NDLI: A social aggregation based combination movement model for opportunistic networks

Content Provider	IEEE Xplore Digital Library
Author	Xuebin Ma Zhenchao Ouyang Liting Wang Jing Bai
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Inner Mongolia Univ., Hohhot, China (Xuebin Ma; Zhenchao Ouyang; Liting Wang; Jing Bai)
Abstract	Simulations with trace dataset and synthetic movement models are the two main methods for measuring routing protocols and QoS schemes in Opportunistic Networks. But the trace dataset cannot meet the needs of all situations and it is notoriously difficult to be collected. Traditional synthetic movement models are easy to be used, but they do not capture the detailed mobile characteristics of the human. We propose a social aggregation based combination movement model for Opportunistic Networks simulations. In our model, we use several adjustable random distribution generators to generate time-variant mobility parameters and build multiple sub-models to describe more detailed human behavior. By combining those sub-models, which based on a reasonable combination mechanism, one can reproduce complex human activities. So, routing protocols and applications can be tested on our model. We compare our model with different trace datasets and traditional movement models in the Opportunistic Networks Environment (ONE) simulator. Simulation results demonstrate that the model has higher accuracy than traditional movement models and its mobility pattern approximates to real trace datasets.
Starting Page	565
Ending Page	570
File Size	740922
Page Count	6
File Format	PDF
ISBN	9781479934942
DOI	10.1109/ICUFN.2014.6876859
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Movement Mode Trace Date Opportunistic Networks Simulation ONE Wavelength division multiplexing Educational institutions Generators Libraries Data models Mobile nodes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

SAME: A students' daily activity mobility model for campus delay-tolerant networks

Identifying high dissemination capability nodes in opportunistic social networks

Enhanced Lobby Influence: Knowledge based content forwarding algorithm for opportunistic communication networks

Lobby Influence: Opportunistic forwarding algorithm based on human social relationship patterns

A Solution Proposal to the Preferred Nodes Problem in Social-Based Opportunistic Protocols

Impact of Mobility Models on Social Structure Formation in Opportunistic Networks

Simulation Research of Opportunistic Routing Oriented to Network Metrics

Techniques for Radio over Fiber Networks

TOSS: Traffic offloading by social network service-based opportunistic sharing in mobile social networks

A social aggregation based combination movement model for opportunistic networks

Similar Documents

SAME: A students' daily activity mobility model for campus delay-tolerant networks

Identifying high dissemination capability nodes in opportunistic social networks

Enhanced Lobby Influence: Knowledge based content forwarding algorithm for opportunistic communication networks

Lobby Influence: Opportunistic forwarding algorithm based on human social relationship patterns

A Solution Proposal to the Preferred Nodes Problem in Social-Based Opportunistic Protocols

Impact of Mobility Models on Social Structure Formation in Opportunistic Networks

Simulation Research of Opportunistic Routing Oriented to Network Metrics

Techniques for Radio over Fiber Networks

TOSS: Traffic offloading by social network service-based opportunistic sharing in mobile social networks

A social aggregation based combination movement model for opportunistic networks