In this paper, we study the resource management strategies for device-to-device (D2D) communications underlying the cellular networks. To cater for green communications, our design goal is to maximize ergodic energy efficiency (EE) of all D2D links with the fact that it may be tricky for the base station (BS) to receive all the real-time channel state information (CSI) while guaranteeing the stabi...Show More
An Online Computation Offloading with Energy-Harvesting in Mobile ad Hoc Network
Weiping Wang;Guangsheng Feng;Bingyang Li;Yingying Yuan;Quanming Li;Hongwu Lv;Qian Zhao
Publication Year: 2019,Page(s):22 - 27
Cited by: Papers (2)
In this paper, we study the computation offloading problem in a mobile ad hoc network (MANET) scenario, where the network nodes can cooperatively help each other to fulfill computation tasks, and the energy-harvesting technology is also considered to overcome possible energy-exhausted issues. To tradeoff energy-harvesting and consumption, the problem of task offloading and energy-harvesting is for...Show More
Modeling and Evaluation of a Power-Aware Algorithm for IoT Bluetooth Low Energy Devices
M. Carmen Ruiz;Celia Garrido-Hidalgo;Damas P. Gruska;Teresa Olivares;Diego Hortelano;Luis Roda-Sanchez
Publication Year: 2019,Page(s):28 - 35
Cited by: Papers (1)
Power consumption is one of the main concerns in developing IoT Wireless Sensor Networks (WSNs) due to the limited amount of energy and the difficulty of recharging them. The energy consumption rate in WSNs varies greatly based on the protocols used. Therefore, developing energy-efficient protocols is an unavoidable issue in WSNs. In addition, it is highly advisable both, verify algorithms before ...Show More
Grey Fault Detection Method Based on Application Interference Model in Cloud Storage
Publication Year: 2019,Page(s):36 - 43
The existing failure detection technology in cloud storage system mainly used to identify abnormal states of nodes by analyzing log records and the usage trend of CPU, memory, disk space and other physical resources of nodes. Despite great efforts made by researchers in the field of failure detection, there are still the gray faults have not been detected, such as the effect of memory jitter, and ...Show More
More Competitive Feature Extraction Network for Instance Segmentation
Publication Year: 2019,Page(s):44 - 49
Instance segmentation has a wide range of applications in autonomous driving, video security and so on. Mask R-CNN, which introduces Feature Pyramid Networks (FPN), is a simple and effective instance segmentation framework. However, it still has some problems such as false detection, missed detection, and low instance segmentation accuracy. To address such problems, we make corresponding improveme...Show More
Temperature Prediction Intelligent System Based on BP Neural Network in Wireless Industrial IoT
Publication Year: 2019,Page(s):50 - 55
Cited by: Papers (1)
With the development of industrial Internet of Things, manual production in the factory has gradually changed to automated production, and the temperature requirements in many aspects of the production process are very strict. In order to control temperature more intelligently, reduce errors and improve production efficiency, through the study of BP neural network, this paper designs and implement...Show More
Large Distributed Virtual Infrastructure Partitioning and Provisioning Across Providers
Huan Zhou;Zeshun Shi;Yang Hu;Pieter Donkers;Andrey Afanasyev;Spiros Koulouzis;Arie Taal;Alexandre Ulisses;Zhiming Zhao
Publication Year: 2019,Page(s):56 - 63
Cloud environments provide elastic capacity and flexible pay-as-you-go business model, and can significantly reduce the operational cost for resource-intensive applications like big data, deep learning and the Internet of Things (IoT). The virtual infrastructure, including networked virtual machines, for large scale applications, is often distributed, and involve resources not only from data cente...Show More
Discovering Frequent itemsets over uncertain databases has become a hot topic in data mining community due to the wide application of uncertain data. Several algorithms are proposed to mine frequent itemsets over uncertain data. However, the existing mining algorithms generally suffer from extensive computation and prohibitively running time when the uncertain data is large or the frequent thresho...Show More
Edge Computing for Terminal Query Based on IoT
Publication Year: 2019,Page(s):70 - 76
Cited by: Papers (3)
With the fast development of the IoT, more and more attention has been paid to the acquisition of valuable information from real-time data streams. Nowadays, sampling-based approximate data analytics are properly the most widely used, which trade the output quality for efficiency. What's more, large bandwidth is need for transmitting large amounts of data is these systems. In fact, for some simple...Show More
Distributed Computation Offloading Based on Stochastic Game in Multi-server Mobile Edge Computing Networks
Publication Year: 2019,Page(s):77 - 84
Cited by: Papers (6)
With the popularity of the Internet of things (IoT), 5G technology needs to meet various requirements of a large number of IoT applications. Mobile edge computing (MEC) is a promising approach in 5G scenario, which can solve the problems of resource shortage and high latency. Computation offloading is a key technology to reduce latency and energy consumption in MEC. In this paper, we consider a sc...Show More
Application of Edge Intelligent Computing in Satellite Internet of Things
Publication Year: 2019,Page(s):85 - 91
Cited by: Papers (36)
With the advancement of aerospace technology and the investment of commercial satellite companies in the satellite industry, the number of satellites is increasing. Satellites become an important part of the IoT and 5G/6G communications. The sensors on the satellite will generate a large amount of data every day. However, due to the current on-board processing capability and the limitation of the ...Show More
Joint Computation Offloading and Resource Management for USVs Cluster of Fog-Cloud Computing Architecture
Publication Year: 2019,Page(s):92 - 99
Cited by: Papers (6)
In recent years, unmanned surface vehicles (USVs) have made important advances in civil, maritime, and military applications. With the continuous improvement of autonomy, the increasing complexity of tasks, and the emergence of various types of advanced sensors, higher requirements are imposed on the computing performance of USVs clusters, especially for latency sensitive tasks. Therefore, this pa...Show More
An Artificial Intelligence Perspective on Mobile Edge Computing
Zhuang Chen;Qian He;Lei Liu;Dapeng Lan;Hwei-Ming Chung;Zhifei Mao
Publication Year: 2019,Page(s):100 - 106
Cited by: Papers (18)
The interest of artificial intelligence (AI) and mobile edge computing (MEC) has increased in recent years. As a fundamental building block for the development of mobile edge computing, new techniques are needed in the mobile network. Driven by the techniques of Internet of Things (IoT) and AI, MEC, as an emerging paradigm, enables cloud services and AI frontier in close proximity to users, by pus...Show More
A Greedy Multiple Fixed Node Networking Algorithm for Indoor Environmental Monitoring Scenarios
Publication Year: 2019,Page(s):107 - 112
The design of network layer protocol is one of the key issues in the research of Internet of things(IoT). We propose to design a network layer protocol with focus on the application of specific scenario. In this paper, the indoor environment monitoring application scenario is taken as an example and a matching network layer protocol is proposed. In view of the characteristics of multiple fixed nod...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
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