Related Publication: Vahid, Moosavi and Ludger Hovestadt. “Modeling urban traffic dynamics in coexistence with urban data streams.” Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing. ACM, 2013.
Develop a mobility model for MANETs networks based on fuzzy Logiciosrjce
The study and research in the field of networks MANETs depends alleged understand the protocols
well of the simulation process before they are applied in the real world, so that we create an environment
similar to these networks. The problem of a set of nodes connected with each other wirelessly, this requires the
development of a comprehensive model and full and real emulator for the movement of the contract on behalf of
stochastic models. Many models came to address the problems of random models that restricted the movement
of decade barriers as well as the signals exchanged between them, but these models were not receiving a lot of
light on the movement of the contract, such as direction, speed and path that is going by the node. The main
goal is to get a comprehensive model and simulator for all parts of the environment of the barriers and
obstacles to the movement of the nodes and the mobile signal between them as well as to focus on the movement
transactions for the node of the direction, speed, and best way. . This research aims to provide a realistic
mobility model for MANET networks. It also addresses the problem of imprecision in social relationships and
the location where we apply Fuzzy logic.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
ON THE PROBABILITY OF K-CONNECTIVITY IN WIRELESS AD HOC NETWORKS UNDER DIFFER...graphhoc
We compare the probability of k-Connectivity of an ad hoc network under Random Way Point (RWP),City Section and Manhattan mobility models. A Network is said to be k Connected if there exists at least k edge disjoint paths between any pair of nodes in that network at any given time and velocity. Initially, for each of the three mobility models, the movement of the each node in the ad hoc network at a given velocity and time are captured and stored in the Node Movement Database (NMDB). Using the movements in the NMDB, the location of the node at a given time is computed and stored in the Node
Location Database (NLDB).
Analysis of non-functional aspects like performance and reliability are crucial for the success of dynamic distributed systems that are self adaptive. With the success of the Internet and mobile technology, properties like the reliability of connections, available bandwidth and computing resources become an even greater concern. Non-functional requirements, are often difficult to capture, measure, and predict. Therefore, stochastic methods are required to address these aspects. For the same purpose, architecture of dynamic distributed systems, in particular P2P networks is viewed as a graph and modeled by graph transformation.
Power System Simulation: History, State of the Art, and ChallengesLuigi Vanfretti
This talk will give an overview of power system simulation technology through several decades, aiming to provide an understanding of the modeling philosophy and approach that has lead to the state of the art in (domain specific) power system simulation tools. This historical perspective will contrast the de facto proprietary software development method used by the power engineering community, against the open source development model. Aspects of resistance to change particular to the power system engineering community will be highlighted.
Given this particular context, power system simulation faces enormous challenges to adapt in order to satisfy simulation needs of both cyber-physical and sustainable system challenges. Such challenges will be highlighted during the talk.
There is, however, an opportunity for disruptive change in power system simulation technology emerging for the EU Smart Grid Mandate M/490, which requires "a set of consistent standards, which will support the information exchange (communication protocols and data models) and the integration of all users into the electric system operation." These regulatory aspects will be explained to highlight the importance of collaboration between the power system domain and computer system experts.
Open modeling and simulation standards may have a large role to play in the development of the European Smart Grid which will have to overcome challenges related to the design, operation and control of cyber-physical and sustainable electrical energy systems. To contribute to this role, the KTH SmarTS Lab research group has been applying the standardized Modelica language and the FMI standard for model exchange in order to couple the domain specific data exchange model (CIM) with the powerful and modern simulation technologies developed by the Modelica community. These efforts will be also discussed.
Develop a mobility model for MANETs networks based on fuzzy Logiciosrjce
The study and research in the field of networks MANETs depends alleged understand the protocols
well of the simulation process before they are applied in the real world, so that we create an environment
similar to these networks. The problem of a set of nodes connected with each other wirelessly, this requires the
development of a comprehensive model and full and real emulator for the movement of the contract on behalf of
stochastic models. Many models came to address the problems of random models that restricted the movement
of decade barriers as well as the signals exchanged between them, but these models were not receiving a lot of
light on the movement of the contract, such as direction, speed and path that is going by the node. The main
goal is to get a comprehensive model and simulator for all parts of the environment of the barriers and
obstacles to the movement of the nodes and the mobile signal between them as well as to focus on the movement
transactions for the node of the direction, speed, and best way. . This research aims to provide a realistic
mobility model for MANET networks. It also addresses the problem of imprecision in social relationships and
the location where we apply Fuzzy logic.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
ON THE PROBABILITY OF K-CONNECTIVITY IN WIRELESS AD HOC NETWORKS UNDER DIFFER...graphhoc
We compare the probability of k-Connectivity of an ad hoc network under Random Way Point (RWP),City Section and Manhattan mobility models. A Network is said to be k Connected if there exists at least k edge disjoint paths between any pair of nodes in that network at any given time and velocity. Initially, for each of the three mobility models, the movement of the each node in the ad hoc network at a given velocity and time are captured and stored in the Node Movement Database (NMDB). Using the movements in the NMDB, the location of the node at a given time is computed and stored in the Node
Location Database (NLDB).
Analysis of non-functional aspects like performance and reliability are crucial for the success of dynamic distributed systems that are self adaptive. With the success of the Internet and mobile technology, properties like the reliability of connections, available bandwidth and computing resources become an even greater concern. Non-functional requirements, are often difficult to capture, measure, and predict. Therefore, stochastic methods are required to address these aspects. For the same purpose, architecture of dynamic distributed systems, in particular P2P networks is viewed as a graph and modeled by graph transformation.
Power System Simulation: History, State of the Art, and ChallengesLuigi Vanfretti
This talk will give an overview of power system simulation technology through several decades, aiming to provide an understanding of the modeling philosophy and approach that has lead to the state of the art in (domain specific) power system simulation tools. This historical perspective will contrast the de facto proprietary software development method used by the power engineering community, against the open source development model. Aspects of resistance to change particular to the power system engineering community will be highlighted.
Given this particular context, power system simulation faces enormous challenges to adapt in order to satisfy simulation needs of both cyber-physical and sustainable system challenges. Such challenges will be highlighted during the talk.
There is, however, an opportunity for disruptive change in power system simulation technology emerging for the EU Smart Grid Mandate M/490, which requires "a set of consistent standards, which will support the information exchange (communication protocols and data models) and the integration of all users into the electric system operation." These regulatory aspects will be explained to highlight the importance of collaboration between the power system domain and computer system experts.
Open modeling and simulation standards may have a large role to play in the development of the European Smart Grid which will have to overcome challenges related to the design, operation and control of cyber-physical and sustainable electrical energy systems. To contribute to this role, the KTH SmarTS Lab research group has been applying the standardized Modelica language and the FMI standard for model exchange in order to couple the domain specific data exchange model (CIM) with the powerful and modern simulation technologies developed by the Modelica community. These efforts will be also discussed.
Finding Candidate Locations for Aerosol Pollution Monitoring at Street Level ...Vahid Moosavi
Presented at MIT CENSAM Workshop on June 2014 as a part of collaborative project between ETH and MIT in Singapore.
Air pollution at street level: http://censam.mit.edu/research/Pages/Characterization%20of%20airborne%20particles%20in%20outdoor%20environments%20of%20Singapore.aspx
related publication: http://www.atmos-meas-tech.net/8/3563/2015/
poster:http://censam.mit.edu/research/CENSAM%20Publications/Urban/Characterization%20of%20airborne%20particles%20in%20outdoor%20environments%20of%20Singapore/Vahid%20poster.pdf
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Markovian Modeling of Urban Traffic Flows in Coexistence With Urban Data Streams
1. svm@arch.ethz.ch
SEC
Markovian Modeling of Urban Traffic Flows in Coexistence
With Urban Data Streams
Vahid Moosavi
Simulation platform, Future Cities Lab, ETHZ
Supervisor: Professor Ludger Hovestadt
Chair for Computer Aided Architectural Design, Department for Architecture, ETH Zürich
26 April 2013
1
2. Multi-layer modeling and the curse of dimensionality…
2
We take different layers (dimensions) and want to
mimic the behavior.
For example in Traffic modeling:
• Shortest Path and rationality??!!
• Traffic congestions?!
• Traffic Lights?!!
• Lots of other unknown elements that we don’t
know yet and in fact manipulate.
…Curse of Dimensionality
…Complicated models, but not complex
5. 5
Rational (Specific )
Models
Complex (Pre-specific )
Models
Properties of the system for modeling
PossibleRelations
(typesandnumbers)
Multi-Agent
Systems
Urban Cellular
automata
Urban Dynamics
Basic Statistics
(Hypothesis Testing)
Urban Metabolism
Natural
(Deterministic)
Models
Urban Scaling
Social Physics
Fractal Models
Complexity and the Limits of Model-ability in Rational Way
It is not about more data or
more computing power, we
need an abstraction from
the concept of rational
modeling.
6. An inversion in the concept of modeling
6
X Y
X Y
Model
Reality
Analysis
Synthesis Model
Reality
Celebration of Computation
Celebration of Connectedness
Celebration of Analysis
If not then,
7. An inversion in the concept of modeling
7
X Y X Y
Celebration of Computation Celebration of Connectedness
Celebration of Analysis
If not then,
Logic or rationale
Or (descriptive
theories)
ObservationsObservations
Celebration of Computation
supports
8. An example From Language modeling…
Problems
• Sentiment Analysis
• Translation
• Communication
• …
8
Approaches for dealing
with these problems
1. Based on Grammar, Logic
and Model of the language.
(Noam Chomsky)
2. Based on data-driven
probabilistic models.
(Originally by Markov and
now in Google Translate)
… And maybe be a dialectical
approach too...
On Chomsky and the Two Cultures of Statistical Learning: http://norvig.com/chomsky.html
9. Relational Model
Classic SpaceSyntax, London
“The social logic of space,(1984)”
33,000+ taxicabs
GPS Trajectory of Taxicabs,
Beijing, 2012
Inversion in
Modeling
9
Rational Model
X Y X Y
Celebration of Computation Celebration of Connectedness
11. An Experiment : Markovian Models in coexistence with data
streams (using Taxi cabs GPS trajectories)
11
• Each Taxi produces a sequence of
symbols. …It is telling its own story.
• Symbols could be road names, units of
space, district names,…
• Sequence can be based on any time
resolution.
… we can construct a Markov Network
encapsulating the transitions between
states (symbols)
• Remark: The Markov network construction
can be based on a specific time period (e.g.
rush hours, weekends,…) or specific part of
the city.
Possible functions
• Simulation of traffic flow
• Stationary distribution of cars
• Road clustering
• Road Engineering and scenario planning
– Finding critical roads
– Road network sensitivity analysis
– …
– As an opposing or complementary view to
Chomsky, Linell presented interactionism:
The sense-making ability of humans is
rooted in social interaction; the mind is
interactive, dialogical, social, shared,
extended, distributed, etc.
14. Some Properties of Markov Chain in Urban road network
Quantity / Markov Network Trafic Network
Perron Eigenvector (dual) Vehicular density in the city network
Mean First Passage Times Average travel times for a pair of origin/destination
Kemeny constant Average travel time for a random trip
Perron Eigenvector (primal) Congested junctions in the network
Second Eigenvector (dual) Associates nodes to traffic sub-communities
141.Crisostomi, E., Kirkland, S., Shorten, R. (2011), A Google-like model of road network dynamics and its application to regulation and control. International Journal of Control
15. Future Steps
• Time series prediction for individuals
• MCMC for multi-agent based simulation if needed : Data-Driven
Simulation no more direct theory or logic, but in principle we no
longer need simulation but just analysis on top of data-driven models.
For example, there is no need to be able mimicking the behavior of
one day of a city, with urban data streams, we can watch it. We should
go back to the history of simulation as a numerical approximation to
Analytical models, which was the celebration of computing power, but
now the issue is not about the computing power, it is about the limit
of the thing (model based on theories) which are being computed. It is
a limit of model-ability. Then, urban data streams brings a new
capability for us.
15
16. • Markov Modeling of Singapore Ezlink Data
• Based on important link in the Kemeny Analysis, run again the steady state
probability without that area.
• Validation: Use power k of Markov and then compare with the result in K
steps based on empirical data
• Predicting the future states by power of Markov Chain
• Caclulating and visualizing the other network measures
• Accessibility analysis using Mean first passage time: one measure can be just
a an average and deviation
• Use SOM to compare different features such as Kemeny constant effect, First
Eig, Average Mean First Paassage time, Other features such closeness,
betweenness, other network features
16
19. Urban Data Streams Planning Interventions
Markov Chain (MC)
Construction
Updating MC periodically
Urban Segments
Regional Scale
Transition Time
Selected Time Period Traffic Community Detection
Real Time Traffic Flow
Road network Engineering
Expected Empirical Travel Times
Network Analytics
City
Mining and Analysis
Modeling
It is just the presentation of PhD research proposal
Not a progress report
Don’t say about models, just the reason for the limit
Walkability as an example
Godel’s incompleteness theorem
Hamiltonian Complexity Theory to show the limit of Model-ability!!
So, is it enough? Just to visualize?
How to model without direct rational assumptions about the real phenomena?
An inversion in paradigm of experiments and observation
The first one is that cars can be easily equipped to start collecting real data to build the Markov transition matrix.
The second advantage is that from the mathematical analysis of the Markov chain it is possible to infer hidden properties of the underlying road network which can be hardly revealed even by tailored ad-hoc simulations.
Encapsulating the properties in relations
So, is it enough? Just to visualize?
How to model without direct rational assumptions about the real phenomena?
An inversion in paradigm of experiments and observation