Information Processing and Routing in Wireless Sensor Networks

Yu, Yang; Prasanna, Viktor K.; Krishnamachari, Bhaskar

doi:10.1142/9789812772589

Cited by 16 publications

(17 citation statements)

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“…[14], [15], [16], [17] and references therein. Every single multi-hop routing protocol has its own routing metric including quality of service (QoS),fairness, security, robustness, delays, and so forth.…”

Section: B Objectivementioning

confidence: 99%

Quality-aware millimeter-wave device-to-device multi-hop routing for 5G cellular networks

Kim

Molisch

2014

2014 IEEE International Conference on Communications (ICC)

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Millimeter-wave (mm-wave) transmission is a promising method for increasing capacity in next-generation cellular systems. However, since mm-wave signals are too weak to (i) do long-distance communication and (ii) survive in non-lineof-sight situations, multi-hop relaying is required. We thus study in this paper a multi-hop routing protocol at mm-wave (38 GHz and 28 GHz) frequencies. Due to the great and steadily increasing importance of video streaming in cellular applications, we pay special attention to the maximization of video transmission quality, which makes the optimization problem different from the usual sum-rate maximization. Specifically, we develop a protocol that optimizes the "sum quality" of the transmission of different video streams, subject to constraints (minimum quality) of separate streams. We take the unique properties of mm-waves (sparse angular power spectrum, leading to low interference) into account in our method. Extensive simulation results show the superiority of our approach compared to max-min flow routing which is widely used in QoS-sensitive applications.

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Section: B Objectivementioning

confidence: 99%

Quality-aware millimeter-wave device-to-device multi-hop routing for 5G cellular networks

Kim

Molisch

2014

2014 IEEE International Conference on Communications (ICC)

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“…This paper is clearly related to a large body of research on routing for sensor networks, an overview of which is provided in [22].…”

Section: A Backgroundmentioning

confidence: 99%

Efficient Data Propagation in Traffic-Monitoring Vehicular Networks

Skordylis

Trigoni

2011

IEEE Trans. Intell. Transport. Syst.

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Road congestion and traffic-related pollution have a large negative social and economic impact on several economies worldwide. We believe that investment in the monitoring, distribution, and processing of traffic information should enable better strategic planning and encourage better use of public transport, both of which would help cut pollution and congestion. This paper investigates the problem of efficiently collecting and disseminating traffic information in an urban setting. We formulate the traffic data acquisition problem and explore solutions in the mobile sensor network domain while considering realistic application requirements. By leveraging existing infrastructure such as traveling vehicles in the city, we propose traffic data dissemination schemes that operate on both the routing and the application layer; our schemes are frugal in the use of the wireless medium, rendering our system interoperable with the proliferation of competing applications. We introduce the following two routing algorithms for vehicular networks that aim at minimizing communication and, at the same time, adhering to a delay threshold set by the application: 1) delay-bounded greedy forwarding and 2) delay-bounded minimum-cost forwarding. We propose a framework that jointly optimizes the two key processes associated with monitoring traffic, i.e., data acquisition and data delivery, and provide a thorough experimental evaluation based on realistic vehicular traces on a real city map.

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“…Each node has different capabilities. Nodes consist of components that have the ability to sense, computing, communication, actuation, and power [9]. The ability of the node component makes the WSN able to process measurements, observations and react to phenomena that exist in the environment around us.…”

Section: Introductionmentioning

confidence: 99%

Application of Internet of Things (IoT) on air pollution monitoring database system

2019

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In the present work, a database system of air pollution monitoring is developed using Internet of Things (IoT) technology. The system aims to give structural information and trace of air pollution level at particular monitoring station. The particular monitoring location (node) is connected to IoT/M2M server via GSM network using GPRS feature and display on IoT/M2M application in web form. The database on IoT/M2M contains name, description, and location of the monitoring station, Pollution index and the time when the data are taken. On IoT/M2M, the data are displayed either in a color bar graph or a line graph. The color indicated the index value of the pollution. The data can be accessed via internet on isfuonline.info. The system is tested at laboratory environment to detect CO, SO2, NO2, O3, and PM. The test result shows that the system is worked well. Time required to transfer the monitoring data to the IoT server is about 15 minutes. Meanwhile, response time of the system is 30 minutes.

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Information Processing and Routing in Wireless Sensor Networks

Cited by 16 publications

References 0 publications

Quality-aware millimeter-wave device-to-device multi-hop routing for 5G cellular networks

Quality-aware millimeter-wave device-to-device multi-hop routing for 5G cellular networks

Efficient Data Propagation in Traffic-Monitoring Vehicular Networks

Application of Internet of Things (IoT) on air pollution monitoring database system

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