This document proposes a framework for modeling human mobility that unifies the social, spatial, and temporal dimensions. It summarizes existing models and their limitations in capturing all dimensions. The proposed framework models visits as sequences rather than trajectories. It takes a social graph and arrival processes as input and outputs contact statistics. Case studies show it can generate different inter-contact time distributions by varying the arrival rates. The framework is customizable and allows analytical analysis of temporal dependencies. It was tested on a real mobility dataset.
An ontology for semantic modelling of virtual worldijaia
This article presents a new representation of semantic virtual environments. We propose to use the ontology as a tool for implementation. Our model, called SVHsIEVs1 provides a consistent representation of the following aspects: the simulated environment, its structure, and the knowledge items using ontology, interactions and tasks that virtual humans can perform in the environment. In SVHsIEVs, we find two type of ontology: the global ontology and the local ontology for Virtual Human. Our architecture has been successfully tested in 3D dynamic environments.
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
COMMUNITY DETECTION USING INTER CONTACT TIME AND SOCIAL CHARACTERISTICS BASED...ijasuc
Delay Tolerant Networks (DTNs) where the node connectivity is opportunistic and end-to-end path between
any pair of source and destination is not guaranteed most of the time. Hence the messages are transferred
from source to destination via intermediate nodes on hop to hop basis using store-carry-forward paradigm.
Due to quick advancement in hand held devices such as smart phone and laptop with support of wireless
communication interface carried by human being, it is possible in coming days to use DTNs for message
dissemination without setting up infrastructure. The routing task becomes challenging in DTNs due to
intermittent network connectivity and the connection opportunity arises only when node comes in
transmission range of each other. The performance of the routing protocols depend on the selection of
appropriate relay node which can deliver the message to final destination in case of source and destination
do not meet at all. Many social characteristics are exhibited by the human being like friendship,
community, similarity and centrality which can be exploited by the routing protocol in order to take the
forwarding decisions. Literature shows that by using these characteristics, the performance of DTN routing
protocols have been improved in terms of delivery probability. The existing routing schemes used
community detection using aggregated contact duration and contact frequency which does not change over
the time period. We propose community detection through Inter Contact Time (ICT) between node pair
using power law distribution where the members of community are added and removed dynamically. We
also considered single copy of each message in entire network to reduce the network overhead. The
proposed routing protocol named Social Based Single Copy Routing (SBSCR) selects the suitable relay
node from the community members only based on the social metrics such as similarity and friendship
together. ICTs show power law nature in human mobility which is used to detect the community structure at
each node. A node maintains its own community and social metrics such as similarity and friendship with
other nodes. Whenever node has to select the relay node then it selects from its community with higher
value of social metric. The simulations are conducted using ONE simulator on the real traces of campus
and conference environments. SBSCR is compared with existing schemes and results show that it
outperforms in terms of delivery probability and delivery delay with comparable overhead ratio.
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
An ontology for semantic modelling of virtual worldijaia
This article presents a new representation of semantic virtual environments. We propose to use the ontology as a tool for implementation. Our model, called SVHsIEVs1 provides a consistent representation of the following aspects: the simulated environment, its structure, and the knowledge items using ontology, interactions and tasks that virtual humans can perform in the environment. In SVHsIEVs, we find two type of ontology: the global ontology and the local ontology for Virtual Human. Our architecture has been successfully tested in 3D dynamic environments.
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
COMMUNITY DETECTION USING INTER CONTACT TIME AND SOCIAL CHARACTERISTICS BASED...ijasuc
Delay Tolerant Networks (DTNs) where the node connectivity is opportunistic and end-to-end path between
any pair of source and destination is not guaranteed most of the time. Hence the messages are transferred
from source to destination via intermediate nodes on hop to hop basis using store-carry-forward paradigm.
Due to quick advancement in hand held devices such as smart phone and laptop with support of wireless
communication interface carried by human being, it is possible in coming days to use DTNs for message
dissemination without setting up infrastructure. The routing task becomes challenging in DTNs due to
intermittent network connectivity and the connection opportunity arises only when node comes in
transmission range of each other. The performance of the routing protocols depend on the selection of
appropriate relay node which can deliver the message to final destination in case of source and destination
do not meet at all. Many social characteristics are exhibited by the human being like friendship,
community, similarity and centrality which can be exploited by the routing protocol in order to take the
forwarding decisions. Literature shows that by using these characteristics, the performance of DTN routing
protocols have been improved in terms of delivery probability. The existing routing schemes used
community detection using aggregated contact duration and contact frequency which does not change over
the time period. We propose community detection through Inter Contact Time (ICT) between node pair
using power law distribution where the members of community are added and removed dynamically. We
also considered single copy of each message in entire network to reduce the network overhead. The
proposed routing protocol named Social Based Single Copy Routing (SBSCR) selects the suitable relay
node from the community members only based on the social metrics such as similarity and friendship
together. ICTs show power law nature in human mobility which is used to detect the community structure at
each node. A node maintains its own community and social metrics such as similarity and friendship with
other nodes. Whenever node has to select the relay node then it selects from its community with higher
value of social metric. The simulations are conducted using ONE simulator on the real traces of campus
and conference environments. SBSCR is compared with existing schemes and results show that it
outperforms in terms of delivery probability and delivery delay with comparable overhead ratio.
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
Measuring and Predicting Departures from Routine in Human MobilityDirk Gorissen
Understanding human mobility patterns is a significant research endeavor that has recently received considerable attention. Developing the science to describe and predict how people move from one place to another during their daily lives promises to address a wide range of societal challenges: from predicting the spread of infectious diseases, improving urban planning, to devising effective emergency response strategies. This presentation will discuss a Bayesian framework to analyse an individual’s mobility patterns and identify departures from routine. It is able to detect both spatial and temporal departures from routine based on heterogeneous sensor data (GPS, Cell Tower, social media, ..) and outperforms existing state-of-the-art predictors. Applications include mobile digital assistants (e.g., Google Now), mobile advertising (e.g., LivingSocial), and crowdsourcing physical tasks (e.g., TaskRabbit).
CD-GAIN: Content Delivery Through the Analysis of Users' Access Patterns, ta...Dima Karamshuk
Using nine months of access logs comprising 1.9Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem to understand the factors affecting adoption and usage of a high bandwidth TV streaming application across different providers. We find evidence that connection speeds are important and that external events can have a huge impact for live TV usage. Then, through a temporal analysis of the access logs, we demonstrate that data usage caps imposed by mobile ISPs significantly affect usage patterns, and look for solutions. We show that product bundle discounts with a related fixed-line ISP, a strategy already employed by some mobile providers, can better support user needs and capture a bigger share of accesses.
To effectively serve massive volumes of video traffic content delivery networks (CDNs) are turning to clients for assistance, creating hybrid peer-assisted content delivery systems. We analyze how peer-assisted CDNs are affected by a number of design obstacles which include: the need of localizing peer-to-peer traffic within ISPs (isp-friendliness), reluctance of users to participate in redistributing the content (partial participation) and necessity to match users with similar bitrate requirements (bitrate stratification).
Identifying Partisan Slant in News Articles and Twitter during Political CrisesDima Karamshuk
In this paper, we are interested in understanding the interrelationships between mainstream and social media in forming public opinion during mass crises, specifically in regards to how events are framed in the mainstream news and on social networks and to how the language used in those frames may allow to infer political slant and partisanship. We study the lingual choices for political agenda setting in mainstream and social media by analyzing a dataset of more than 40M tweets and more than 4M news articles from the mass protests in Ukraine during 2013-2014 — known as "Euromaidan" — and the post-Euromaidan conflict between Russian, pro-Russian and Ukrainian forces in eastern Ukraine and Crimea. We design a natural language processing algorithm to analyze at scale the linguistic markers which point to a particular political leaning in online media and show that political slant in news articles and Twitter posts can be inferred with a high level of accuracy. These findings allow us to better understand the dynamics of partisan opinion formation during mass crises and the interplay between mainstream and social media in such circumstances.
ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BB...Dima Karamshuk
In search of scalable solutions, CDNs are exploring
P2P support. However, the benefits of peer assistance can be limited by various obstacle factors such as ISP friendliness—requiring peers to be within the same ISP, bitrate stratification—the need to match peers with others needing similar bitrate, and partial participation—some peers choosing not to redistribute content.
This work relates potential gains from peer assistance to the average number of users in a swarm, its capacity, and empirically studies the effects of these obstacle factors at scale, using a monthlong trace of over 2 million users in London accessing BBC shows online. Results indicate that even when P2P swarms are localised within ISPs, up to 88% of traffic can be saved. Surprisingly, bitrate stratification results in 2 large sub-swarms and does
not significantly affect savings. However, partial participation, and the need for a minimum swarm size do affect gains. We investigate improvements to gain from increasing content availability through two well-studied techniques: content bundling–combining multiple items to increase availability, and historical caching of previously watched items. Bundling proves ineffective as increased server traffic from larger bundles outweighs benefits
of availability, but simple caching can considerably boost traffic gains from peer assistance.
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Ser...Dima Karamshuk
Using nine months of access logs comprising 1.9
Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem to understand the factors affecting adoption and usage of a high bandwidth TV streaming application across different providers. We find evidence that connection speeds are important and that external events can have a huge impact for live TV usage. Then, through a temporal analysis of the access logs, we demonstrate that data usage caps imposed by mobile ISPs significantly affect usage patterns, and look for solutions. We show that product bundle discounts with a related fixed-line ISP, a strategy already employed by some mobile providers, can better support user needs and capture a bigger share of accesses. We observe that users regularly split their sessions between mobile and fixed-line connections, suggesting a straightforward strategy for offloading by speculatively pre-fetching content from a fixed-line ISP before access on mobile devices.
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Ser...Dima Karamshuk
Using nine months of access logs comprising 1.9
Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem
to understand the factors affecting adoption and usage of a high bandwidth
TV streaming application across different providers.
We find evidence that connection speeds are important and that
external events can have a huge impact for live TV usage. Then,
through a temporal analysis of the access logs, we demonstrate
that data usage caps imposed by mobile ISPs significantly affect
usage patterns, and look for solutions. We show that product
bundle discounts with a related fixed-line ISP, a strategy already
employed by some mobile providers, can better support user
needs and capture a bigger share of accesses. We observe that
users regularly split their sessions between mobile and fixed-line
connections, suggesting a straightforward strategy for offloading
by speculatively pre-fetching content from a fixed-line ISP before
access on mobile devices.
Take-away TV: Recharging Work Commutes with Greedy and Predictive Preloading ...Dima Karamshuk
Mobile data offloading can greatly decrease the load on and usage of cellular data networks by exploiting opportunistic and frequent access to Wi- Fi connectivity. Unfortunately, Wi-Fi access from mobile devices can be difficult during typical work commutes, e.g., via trains or cars on highways. In this paper, we propose a new approach: to preload the mobile device with content that a user might be interested in, and thereby avoid the need for cellular data access. We demonstrate the feasibility of this approach by developing a supervised machine learning model that learns from user preferences for different types of content, and propensity to be guided by the UI of the player, and predictively preload entire TV shows. Testing on a dataset of nearly 3.9 million sessions from all over the UK to BBC TV shows, we find that predictive preloading can save significant share of the mobile data for an average user.
GEOVISUALIZING SPATIO-TEMPORAL PATTERNS IN TENNISDamien Demaj
Traditional methods for summarizing tennis matches have long ignored the spatio-temporal component of the match, and often fail to geovisualize patterns by way of map or graphic. This presentation presents alternative approaches to post-match analysis using geospatial data analysis with a Geographical Information System (GIS). A case study focusing on the spatial variation of serving from the London Olympics Gold Medal match, where Andy Murray defeated Roger Federer 6-2, 6-1, 6-4, is conducted. By mapping the relationship between space and time, we were able to visually and statistically quantify that Federer served with more spatial variation during the match. Murray, however, served with greater spatial variation at key points during the match. Results suggest that there is potential to better understand players serve tendencies using spatio-temporal analysis. The importance of such analysis for coaches, players, fans and the media to further explore player tactics and strategies are discussed.
Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store ...Dima Karamshuk
The problem of identifying the optimal location for a new retail store has been the focus of past research,
especially in the field of land economy, due to its importance in the success of a business. Traditional approaches to the problem have factored in demographics, revenue and aggregated human flow statistics from nearby or remote areas. However, the acquisition of relevant data is usually expensive. With the growth of location-based social networks, fine grained data describing user mobility and popularity of places has recently become attainable.
In this paper we study the predictive power of various machine learning features on the popularity of retail
stores in the city through the use of a dataset collected from Foursquare in New York. The features we mine are
based on two general signals: geographic, where features are formulated according to the types and density of nearby
places, and user mobility, which includes transitions between venues or the incoming flow of mobile users from distant areas. Our evaluation suggests that the best performing features are common across the three different commercial chains considered in the analysis, although variations may exist too, as explained by heterogeneities in the way retail facilities attract users. We also show that performance improves significantly when combining multiple features in supervised learning algorithms, suggesting that the retail success of a business may depend on multiple factors.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
AN GROUP BEHAVIOR MOBILITY MODEL FOR OPPORTUNISTIC NETWORKS csandit
Mobility is regarded as a network transport mechanism for distributing data in many networks.
However, many mobility models ignore the fact that peer nodes often carried by people and
thus move in group pattern according to some kind of social relation. In this paper, we propose
one mobility model based on group behavior character which derives from real movement
scenario in daily life. This paper also gives the character analysis of this mobility model and
compares with the classic Random Waypoint Mobility model.
Markovian Modeling of Urban Traffic Flows in Coexistence With Urban Data StreamsVahid Moosavi
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.
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.
Present new mechanisms for modelling multiple interfaces on a node, support for interference-limited links and a frame-work for modelling complex applications running on the nodes. Furthermore, provide an overview of concrete use cases where the simulator has been successfully exploited to study a variety of aspects related to opportunistic, message-based communications. Node movement is implemented by movement models. These are either synthetic models or existing movement traces. Connectivity between the nodes is based on their location, communication range and the bit-rate. The routing function is implemented by routing modules that decide which messages to forward over existing contacts. Finally, the messages themselves are generated either through event generators that generate random traffic between the nodes, or through applications that generate traffic based on application interactions. The main functions of the simulator are the modelling of node movement, inter-node contacts using various interfaces, routing, message handling and application interactions. Result collection and analysis are done through visualization, reports and post-processing tools.
In this short presentation, we will provide some recent developments in the field of crowd monitoring, modelling and management. We will illustrate these by showing various projects that we are involved in, including the SmartStation project, and the different events organised in and around the city of Amsterdam (including the Europride, SAIL, etc.).
In the talk, we will discuss the different components of the system and the methods and technology involved in these. We focus on advanced data collection techniques, the use of social media data, data fusion and the advanced macroscopic modelling required for this. Also, we will show examples of interventions that have been tested, showing how these systems are used in practise.
Measuring and Predicting Departures from Routine in Human MobilityDirk Gorissen
Understanding human mobility patterns is a significant research endeavor that has recently received considerable attention. Developing the science to describe and predict how people move from one place to another during their daily lives promises to address a wide range of societal challenges: from predicting the spread of infectious diseases, improving urban planning, to devising effective emergency response strategies. This presentation will discuss a Bayesian framework to analyse an individual’s mobility patterns and identify departures from routine. It is able to detect both spatial and temporal departures from routine based on heterogeneous sensor data (GPS, Cell Tower, social media, ..) and outperforms existing state-of-the-art predictors. Applications include mobile digital assistants (e.g., Google Now), mobile advertising (e.g., LivingSocial), and crowdsourcing physical tasks (e.g., TaskRabbit).
CD-GAIN: Content Delivery Through the Analysis of Users' Access Patterns, ta...Dima Karamshuk
Using nine months of access logs comprising 1.9Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem to understand the factors affecting adoption and usage of a high bandwidth TV streaming application across different providers. We find evidence that connection speeds are important and that external events can have a huge impact for live TV usage. Then, through a temporal analysis of the access logs, we demonstrate that data usage caps imposed by mobile ISPs significantly affect usage patterns, and look for solutions. We show that product bundle discounts with a related fixed-line ISP, a strategy already employed by some mobile providers, can better support user needs and capture a bigger share of accesses.
To effectively serve massive volumes of video traffic content delivery networks (CDNs) are turning to clients for assistance, creating hybrid peer-assisted content delivery systems. We analyze how peer-assisted CDNs are affected by a number of design obstacles which include: the need of localizing peer-to-peer traffic within ISPs (isp-friendliness), reluctance of users to participate in redistributing the content (partial participation) and necessity to match users with similar bitrate requirements (bitrate stratification).
Identifying Partisan Slant in News Articles and Twitter during Political CrisesDima Karamshuk
In this paper, we are interested in understanding the interrelationships between mainstream and social media in forming public opinion during mass crises, specifically in regards to how events are framed in the mainstream news and on social networks and to how the language used in those frames may allow to infer political slant and partisanship. We study the lingual choices for political agenda setting in mainstream and social media by analyzing a dataset of more than 40M tweets and more than 4M news articles from the mass protests in Ukraine during 2013-2014 — known as "Euromaidan" — and the post-Euromaidan conflict between Russian, pro-Russian and Ukrainian forces in eastern Ukraine and Crimea. We design a natural language processing algorithm to analyze at scale the linguistic markers which point to a particular political leaning in online media and show that political slant in news articles and Twitter posts can be inferred with a high level of accuracy. These findings allow us to better understand the dynamics of partisan opinion formation during mass crises and the interplay between mainstream and social media in such circumstances.
ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BB...Dima Karamshuk
In search of scalable solutions, CDNs are exploring
P2P support. However, the benefits of peer assistance can be limited by various obstacle factors such as ISP friendliness—requiring peers to be within the same ISP, bitrate stratification—the need to match peers with others needing similar bitrate, and partial participation—some peers choosing not to redistribute content.
This work relates potential gains from peer assistance to the average number of users in a swarm, its capacity, and empirically studies the effects of these obstacle factors at scale, using a monthlong trace of over 2 million users in London accessing BBC shows online. Results indicate that even when P2P swarms are localised within ISPs, up to 88% of traffic can be saved. Surprisingly, bitrate stratification results in 2 large sub-swarms and does
not significantly affect savings. However, partial participation, and the need for a minimum swarm size do affect gains. We investigate improvements to gain from increasing content availability through two well-studied techniques: content bundling–combining multiple items to increase availability, and historical caching of previously watched items. Bundling proves ineffective as increased server traffic from larger bundles outweighs benefits
of availability, but simple caching can considerably boost traffic gains from peer assistance.
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Ser...Dima Karamshuk
Using nine months of access logs comprising 1.9
Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem to understand the factors affecting adoption and usage of a high bandwidth TV streaming application across different providers. We find evidence that connection speeds are important and that external events can have a huge impact for live TV usage. Then, through a temporal analysis of the access logs, we demonstrate that data usage caps imposed by mobile ISPs significantly affect usage patterns, and look for solutions. We show that product bundle discounts with a related fixed-line ISP, a strategy already employed by some mobile providers, can better support user needs and capture a bigger share of accesses. We observe that users regularly split their sessions between mobile and fixed-line connections, suggesting a straightforward strategy for offloading by speculatively pre-fetching content from a fixed-line ISP before access on mobile devices.
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Ser...Dima Karamshuk
Using nine months of access logs comprising 1.9
Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem
to understand the factors affecting adoption and usage of a high bandwidth
TV streaming application across different providers.
We find evidence that connection speeds are important and that
external events can have a huge impact for live TV usage. Then,
through a temporal analysis of the access logs, we demonstrate
that data usage caps imposed by mobile ISPs significantly affect
usage patterns, and look for solutions. We show that product
bundle discounts with a related fixed-line ISP, a strategy already
employed by some mobile providers, can better support user
needs and capture a bigger share of accesses. We observe that
users regularly split their sessions between mobile and fixed-line
connections, suggesting a straightforward strategy for offloading
by speculatively pre-fetching content from a fixed-line ISP before
access on mobile devices.
Take-away TV: Recharging Work Commutes with Greedy and Predictive Preloading ...Dima Karamshuk
Mobile data offloading can greatly decrease the load on and usage of cellular data networks by exploiting opportunistic and frequent access to Wi- Fi connectivity. Unfortunately, Wi-Fi access from mobile devices can be difficult during typical work commutes, e.g., via trains or cars on highways. In this paper, we propose a new approach: to preload the mobile device with content that a user might be interested in, and thereby avoid the need for cellular data access. We demonstrate the feasibility of this approach by developing a supervised machine learning model that learns from user preferences for different types of content, and propensity to be guided by the UI of the player, and predictively preload entire TV shows. Testing on a dataset of nearly 3.9 million sessions from all over the UK to BBC TV shows, we find that predictive preloading can save significant share of the mobile data for an average user.
GEOVISUALIZING SPATIO-TEMPORAL PATTERNS IN TENNISDamien Demaj
Traditional methods for summarizing tennis matches have long ignored the spatio-temporal component of the match, and often fail to geovisualize patterns by way of map or graphic. This presentation presents alternative approaches to post-match analysis using geospatial data analysis with a Geographical Information System (GIS). A case study focusing on the spatial variation of serving from the London Olympics Gold Medal match, where Andy Murray defeated Roger Federer 6-2, 6-1, 6-4, is conducted. By mapping the relationship between space and time, we were able to visually and statistically quantify that Federer served with more spatial variation during the match. Murray, however, served with greater spatial variation at key points during the match. Results suggest that there is potential to better understand players serve tendencies using spatio-temporal analysis. The importance of such analysis for coaches, players, fans and the media to further explore player tactics and strategies are discussed.
Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store ...Dima Karamshuk
The problem of identifying the optimal location for a new retail store has been the focus of past research,
especially in the field of land economy, due to its importance in the success of a business. Traditional approaches to the problem have factored in demographics, revenue and aggregated human flow statistics from nearby or remote areas. However, the acquisition of relevant data is usually expensive. With the growth of location-based social networks, fine grained data describing user mobility and popularity of places has recently become attainable.
In this paper we study the predictive power of various machine learning features on the popularity of retail
stores in the city through the use of a dataset collected from Foursquare in New York. The features we mine are
based on two general signals: geographic, where features are formulated according to the types and density of nearby
places, and user mobility, which includes transitions between venues or the incoming flow of mobile users from distant areas. Our evaluation suggests that the best performing features are common across the three different commercial chains considered in the analysis, although variations may exist too, as explained by heterogeneities in the way retail facilities attract users. We also show that performance improves significantly when combining multiple features in supervised learning algorithms, suggesting that the retail success of a business may depend on multiple factors.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
AN GROUP BEHAVIOR MOBILITY MODEL FOR OPPORTUNISTIC NETWORKS csandit
Mobility is regarded as a network transport mechanism for distributing data in many networks.
However, many mobility models ignore the fact that peer nodes often carried by people and
thus move in group pattern according to some kind of social relation. In this paper, we propose
one mobility model based on group behavior character which derives from real movement
scenario in daily life. This paper also gives the character analysis of this mobility model and
compares with the classic Random Waypoint Mobility model.
Markovian Modeling of Urban Traffic Flows in Coexistence With Urban Data StreamsVahid Moosavi
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.
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.
Present new mechanisms for modelling multiple interfaces on a node, support for interference-limited links and a frame-work for modelling complex applications running on the nodes. Furthermore, provide an overview of concrete use cases where the simulator has been successfully exploited to study a variety of aspects related to opportunistic, message-based communications. Node movement is implemented by movement models. These are either synthetic models or existing movement traces. Connectivity between the nodes is based on their location, communication range and the bit-rate. The routing function is implemented by routing modules that decide which messages to forward over existing contacts. Finally, the messages themselves are generated either through event generators that generate random traffic between the nodes, or through applications that generate traffic based on application interactions. The main functions of the simulator are the modelling of node movement, inter-node contacts using various interfaces, routing, message handling and application interactions. Result collection and analysis are done through visualization, reports and post-processing tools.
In this short presentation, we will provide some recent developments in the field of crowd monitoring, modelling and management. We will illustrate these by showing various projects that we are involved in, including the SmartStation project, and the different events organised in and around the city of Amsterdam (including the Europride, SAIL, etc.).
In the talk, we will discuss the different components of the system and the methods and technology involved in these. We focus on advanced data collection techniques, the use of social media data, data fusion and the advanced macroscopic modelling required for this. Also, we will show examples of interventions that have been tested, showing how these systems are used in practise.
Effects of mobility models and nodes distribution on wireless sensors networksijasuc
Wireless sensor networks (WSN) is an important future technology, in several applications in military,
health, environment and industries. Currently the integration of social and sensor is very important by
considering the characteristics of social networks in designing wireless sensor networks WSN for
improvement such as (number of messages from source to destination, radius of coverage, connectivity, and
spreading). This area has not received much attention and few researches focus on the performance
evaluation. In this paper we have studied the impact of different mobility and distribution models which is a
variable one should define which model is best for the infrastructure given their differences, also study
include the exact effect of nodes distribution and analyzed by calculation the number of messages of 12
cases to get a real performance evaluation under different conditions and same routing techniques. This
work provides us a greater understanding and clear an idea of the effect of mobility plus distribution.
COMMUNITY DETECTION USING INTER CONTACT TIME AND SOCIAL CHARACTERISTICS BASED...ijasuc
Delay Tolerant Networks (DTNs) where the node connectivity is opportunistic and end-to-end path between
any pair of source and destination is not guaranteed most of the time. Hence the messages are transferred
from source to destination via intermediate nodes on hop to hop basis using store-carry-forward paradigm.
Due to quick advancement in hand held devices such as smart phone and laptop with support of wireless
communication interface carried by human being, it is possible in coming days to use DTNs for message
dissemination without setting up infrastructure. The routing task becomes challenging in DTNs due to
intermittent network connectivity and the connection opportunity arises only when node comes in
transmission range of each other. The performance of the routing protocols depend on the selection of
appropriate relay node which can deliver the message to final destination in case of source and destination
do not meet at all. Many social characteristics are exhibited by the human being like friendship,
community, similarity and centrality which can be exploited by the routing protocol in order to take the
forwarding decisions. Literature shows that by using these characteristics, the performance of DTN routing
protocols have been improved in terms of delivery probability. The existing routing schemes used
community detection using aggregated contact duration and contact frequency which does not change over
the time period. We propose community detection through Inter Contact Time (ICT) between node pair
using power law distribution where the members of community are added and removed dynamically. We
also considered single copy of each message in entire network to reduce the network overhead. The
proposed routing protocol named Social Based Single Copy Routing (SBSCR) selects the suitable relay
node from the community members only based on the social metrics such as similarity and friendship
together. ICTs show power law nature in human mobility which is used to detect the community structure at
each node. A node maintains its own community and social metrics such as similarity and friendship with
other nodes. Whenever node has to select the relay node then it selects from its community with higher
value of social metric. The simulations are conducted using ONE simulator on the real traces of campus
and conference environments. SBSCR is compared with existing schemes and results show that it
outperforms in terms of delivery probability and delivery delay with comparable overhead ratio.
Community Detection Using Inter Contact Time and Social Characteristics Based...jake henry
Delay Tolerant Networks (DTNs) where the node connectivity is opportunistic and end-to-end path between
any pair of source and destination is not guaranteed most of the time. Hence the messages are transferred
from source to destination via intermediate nodes on hop to hop basis using store-carry-forward paradigm.
Due to quick advancement in hand held devices such as smart phone and laptop with support of wireless
communication interface carried by human being, it is possible in coming days to use DTNs for message
dissemination without setting up infrastructure. The routing task becomes challenging in DTNs due to
intermittent network connectivity and the connection opportunity arises only when node comes in
transmission range of each other. The performance of the routing protocols depend on the selection of
appropriate relay node which can deliver the message to final destination in case of source and destination
do not meet at all. Many social characteristics are exhibited by the human being like friendship,
community, similarity and centrality which can be exploited by the routing protocol in order to take the
forwarding decisions. Literature shows that by using these characteristics, the performance of DTN routing
protocols have been improved in terms of delivery probability. The existing routing schemes used
community detection using aggregated contact duration and contact frequency which does not change over
the time period. We propose community detection through Inter Contact Time (ICT) between node pair
using power law distribution where the members of community are added and removed dynamically. We
also considered single copy of each message in entire network to reduce the network overhead. The
proposed routing protocol named Social Based Single Copy Routing (SBSCR) selects the suitable relay
node from the community members only based on the social metrics such as similarity and friendship
together. ICTs show power law nature in human mobility which is used to detect the community structure at
each node. A node maintains its own community and social metrics such as similarity and friendship with
other nodes. Whenever node has to select the relay node then it selects from its community with higher
value of social metric. The simulations are conducted using ONE simulator on the real traces of campus
and conference environments. SBSCR is compared with existing schemes and results show that it
outperforms in terms of delivery probability and delivery delay with comparable overhead ratio.
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.
Geo community-based broadcasting for data dissemination in mobile social netw...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Similar to Modeling the Social, Spatial, and Temporal dimensions of Human Mobility in a unifying framework (20)
Geo community-based broadcasting for data dissemination in mobile social netw...
Modeling the Social, Spatial, and Temporal dimensions of Human Mobility in a unifying framework
1. Modeling the Social, Spatial, and Temporal dimensions of
Human Mobility in a unifying framework
Dmytro Karamshuk
IMT - Institutions Markets Technologies
Institute for Advanced Studies, Lucca
January 2013
2. Why do we study human mobility
● modeling ad-hoc wireless networks
● modeling information propagation, disease
spreading etc.
● developing new mobile services, e.g., location
recommendation systems
● security systems in location based social networks
● transportation, urban infrastructure
3. Opportunistic Networks
● Motivation: 5,3 billion mobile devices, 10 billion ARM
processors in embedded systems of vehicles, street
cameras etc.
● Approach: based on 'stare, carry and forward' principle
● Main challenge: forwarding (routing) protocols and more
generally information dissemination
4. Properties of Human Mobility
● in human mobility we study how people visit different places
● we are interested in social, spatial, and temporal characteristics of the
visits
5. Mobility Properties - Spatial
How far we travel from place to place?
M. Gonzalez, C. Hidalgo, A. Barabasi, Understanding individual human mobility
patterns, Nature
6. Mobility Properties – Temporal
● returning time probability ● visits of top k-th location
How frequently we visit different places?
C. Song, T. Koren, P. Wang, A. Barabasi, Modelling the scaling properties
of human mobility, Nature Physics
7. Mobility Properties - Social
● To what extend our
movements depend
on our social ties?
● How the influence of
our social ties depend
on time?
● How the places
associated with
different social
communities are
spatially distributed?
How our social ties influence the choice of the places we visit?
8. Mobility Properties – Social (another view)
● inter-contact time
i.e. time between two consecutive contacts
of two persons (mobile devices)
●
this in t e r-c o n ta c t tim e s characteristic is crucial for studying mobile social
networks, particularly opportunistic networks based on p2p communications
●
usually this is the o u tpu t o f th e m o b ilit y m o de lin g
T. Karagiannis, J. Le Boudec, M. Vojnovic, Power law and exponential
decay of intercontact times between mobile devices, Mobile Computing
9. Mobility Models
● existing models does not combine all directions
● existing models are neither flexible nor controllable
A survey of existing models:
D. Karamshuk, C. Boldrini, M. Conti, and A. Passarella. Human mobility models for
opportunistic networks. IEEE Commun. Mag, 2011
10. Arrival Based Mobility Framework
● defines mobility in terms of visits sequences not trajectories
● customizable for any temporal patterns of visits
● provides a framework for analytical analysis of the temporal
dependencies between visits and contacts
11. Adding Spatial Dimension to Social Graphs
● cliques (i.e., fully connected
sub-graphs) of users share
common meeting places
● cliques are overlapping and
hierarchically organized
● example: a company has
meeting rooms shared by all
employees, while each
subdivision of the company
has their own offices, shared
only by the members of the
subdivision. The subdivisions
might share common
members.
We develop an algorithm that:
● takes a social graph as input
● partitions the graph into a set of overlapping and hierarchically organized cliques
● generates arrival network by assigning each clique a separate meeting place
12. Adding Spatial Dimension to Social Graphs
The clique partitioning algorithm consists of two main parts:
● finding the cover of the maximum overlapping cliques in the input social graph (we
use BronKerbosch algorithm)
● reproducing hierarchical cliques structure by randomly splitting the cliques
14. Adding Temporal Dimension
To characterize the temporal dimension of
human mobility we model time sequences of
users' arrivals to places with stochastic point
processes.
For simplicity we consider that arrival processes are:
● discrete (e.g., with the time unit equal to one day)
● the contact between persons happen if they both arrive in
the same place in the same time slot
Although, the framework could be extended to other cases.
15. Customizing the model
Input: Output:
● social graph ● statistics of contact sequences
● link removal probability
● arrival processes
16. Data Analysis
● 27M check-in records
● 619K users
● 2.4M venues
● 15M user-place pairs and 94K of them
with at least 20 repeats
● 1.3K user pairs with at least 20
contacts
● time period from 21.01.09 to 07.08.11
T. Hossmann, T. Spyropoulos, F. Legendre, Putting contacts into context: Mobility
modeling beyond inter-contact times
17. Individual arrival sequences
● fitting geometric distribution with Maximum Likelihood Estimation
● Pearson's chi-squared test to attest the quality of approximation
● 70% of individual inter-arrivals sequences follows a geometric distribution
● arrival sequences can be potentially approximated by a simple Bernoulli process
18. Flexibility of the Framework
Input: Output:
● social graph and link removal ● statistics of contact sequences
probability measured from the
Gowalla data
● homogenous Bernoulli arrival
processes with the distribution of
rates measured from the Gowalla
data
model is in agreement with data
19. Analytical analysis - Prerequisites
A: Does aggregate power-law
imply power-law for individual
components?
Q: Not necessarily
●A. Passarella and M. Conti. Characterizing aggregate inter-contact times in
heterogeneous opportunistic networks. NETWORKING 2011
20. Analytical analysis - Idea
In the same network with the
same arrival processes
we can obtain very
different inter-contact times
distributions.
21. Analytical Analysis – Contact Process
Contacts between two users in a Contacts between two users in all
single meeting place. shared meeting places.
The rate of the resulting contact process depends on arrival rates as:
22. Analytical Analysis – Scheme
where
● different shapes of the inter-contact times distribution can be obtained by tuning
the distribution of arrival rates
● although we cannot derive a closed-form expression for a general case, we can
do for specific cases, e.g., for exponential or long-tail F(τ)
23. Case study N1 – long-tail ICT
Input: Output:
● random graph with number of nodes ● long-tail distribution of inter-contact
n and probability of link χ times
●
removal probability α
● Bernoulli arrival processes with
rates where Y is a
standard normal random variable
24. Case study N2 – exponential ICT
Input: Output:
● similar as in the first case but the ● inter-contact times distribution with
Bernoulli arrival processes with exponential shape
identical rates
25. Conclusion
● The framework allows us to model the way users visit different
places and contact each other in those places
● The framework is customizable for any social environment by
taking social graph as an input parameter
● The framework is customizable for any temporal patterns of
users' visits to places by taking arrival stochastic processes as an
input parameter
● Temporal characteristics of the contact sequences can be analyzed
analytically
D. Karamshuk, C. Boldrini, M. Conti, and A. Passarella. An arrival based
framework for human mobility modeling. WoWMoM, 2012
D. Karamshuk, C. Boldrini, M. Conti, and A. Passarella. SPoT: Representing
the Social, Spatial, and Temporal Dimensions of Human Mobility with a
Unifying Framework. Under submission.
26. Thank you for attention!
Dmytro Karamshuk
PhD student @ IMT Lucca
Research Associate @ IIT CNR di Pisa
email: karamshuk@gmail.com
follow me on Twitter: @karamshuk