UPSTREAM TRANSMISSION IN AN HFC SYSTEM USING SDMT: THE NETWORK, DATA RATES AND A MAC PROTOCOL

2005 ◽  
Author(s):  
J.A.C. Bingham ◽  
K. Jacobson
Keyword(s):  
Mac Protocol ◽  
Network Data ◽  
Data Rates

A MAC Protocol for Terahertz Ultra-High Data-Rate Wireless Networks

2013 ◽  
Vol 427-429 ◽  
pp. 2864-2869
Author(s):  
Zhi Ren ◽  
Ya Nan Cao ◽  
Shuang Peng ◽  
Hong Jiang Lei
Keyword(s):  
Wireless Networks ◽  
Electromagnetic Waves ◽  
Mac Protocol ◽  
Terahertz Wave ◽  
Data Rate ◽  
High Data Rate ◽  
Control Mechanisms ◽  
High Data ◽  
Large Bandwidth ◽  
Data Rates

The terahertz wave is a kind of electromagnetic waves which locates between millimeter waves and infrared lightwaves, and the frequency range is 0.14THz~10THz. Terahertz is used as a carrier wave to communicate with each other because it has large bandwidth which can support Gbps wireless data rates. Therefore, terahertz communication technologies become research hot spots in recent years. However, its still rare in MAC protocol of terahertz ultra-high data-rate wireless networks at present. In order to realize wireless access of ultra-high data-rate under the condition of terahertz carrier frequency, a novel MAC protocol is proposed in this paper. The improved MAC protocol which makes the maximum data rates reach up to 10Gbps or higher is designed by new MAC control mechanisms, new time-slots allocation schemes and new superframe structure. Theoretical analysis and simulation results show that the new proposed MAC protocol of terahertz ultra-high data-rate wireless networks can operation normally, and the maximum data rate can reach up to 19.2Gbps. This maximum data rate is 2 times higher than 5.78 Gbps which IEEE 802.15.3c can achieve.

DADC: A Novel Duty-cycling Scheme for IEEE 802.15.4 Cluster-tree-based IoT Applications

2022 ◽  
Vol 22 (2) ◽  
pp. 1-26
Author(s):  
Nikumani Choudhury ◽  
Rakesh Matam ◽  
Mithun Mukherjee ◽  
Jaime Lloret
Keyword(s):  
Ieee 802.15.4 ◽  
Mac Protocol ◽  
Cluster Tree ◽  
Medium Access ◽  
Duty Cycling ◽  
Duty Cycles ◽  
Data Rates ◽  
Network Topologies ◽  
Two Parameters ◽  
Ieee 802.15.4 Standard

The IEEE 802.15.4 standard is one of the widely adopted specifications for realizing different applications of the Internet of Things. It defines several physical layer options and Medium Access Control (MAC) sub-layer for devices with low-power operating at low data rates. As devices implementing this standard are primarily battery-powered, minimizing their power consumption is a significant concern. Duty-cycling is one such power conserving mechanism that allows a device to schedule its active and inactive radio periods effectively, thus preventing energy drain due to idle listening. The standard specifies two parameters, beacon order and superframe order, which define the active and inactive period of a device. However, it does not specify a duty-cycling scheme to adapt these parameters for varying network conditions. Existing works in this direction are either based on superframe occupation ratio or buffer/queue length of devices. In this article, the particular limitations of both the approaches mentioned above are presented. Later, a novel duty-cycling mechanism based on MAC parameters is proposed. Also, we analyze the role of synchronization schemes in achieving efficient duty-cycles in synchronized cluster-tree network topologies. A Markov model has also been developed for the MAC protocol to estimate the delay and energy consumption during frame transmission.

scholarly journals A Novel QoS-Aware A-MPDU Aggregation Scheduler for Unsaturated IEEE802.11n/ac WLANs

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1203 ◽  
Author(s):  
Cong Lu ◽  
Bin Wu ◽  
Tianchun Ye
Keyword(s):  
Real Time ◽  
Mac Protocol ◽  
Local Area ◽  
Media Access Control ◽  
Delay Model ◽  
Media Access ◽  
Data Rates ◽  
The Media ◽  
Qos Performance ◽  
The Impact

Improving the quality of service (QoS) performance to support existing and upcoming real-time applications is critical for IEEE 802.11n/ac devices. The mechanisms of the media access control (MAC) layer, including the aggregate MAC protocol data unit (A-MPDU) aggregation, greatly affect the QoS performance in wireless local area networks (WLANs). To investigate the impact of the aggregation level on the QoS performance for real-time multimedia applications, a novel end-to-end delay model for the unsaturated settings is proposed in this paper. The presented model considers the gathering procedure of packets, queuing behaviors, and transmissions using the RTS/CTS (request to send/clear to send) mechanism on error-prone channels. Based on the model, a novel QoS-aware A-MPDU aggregation scheduler for IEEE802.11n/ac WLANs was shown to obtain better QoS performance with lower latency and less packet loss, a larger capacity to hold higher data rates, and more working nodes. The validation of the proposed model and the promotion of the proposed scheduler are well benchmarked by ns-3.

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

Collection of Ego-Centered Network Data with Computer-Assisted Interviews

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Joachim Gerich ◽  
Roland Lehner
Keyword(s):  
Survey Methods ◽  
A Priori ◽  
Dynamic Structure ◽  
Computer Assisted ◽  
Network Data ◽  
Great Effort ◽  
Self Administration ◽  
Face To Face ◽  
Full Network

Although ego-centered network data provide information that is limited in various ways as compared with full network data, an ego-centered design can be used without the need for a priori and researcher-defined network borders. Moreover, ego-centered network data can be obtained with traditional survey methods. However, due to the dynamic structure of the questionnaires involved, a great effort is required on the part of either respondents (with self-administration) or interviewers (with face-to-face interviews). As an alternative, we will show the advantages of using CASI (computer-assisted self-administered interview) methods for the collection of ego-centered network data as applied in a study on the role of social networks in substance use among college students.

Positional Estimation Within a Latent Space Model for Networks

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Susan Shortreed ◽  
Mark S. Handcock ◽  
Peter Hoff
Keyword(s):  
Random Effects ◽  
Network Data ◽  
Random Effects Models ◽  
Space Model ◽  
Network Analyses ◽  
Recent Advances ◽  
Latent Space ◽  
Latent Space Model ◽  
Modeling Data

Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently developed latent space model that is particularly appropriate for the visualization of networks. We suggest a new estimator of the latent positions and perform two network analyses, comparing four alternative estimators. We demonstrate a method of checking the validity of the positional estimates. These estimators are implemented via a package in the freeware statistical language R. The package allows researchers to efficiently fit the latent space model to data and to visualize the results.

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