Know Thy Neighbor: Towards Optimal Mapping of Contacts to Social Graphs for DTN Routing

2010 ◽  
Author(s):  
Theus Hossmann ◽  
Thrasyvoulos Spyropoulos ◽  
Franck Legendre
Keyword(s):  
Dtn Routing ◽  
Social Graphs

Influence maximization in social graphs based on community structure and node coverage gain

2021 ◽  
Vol 118 ◽  
pp. 327-338
Author(s):  
Zhixiao Wang ◽  
Chengcheng Sun ◽  
Jingke Xi ◽  
Xiaocui Li
Keyword(s):  
Community Structure ◽  
Influence Maximization ◽  
Social Graphs

scholarly journals An Efficient Routing Protocol with Overload Control for Group Mobility in Delay-Tolerant Networking

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 521
Author(s):  
Min Wook Kang ◽  
Yun Won Chung
Keyword(s):  
Routing Protocol ◽  
Overload Control ◽  
Group Mobility ◽  
Movement Model ◽  
Delay Tolerant Networking ◽  
Group Movement ◽  
Dtn Routing ◽  
Military Networks ◽  
Delay Tolerant ◽  
Stable Routing

In delay-tolerant networking (DTN), messages are delivered to destination nodes by using opportunistic contacts between contact nodes, even if stable routing paths from source nodes to destination nodes do not exist. In some DTN network environments, such as military networks, nodes movement follows a group movement model, and an efficient DTN routing protocol is required to use the characteristics of group mobility. In this paper, we consider a network environment, where both intra- and intergroup routing are carried out by using DTN protocols. Then, we propose an efficient routing protocol with overload control for group mobility, where delivery predictability for group mobility is defined and proactive overload control is applied. Performance evaluation results show that the proposed protocol had better delivery ratios and overhead ratios than compared protocols, although the delivery latency was increased.

scholarly journals Assessing the Effectiveness of Social and Political Innovations in the Development of Interaction between the Authorities and the Population during COVID-19: The Implication of Open Innovation

2021 ◽  
Vol 7 (3) ◽  
pp. 172
Author(s):  
Elena Kranzeeva ◽  
Evgeny Golovatsky ◽  
Anna Orlova ◽  
Natalia Nyatina ◽  
Anna Burmakina
Keyword(s):  
Open Innovation ◽  
Remote Access ◽  
Border Region ◽  
Regional Innovation ◽  
Data Format ◽  
Digital Platforms ◽  
Innovation Activities ◽  
Political Interaction ◽  
Social Graphs ◽  
Regions Of Russia

Open innovations combine the interaction of the authorities and the population in regions of Russia. Social and political interaction of Russian network users demonstrates new open forms of political participation, mobilization practices (initiative appeals, petitions), the use of expert systems data, and remote access technologies. The increasing number of initiatives and the growth of online communities involved in the discussion and adjustment of the results of innovation activities require the use of a big data format. The demand for open innovation based on the principles of transparency of social and political interactions is being updated during COVID-19. This study aims to assess the effectiveness of open innovations in social and political interactions during COVID-19. The innovative practices of communication between the population and authorities were studied using DataMining tools based on digital platforms: “Russian Public Initiative”, “Change.org” and “GoogleTrends”. Users’ social graphs represent the visualization in terms of thematic and territorial groupings. The results obtained allow for a conclusion about the dependence of the regional innovation activities on the openness of their communications and their location relative to authoritative and other types of resources. The physical location of the region (center–border region–periphery) and dependence on implementation at the federal, regional or municipal levels are circumstances influencing the effectiveness of social and political innovations.

scholarly journals A Social-Based DTN Routing in Cooperative Vehicular Sensor Networks

2018 ◽  
Vol 27 (01) ◽  
pp. 1741003 ◽  
Author(s):  
Tong Wang ◽  
Yongzhe Zhou ◽  
Xibo Wang ◽  
Yue Cao
Keyword(s):  
Information System ◽  
Sensor Networks ◽  
High Speed ◽  
Delivery Ratio ◽  
Dtn Routing ◽  
Replication Strategy ◽  
Social Metrics ◽  
Routing Mechanism ◽  
Network Overhead ◽  
Overhead Ratio

As a cooperative information system, vehicles in Vehicular Sensor Networks deliver messages based on collaboration. Due to the high speed of vehicles, the topology of the network is highly dynamic, and the network may be disconnected frequently. So how to transfer large files in such network is worth considering. The encountering nodes which never meet before flood messages blindly cause tremendous network overhead. We address this challenge by introducing the Encounter Utility Rank Router (EURR) based on social metrics. EURR includes three cases: Utility Replication Strategy, Lifetime Replication Strategy and SocialRank Replication Strategy. The Lifetime Replication is promising and complements Utility Replication. It enhances the delivery ratio by relaying the copy via the remaining lifetime. Considering the network overhead, the SocialRank Replication replicates a copy according to the SocialRank when two communicating nodes have not met before. The routing mechanism explores the utility of history encounter information and social opportunistic forwarding. The results under the scenario show an advantage of the proposed EURR over the compared algorithms in terms of delivery ratio, average delivery latency and overhead ratio.

scholarly journals A UNIFIED COMMUNITY DETECTION, VISUALIZATION AND ANALYSIS METHOD

2014 ◽  
Vol 17 (01) ◽  
pp. 1450001 ◽  
Author(s):  
MICHEL CRAMPES ◽  
MICHEL PLANTIÉ
Keyword(s):  
Community Detection ◽  
Directed Graphs ◽  
Real Data ◽  
Semantic Interpretation ◽  
Detection Methods ◽  
Analysis Method ◽  
Overlapping Communities ◽  
Social Graphs ◽  
Tractography Data ◽  
Research Domain

With the widespread social networks on the Internet, community detection in social graphs has recently become an important research domain. Interest was initially limited to unipartite graph inputs and partitioned community outputs. More recently, bipartite graphs, directed graphs and overlapping communities have all been investigated. Few contributions however have encompassed all three types of graphs simultaneously. In this paper, we present a method that unifies community detection for these three types of graphs while at the same time it merges partitioned and overlapping communities. Moreover, the results are visualized in a way that allows for analysis and semantic interpretation. For validation purposes this method is experimented on some well-known simple benchmarks and then applied to real data: photos and tags in Facebook and Human Brain Tractography data. This last application leads to the possibility of applying community detection methods to other fields such as data analysis with original enhanced performances.

Sign in / Sign up

Export Citation Format

Share Document