Abstract-Opportunistic networks enable users to communicate in the absence of network infrastructure. But forwarding messages in such a network incurs costs for nodes in terms of energy and storage. This may lead to nodes being selfish and not forwarding messages for other nodes, resulting in degraded network performance. This paper presents a novel incentive mechanism for opportunistic networks that uses pre-existing social-network information to detect and punish selfish nodes, incentivising them to participate in the network. Trace-driven simulations demonstrate that our mechanism performs better than existing mechanisms, and that social-network information can also be used to improve existing incentive mechanisms.
There is a growing interest in the use of variants of the Transmission Control Protocol (TCP) in high-speed networks. ns-2 has implementations of many of these high-speed TCP variants, as does Linux. ns-2, through an extension, permits the incorporation of Linux TCP code within ns-2 simulations. As these TCP variants become more widely used, users are concerned about how these different variants of TCP might interact in a real network environment -how fair are these protocol variants to each other (in their use of the available capacity) when sharing the same network. Typically, the answer to this question might be sought through simulation and/or by use of an experimental testbed. So, we compare with TCP NewReno the fairness of the congestion control algorithms for 5 high-speed TCP variants -BIC, Cubic, Scalable, High-Speed and Hamilton -on both ns-2 and on an experimental testbed running Linux. In both cases, we use the same TCP code from Linux. We observe some differences between the behaviour of these TCP variants when comparing the testbed results to the results from ns-2, but also note that there is generally good agreement.
Abstract-Opportunistic networking -forwarding messages in a disconnected mobile ad hoc network via any encountered nodes -otters a new mechanism for exploiting the mobile devices that many users already carry. Forwarding messages in such a network often involves the use of social network routing-sending messages via nodes in the sender or recipient's social network. Simple social network routing, however, may broadcast these social networks, which introduces privacy concerns. This paper introduces two methods for enhancing privacy in social network routing by obfuscating the social network graphs used to inform routing decisions. We evaluate these methods using two real-world datasets, and find that it is possible to obfuscate the social network information without leading to a significant decrease in routing performance.
Opportunistic routing protocols can enable message delivery in disconnected networks of mobile devices. To conserve energy in mobile environments, such routing protocols must minimise unnecessary message-forwarding.This paper presents an opportunistic routing protocol that leverages social role information. We compute node roles from a social network graph to identify nodes with similar contact relationships, and use these roles to determine routing decisions. By using pre-existing social network information, such as online social network friends, to determine roles, we show that our protocol can bootstrap a new opportunistic network without the delay incurred by encounter-history-based routing protocols such as SimbetTS. Simulations with four real-world datasets show improved performance over SimbetTS, with performance approaching Epidemic routing in some scenarios.
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