ONSIDE: Socially-aware and Interest-based dissemination in opportunistic networks

Abstract

Data dissemination in opportunistic networks poses a series of challenges, since there is no central entity aware of all the nodes' subscriptions. Each individual node is only aware of its own interests and those of a node that it is contact with, if any. Thus, dissemination is generally performed using epidemic algorithms that flood the network, but they have the disadvantage that the network overhead and congestion are very high. In this paper, we propose ONSIDE, an algorithm that leverages a node's online social connections (i.e. friends on social networks such as Facebook or Google+), its interests and the history of contacts, in order to decrease congestion and required bandwidth, while not affecting the overall network's hit rate and the delivery latency. We present the results of testing our algorithm using an opportunistic network emulator and three mobility traces taken in different environments.

An Effective Data Transmission Algorithm Based on Social Relationships in Opportunistic Mobile Social Networks

“…Reference [9] proposes an algorithm based on the social characteristics of nodes, such as online social connections, interests, and contact history. The hit ratio and transmission delay of the entire network are not affected.…”

Weak social ties improve content delivery in behavior-aware opportunistic networks

“…the local interest and a summary of the held content -according to the implemented algorithm (5). This information is obtained from the BCM, which has access to the user interests (6). The state information is used to update the local knowledge maintained by n (7) to compute its own utility and the utility of the other node for each message held in the buffer using the utility engine included in the BCM (8).…”

“…Received messages are stored in the buffer for further dissemination. Moreover, the BCM module uses its interest engine to match the content interest against the local interest (6): messages that are of local interest are notified to the user via the delivery.Ind service primitive and inserted in the local content repository (10). The algorithms solving the BehaviorCast problem implement the BCM.…”

“…A content generated by a node is addressed to (''is of interest for'') nodes used to visit the same locations as the source. Another class of approaches (SocialCast [7], ONSIDE [6], SANE [22]) goes a little further by assuming that users with the same interests have the attitude to meet with each other more often than with other users. These are the solutions in the literature more similar to the ICast algorithms proposed in this work and that we use for performance comparison in Section 6.…”

Reliable Platform for Enhanced Living Environment

“…When the number of sending sensors is small, QoS parameters are conformed. This is the reason to simulate very often the network in extreme environment [8][9][10].…”