Simulating node selfishness in opportunistic networks

Author(s):  
Annalisa Socievole ◽  
Floriano De Rango ◽  
Antonio Caputo ◽  
Salvatore Marano
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Annalisa Socievole ◽  
Antonio Caputo ◽  
Floriano De Rango ◽  
Peppino Fazio

When the connection to Internet is not available during networking activities, an opportunistic approach exploits the encounters between mobile human-carried devices for exchanging information. When users encounter each other, their handheld devices can communicate in a cooperative way, using the encounter opportunities for forwarding their messages, in a wireless manner. But, analyzing real behaviors, most of the nodes exhibit selfish behaviors, mostly to preserve the limited resources (data buffers and residual energy). That is the reason why node selfishness should be taken into account when describing networking activities: in this paper, we first evaluate the effects of node selfishness in opportunistic networks. Then, we propose a routing mechanism for managing node selfishness in opportunistic communications, namely, SORSI (Social-based Opportunistic Routing with Selfishness detection and Incentive mechanisms). SORSI exploits the social-based nature of node mobility and other social features of nodes to optimize message dissemination together with a selfishness detection mechanism, aiming at discouraging selfish behaviors and boosting data forwarding. Simulating several percentages of selfish nodes, our results on real-world mobility traces show that SORSI is able to outperform the social-based schemes Bubble Rap and SPRINT-SELF, employing also selfishness management in terms of message delivery ratio, overhead cost, and end-to-end average latency. Moreover, SORSI achieves delivery ratios and average latencies comparable to Epidemic Routing while having a significant lower overhead cost.


2011 ◽  
Vol 24 (11) ◽  
pp. 1261-1269 ◽  
Author(s):  
Sihai Zhang ◽  
Hongyang Qiu ◽  
Yuan Liu ◽  
Wuyang Zhou

2013 ◽  
Vol 24 (2) ◽  
pp. 230-242
Author(s):  
Liang-Yin CHEN ◽  
Zhen-Lei LIU ◽  
Xun ZOU ◽  
Zheng-Kun XU ◽  
Zhen-Qian GUO ◽  
...  

2014 ◽  
Vol 24 (3) ◽  
pp. 507-525 ◽  
Author(s):  
Lei WU ◽  
De-An WU ◽  
Ming LIU ◽  
Xiao-Min WANG ◽  
Hai-Gang GONG

2010 ◽  
Vol 30 (3) ◽  
pp. 723-728 ◽  
Author(s):  
Zhi REN ◽  
Yong HUANG ◽  
Qian-bin CHEN

2021 ◽  
Vol 104 ◽  
pp. 102208
Author(s):  
Samaneh Rashidibajgan ◽  
Thomas Hupperich ◽  
Robin Doss ◽  
Anna Förster

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Enrique Hernández-Orallo ◽  
Antonio Armero-Martínez

One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, opportunistic networks, etc. In this paper, we propose the use of these models for evaluating the temporal and spatial risk of transmission of the COVID-19 disease. First, we study both pure synthetic model and simulated models based on pedestrian simulators, generated for real urban scenarios such as a square and a subway station. In order to evaluate the risk, two different risks of exposure are defined. The results show that we can obtain not only the temporal risk but also a heat map with the exposure risk in the evaluated scenario. This is particularly interesting for public spaces, where health authorities could make effective risk management plans to reduce the risk of transmission.


2021 ◽  
Vol 187 ◽  
pp. 200-205
Author(s):  
Meiqi Ji ◽  
Xuerong Cui ◽  
Juan Li ◽  
Tong Xu ◽  
Shibao Li ◽  
...  

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