Putting Contacts into Context: Mobility Modeling beyond Inter-Contact Times
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The document discusses mobility modeling and contact graphs derived from real-world mobility traces. It finds that existing mobility models do not accurately capture the structural properties observed in traces, such as communities being connected by bridging links rather than bridging nodes. The traces show inter-community contacts occurring outside community locations. They also show synchronized social meetings of multiple nodes. The document proposes extending existing models with a social overlay to generate bridging links while maintaining other properties, better reflecting patterns in real-world mobility.
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This document outlines the syllabus for an economics course on Money and Banking taught at Queens College in Fall 2012. The course will focus on central banking, monetary policy, and modern monetary theory using a dynamic aggregate demand and supply model. It lists the instructor, class times, office hours, required textbook, grading structure based on homework assignments and three exams, and a tentative class schedule by week and chapter. Students are expected to attend class regularly, participate in discussions, and complete assigned homework problems from the end of chapters.
MCE
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A Look at the Future of HTML5
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Similar to Putting Contacts into Context: Mobility Modeling beyond Inter-Contact Times
CSE5656 Complex Networks - Final Presentation
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MobiCom CHANTS
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A scalable server architecture for mobile presence services in social network...
This document proposes an efficient and scalable server architecture called PresenceCloud to support large-scale mobile presence services for social network applications. PresenceCloud organizes presence servers into a quorum-based architecture to efficiently search for friends' presence information when a mobile user joins a network. It leverages a directed search algorithm and caching to achieve small constant search latency. Simulations show that PresenceCloud significantly reduces the number of messages generated during searches without compromising search satisfaction levels compared to alternative architectures.
Taxis.key
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Applications and services that take advantage of social data usually infer social relationships using information produced only within their own context. We propose to combine social information from multiple sources into a directed and weighted social multigraph in order to enable novel socially- aware applications and services. We present GeoS, our early prototype of a geo-social data management service which implements a representative set of social inferences. We demonstrate GeoS’ potential for social applications on a collection of social data that combines collocation information and Facebook friendship declarations from 100 students.
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Sub1527
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AN GROUP BEHAVIOR MOBILITY MODEL FOR OPPORTUNISTIC NETWORKS
Mobility is regarded as a network transport mechanism for distributing data in many networks.
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Lecture 01 - Chapter 1 (Part 01): Some basic concept of Operating System (OS)...
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Lecture 01 - Chapter 1 (Part 01): This Lecture show the Overview of Course, What is an Operating System, Operating System Functions, Definition of a Distributed System, Properties of Distributed Systems, Software Concepts, Transparency in a Distributed System, Challenges, Approaches, Scalability Problems, Scalability Examples, Web Search, Financial Transactions, Multiplayer Games. Some basic concept of Operating System (OS).Using Topological Data Analysis to Explore Emergent Consumer Experience from ...
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differences that originate from their focus. Link prediction uses evidence to predict network structure evolution, whereas our focal point is directed communication initiation between
users who are previously not structurally connected. To address this problem, we employ topological evidence in conjunction to transactional information in order to predict communication intention. It is not intuitive whether methods that work well for
link prediction would work well in this case. In fact, we show in this work that network or content evidence, when considered separately, are not sufficiently accurate predictors. Our novel approach, which jointly considers local structural properties of users in a social network, in conjunction with their generated content, captures numerous interactions, direct and indirect, social and contextual, which have up to date been considered independently. We performed an empirical study to evaluate our method using an extracted network of directed @-messages sent between users of a corporate microblogging service, which resembles Twitter. We find that our method outperforms state of the art techniques for link prediction. Our findings have implications for a wide range of social web applications, such as contextual expert recommendation for Q&A, new friendship relationships creation, and targeted content delivery.
Temporal networks - Alain Barrat
- Temporal networks are dynamic networks that change over time. They are commonly represented through temporal contact sequences or time-varying adjacency matrices.
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Resource Mapping Optimization for Distributed Cloud Services - PhD Thesis Def...
The magnitude of data being stored and processed in the Cloud is quickly increasing due to advancements in areas that rely on cloud computing, e.g. Big Data, Internet of Things and mobile code offloading. Concurrently, cloud services are getting more global and geographically distributed. To handle such changes in its usage scenario, the Cloud needs to transform into a completely decentralized, federated and ubiquitous environment similar to the historical transformation of the Internet. Indeed, research ideas for the transformation has already started to emerge including but not limited to Cloud Federations, Multi-Clouds, Fog Computing, Edge Computing, Cloudlets, Nano data centers, etc.
Standardization and resource management come up as the most significant issues for the realization of the distributed cloud paradigm. The focus in this thesis is the latter: efficient management of limited computing and network resources to adapt to the decentralization. Specifically, cloud services that consist of several virtual machines, dedicated network connections and databases are mapped to a multi-provider, geographically distributed and dynamic cloud infrastructure. The objective of the mapping is to improve quality of service in a cost-effective way. To that end; network latency and bandwidth as well as the cost of storage and computation are subjected to a multi-objective optimization.
The first phase of the resource mapping optimization is the topology mapping. In this phase, the virtual machines and network connections (i.e. the virtual cluster) of the cloud service are mapped to the physical cloud infrastructure. The hypothesis is that mapping the virtual cluster to a group of data centers with a similar topology would be the optimal solution.
Replication management is the second phase where the focus is on the data storage. Data objects that constitute the database are replicated and mapped to the storage as a service providers and end devices. The hypothesis for this phase is that an objective function adapted from the facility location problem optimizes the replica placement.
Detailed experiments under real-world as well as synthetic workloads prove that the hypotheses of the both phases are true.
Assigning semantic labels to data sources
This document proposes an approach called SemTyper for assigning semantic labels from a domain ontology to data attributes in a source. SemTyper uses text similarity and statistical tests to holistically label textual and numeric data, respectively. It was evaluated on museum, city, weather, and flight data and showed improved accuracy over prior approaches while training 250x faster. SemTyper can also handle noisy data and works with any user-selected ontology.
Geo community-based broadcasting for data dissemination in mobile social netw...
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.orgSimilar to Putting Contacts into Context: Mobility Modeling beyond Inter-Contact Times (20)
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- 1. Putting Contacts into Context Mobility Modeling beyond Inter-Contact Times Theus Hossmann ETH Zürich, Switzerland Thrasyvoulos Spyropoulos EURECOM, France Franck Legendre ETH Zürich, Switzerland
- 3. Known Mobility Properties MASTERED MASTERED [email_address] Individual Properties Diurnal & weekly periodicity [Henderson et al MobiCom `04] Location preference [Tuduce et al Infocom `05] Power law trip length [Lee et al Infocom `09] Pairwise Properties Heavy tailed aggregate inter-contact times (exponential cut -off) [Chaintreau et al Infocom `06] [Karagiannis et al MobiCom `07] [Cai et al MobiCom `07] Individual pairs with various distributions [Leguay et al Autonomics `07)]
- 5. Methodology [email_address] Mobility Model ?? Synthetic Trace Contact Graph Contact Trace Contact Graph Community Structure? Modularity Community Connections? Bridges Structural Properties?
- 6. Mobility Traces [email_address] Self-reported “check-ins” (like Foursquare) ~ 440’000 users (October 2010) ~ 16.7 Mio check-ins to ~ 1.6 Mio spots 473 “power users” who check-in at least 5 out of 7 days
- 7. Mobility Models [email_address] TVCM (location based) [Spyropoulos et al ToN `09] HCMM (social network based) [Boldrini et al Comp. Comm. `10] SLAW (location based) [Lee et al Infocom `09]
- 9. The Contact Graph [email_address]