A dynamic network simulator for testing TP monitor system performance and behavior

2007 ◽  
Author(s):  
Maria Luisa Catalan ◽  
Dennis Ludena ◽  
Hidenori Umeno
Keyword(s):  
System Performance ◽  
Dynamic Network ◽  
Monitor System ◽  
Network Simulator ◽  
And Behavior

scholarly journals E08-C Developing National Palliative and End-of-Life Indicators to Monitor System Performance

2016 ◽  
Vol 52 (6) ◽  
pp. e44
Author(s):  
Ruth Barker ◽  
Margaret Fitch ◽  
Deborah Dudgeon ◽  
Esther Green ◽  
Raquel Shaw-Moxam
Keyword(s):  
End Of Life ◽  
System Performance ◽  
Monitor System

Emerging concepts in cardiac matrix biologyThis article is one of a selection of papers published in a special issue on Advances in Cardiovascular Research.

2009 ◽  
Vol 87 (12) ◽  
pp. 996-1008 ◽  
Author(s):  
Leon Espira ◽  
Michael P. Czubryt
Keyword(s):  
Cardiac Development ◽  
Cardiac Fibroblasts ◽  
Dynamic Network ◽  
Support Structure ◽  
Cardiovascular Research ◽  
Cell Matrix ◽  
The Matrix ◽  
And Function ◽  
Cell Matrix Interactions ◽  
And Behavior

The cardiac extracellular matrix, far from being merely a static support structure for the heart, is now recognized to play central roles in cardiac development, morphology, and cell signaling. Recent studies have better shaped our understanding of the tremendous complexity of this active and dynamic network. By activating intracellular signal cascades, the matrix transduces myocardial physical forces into responses by myocytes and fibroblasts, affecting their function and behavior. In turn, cardiac fibroblasts and myocytes play active roles in remodeling the matrix. Coupled with the ability of the matrix to act as a dynamic reservoir for growth factors and cytokines, this interplay between the support structure and embedded cells has the potential to exert dramatic effects on cardiac structure and function. One of the clearest examples of this occurs when cell–matrix interactions are altered inappropriately, contributing to pathological fibrosis and heart failure. This review will examine some of the recent concepts that have emerged regarding exactly how the cardiac matrix mediates these effects, how our collective vision of the matrix has changed as a result, and the current state of attempts to pharmacologically treat fibrosis.

scholarly journals Performance Evaluation of Routing Protocols for Voice and Video Traffics

2018 ◽  
Vol 7 (3) ◽  
pp. 86-90 ◽  
Author(s):  
S. Vasundra ◽  
D. Venkatesh
Keyword(s):  
Routing Protocols ◽  
Routing Algorithm ◽  
Dynamic Network ◽  
Access Point ◽  
Network Dynamic ◽  
Transmission Range ◽  
Delivery Ratio ◽  
Node Mobility ◽  
Network Simulator ◽  
Dynamic Source

Wireless networks are comprised of nodes which are high in mobility and are adhoc natured where centralized access point is not required. Each node will have particular transmission range in which the data transmits from source to destination in that transmission range. Route construction for transmission of data from source to destination is tough due to high node mobility and dynamic nature of network. Many routing protocols are proposed and implemented in networks to reduce such mobility and dynamic difficulties for route construction. These routing protocols construct a route from source to destination based on availability of network nodes. Adhoc On demand Distance vector (AODV) is a self-starting dynamic network, Dynamic source routing (DSR) and Temporally Ordered Routing Algorithm (TORA) are most frequent used ones for dynamic route construction. Voice and Video are two mostly used applications nowadays as the users are immensely using them. In this paper, a comparison is made in performances of AODV, DSR and TORA for the traffics of voice and video. The performance is evaluated in terms of delay, throughput and packet delivery ratio. Simulations are conducted using network simulator NS 2.35.

Software-Defined Networking for Scalable Cloud-based Services to Improve System Performance of Hadoop-based Big Data Applications

2016 ◽  
Vol 8 (2) ◽  
pp. 1-22 ◽  
Author(s):  
Desta Haileselassie Hagos
Keyword(s):  
Big Data ◽  
System Performance ◽  
Dynamic Network ◽  
Software Defined Networking ◽  
Network Control ◽  
Virtual Networks ◽  
Big Data Applications ◽  
New Research ◽  
Cloud Infrastructures ◽  
The Impact

The rapid growth of Cloud Computing has brought with it major new challenges in the automated manageability, dynamic network reconfiguration, provisioning, scalability and flexibility of virtual networks. OpenFlow-enabled Software-Defined Networking (SDN) alleviates these key challenges through the abstraction of lower level functionality that removes the complexities of the underlying hardware by separating the data and control planes. SDN has an efficient, dynamic, automated network management, higher availability and application provisioning through programmable interfaces which are very critical for flexible and scalable cloud-based services. In this study, the author explores broadly useful open technologies and methodologies for applying an OpenFlow-enabled SDN to scalable cloud-based services and a variety of diverse applications. The approach in this paper introduces new research challenges in the design and implementation of advanced techniques for bringing an SDN-enabled components and big data applications into a cloud environment in a dynamic setting. Some of these challenges become pressing concerns to cloud providers when managing virtual networks and data centers, while others complicate the development and deployment of cloud-hosted applications from the perspective of developers and end users. However, the growing demand for manageable, scalable and flexible clouds necessitates that effective solutions to these challenges be found. Hence, through real-world research validation use cases, this paper aims at exploring useful mechanisms for the role and potential of an OpenFlow-enabled SDN and its direct benefit for scalable cloud-based services. Finally, it demonstrates the impact of an OpenFlow-enabled SDN that fully embraces the opportunities and challenges of cloud infrastructures to improve the system performance of Hadoop-based big data applications by utilizing the network control capabilities of an OpenFlow to solve network congestion.

Software-Defined Networking for Scalable Cloud-Based Services to Improve System Performance of Hadoop-Based Big Data Applications

Web Services ◽  
2019 ◽  
pp. 1460-1484
Author(s):  
Desta Haileselassie Hagos
Keyword(s):  
Big Data ◽  
System Performance ◽  
Dynamic Network ◽  
Software Defined Networking ◽  
Network Control ◽  
Virtual Networks ◽  
Big Data Applications ◽  
New Research ◽  
Cloud Infrastructures ◽  
And Control

The rapid growth of Cloud Computing has brought with it major new challenges in the automated manageability, dynamic network reconfiguration, provisioning, scalability and flexibility of virtual networks. OpenFlow-enabled Software-Defined Networking (SDN) alleviates these key challenges through the abstraction of lower level functionality that removes the complexities of the underlying hardware by separating the data and control planes. SDN has an efficient, dynamic, automated network management, higher availability and application provisioning through programmable interfaces which are very critical for flexible and scalable cloud-based services. In this study, the author explores broadly useful open technologies and methodologies for applying an OpenFlow-enabled SDN to scalable cloud-based services and a variety of diverse applications. The approach in this paper introduces new research challenges in the design and implementation of advanced techniques for bringing an SDN-enabled components and big data applications into a cloud environment in a dynamic setting. Some of these challenges become pressing concerns to cloud providers when managing virtual networks and data centers, while others complicate the development and deployment of cloud-hosted applications from the perspective of developers and end users. However, the growing demand for manageable, scalable and flexible clouds necessitates that effective solutions to these challenges be found. Hence, through real-world research validation use cases, this paper aims at exploring useful mechanisms for the role and potential of an OpenFlow-enabled SDN and its direct benefit for scalable cloud-based services. Finally, it demonstrates the impact of an OpenFlow-enabled SDN that fully embraces the opportunities and challenges of cloud infrastructures to improve the system performance of Hadoop-based big data applications by utilizing the network control capabilities of an OpenFlow to solve network congestion.

scholarly journals Model Adequacy Checking/Goodness-of-fit Testing for Behavior in Joint Dynamic Network/Behavior Models, with an Extension to Two-mode Networks

2020 ◽  
pp. 004912412091493
Author(s):  
Cheng Wang ◽  
Carter T. Butts ◽  
John Hipp ◽  
Cynthia M. Lakon
Keyword(s):  
Network Structure ◽  
Goodness Of Fit ◽  
Dynamic Properties ◽  
Practical Importance ◽  
Dynamic Network ◽  
Simulated Data ◽  
Network Models ◽  
Model Adequacy ◽  
Dynamic Network Models ◽  
And Behavior

The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to reproduce network structure over time, to date there are few indices for assessing the ability of the model to reproduce individuals’ behavior patterns. Drawing on the widely used strategy of assessing model adequacy by comparing index values summarizing features of the observed data to the distribution of those index values on simulated data from the fitted model, we propose four goals that a researcher could reasonably expect of a joint structure/behavior model regarding how well it captures behavior and describe indices for assessing each of these. These reasonably simple and easily implemented indices can be used for assessing model adequacy with any dynamic network models jointly working with networks and behavior, including the stochastic actor-based models implemented within software packages such as RSien version 1.2-24. We demonstrate the use of our indices with an empirical example to show how they can be employed in practical settings, with an additional extension to modeling affiliation dynamics in two-mode networks. Key scripts are provided in the Supplemental Document (which can be found at http://smr.sagepub.com/supplemental/ ).

scholarly journals Dynamic contextual influences on social motivation and behavior in schizophrenia: a case-control network analysis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Varsha D. Badal ◽  
Emma M. Parrish ◽  
Jason L. Holden ◽  
Colin A. Depp ◽  
Eric Granholm
Keyword(s):  
Network Analysis ◽  
Positive Emotions ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Social Motivation ◽  
Emotional States ◽  
Contextual Influences ◽  
Network Analyses ◽  
And Behavior ◽  
Ema Data

AbstractContextual influences on social behavior and affective dynamics are not well understood in schizophrenia. We examined the role of social context on emotions, and the motivation to interact in the future, using dynamic network analysis of ecological momentary assessment (EMA) data. Participants included 105 outpatients with schizophrenia or schizoaffective disorder (SZ) and 76 healthy comparators (HC) who completed 7 days, 7 times a day of EMA. Dynamic networks were constructed using EMA data to visualize causal interactions between emotional states, motivation, and context (e.g., location, social interactions). Models were extended to include the type and frequency of interactions and the motivation to interact in the near future. Results indicated SZ networks were generally similar to HC but that contextual influences on emotion and social motivation were more evident in SZ. Further, feedback loops in HC were likely adaptive (e.g., positive emotions leading to social motivation), but most were likely maladaptive in SZ (e.g., sadness leading to reduced happiness leading to increased sadness). Overall, these findings indicate that network analyses may be useful in specifying emotion regulation problems in SZ and that instability related to contextual influences may be a central aspect of aberrant regulation.

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