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Message Forwarding Strategies
Published in Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Hongbo Zhu, Device-to-Device based Proximity Service, 2017
Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Hongbo Zhu
A social graph is an intuitive source for many social metrics such as friendship. Unfortunately, it is not always available (due to either privacy or security reasons) or hard to be obtained via disclosed social data [7]. However, with new networking technology, it is possible to study relationships among people by observing their interactions and interests over wireless networks. Building a contact graph is a common way to study the interactions among people in a network, and thus analyze their relationships and estimate the social metrics among them. In MSNPs, each possible packet forwarding happens when two mobile nodes are in contact (i.e., within transmission range of each other). By recording contacts seen in the past, a contact graph can be generated, where each vertex denotes a mobile node (device or person who carries the device), and each edge represents one or more past meetings between two nodes. An edge in this contact graph conveys the information that two nodes encountered each other in the past. Thus, the existence of an edge intends to have predictive capacity for future contacts. A contact graph can be constructed separately for each single time slot in the past, or it can be constructed to record the encounters in a specific period of time by assigning a set of parameters to each edge to record the time, the frequency, and the duration of these encounters. From the observation that people with close relationships, such as friends, family members, and so on, tend to meet more often, more regular and with longer duration, we can extract nodes’ relationships from the recorded contact graph, estimate their social metrics, and use such information to choose relays with higher probabilities of successful forwarding.
Research in network monitoring: Connections with SPM and new directions
Published in Quality Engineering, 2021
Nathaniel T. Stevens, James D. Wilson, Anne R. Driscoll, Ian McCulloh, George Michailidis, Cecile Paris, Peter Parker, Kamran Paynabar, Marcus B. Perry, Mostafa Reisi-Gahrooei, Srijan Sengupta, Ross Sparks
Monitoring contact sequences: By monitoring one or more contact sequences of a network, one can potentially develop strategies for detecting changes in the spread of information or disease over time. For example, Figure 1a shows a contact graph where the times of contacts between vertices are shown on the edges. Figure 1b shows a time series plot of the contacts explicitly. See Holme (2005) and Holme and Saramäki (2012) for information on contact sequences and temporal networks in general.