Journal ArticleDOI
Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey
Reads0
Chats0
TLDR
This article defines WSNs with MEs and provides a comprehensive taxonomy of their architectures, based on the role of the MEs, and provides an extensive survey of the related literature.Abstract:
Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been proposed. Most of them exploit mobility to address the problem of data collection in WSNs. In this article we first define WSNs with MEs and provide a comprehensive taxonomy of their architectures, based on the role of the MEs. Then we present an overview of the data collection process in such a scenario, and identify the corresponding issues and challenges. On the basis of these issues, we provide an extensive survey of the related literature. Finally, we compare the underlying approaches and solutions, with hints to open problems and future research directions.read more
Citations
More filters
Journal ArticleDOI
Connectivity Weakness Impacts on Coordination in Wireless Sensor and Actor Networks
TL;DR: It is shown that actor and sensor nodes in a WSAN must cooperate to provide an integrated network when network connectivity is weak, and compared the proposed protocols using parameters related to weak connectivity and coordination.
Journal ArticleDOI
Incentive Mechanism Design in Mobile Opportunistic Data Collection With Time Sensitivity
TL;DR: This paper considers selfish mobile users with rational behaviors, and proposes a credit-based incentive-aware mechanism to stimulate mobile users to participate in data collection for mobile opportunistic crowdsensing, where the data can be transferred between mobile users via opportunistic device-to-device communications.
Journal ArticleDOI
Low-Cost Sensors for Urban Noise Monitoring Networks-A Literature Review.
TL;DR: The purpose of this article is to review the literature, and to identify the expected technical characteristics of the sensors to address the problem of noise pollution assessment, and put forward the challenges that are needed to respond to a massive deployment of low-cost noise sensors.
Journal ArticleDOI
A Systematic Review of Quality of Service in Wireless Sensor Networks using Machine Learning: Recent Trend and Future Vision
TL;DR: A statistical analysis of the past ten years ranging from 2011 to 2020 on various ML techniques used for the QoS parameters in the light of Machine Learning (ML) techniques is presented.
Journal ArticleDOI
An Online Algorithm for Data Collection by Multiple Sinks in Wireless-Sensor Networks
TL;DR: In this paper, the authors investigate the problem of data collection with multiple sinks, and design a suboptimal online algorithm via a primal-dual approach, requiring very little priori knowledge.
References
More filters
Journal ArticleDOI
Wireless sensor networks: a survey
TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.
Book
Pattern Recognition and Machine Learning (Information Science and Statistics)
TL;DR: Looking for competent reading resources?
Journal ArticleDOI
Reinforcement learning: a survey
TL;DR: Central issues of reinforcement learning are discussed, including trading off exploration and exploitation, establishing the foundations of the field via Markov decision theory, learning from delayed reinforcement, constructing empirical models to accelerate learning, making use of generalization and hierarchy, and coping with hidden state.
Posted Content
Reinforcement Learning: A Survey
TL;DR: A survey of reinforcement learning from a computer science perspective can be found in this article, where the authors discuss the central issues of RL, including trading off exploration and exploitation, establishing the foundations of RL via Markov decision theory, learning from delayed reinforcement, constructing empirical models to accelerate learning, making use of generalization and hierarchy, and coping with hidden state.
Optimized Link State Routing Protocol (OLSR)
Thomas Clausen,Philippe Jacquet +1 more
TL;DR: The Optimized Link State Routing protocol is an optimization of the classical link state algorithm tailored to the requirements of a mobile wireless LAN and provides optimal routes (in terms of number of hops).