Social DTN routing

Bigwood, Greg; Henderson, Tristan

doi:10.1145/1544012.1544047

Cited by 8 publications

(8 citation statements)

References 6 publications

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“…Most of these defenses weigh trust in the social graph, and an algorithmic property that makes the operation of the defense on top of social network at reasonable cost. Routing and information sharing using social networks is explored in [4], [5], [6], [8], [20], [21] for different settings, where it is shown that connectivity in social graphs can be of benefit in disconnected networks. However, in all of those works collaboration is assumed to be categorical, and there were no attempts in the literature to characterize collaboration and understand how it impacts the cost of operating such routing and sharing algorithms and applications on top of social networks.…”

Section: Related Workmentioning

confidence: 99%

“…This popularity of social networks has motivated a wide spectrum of new technologies. Algorithms, protocols, and systems have been widely proposed on top of social networks, including applications to random-walk based routing [4]- [8], shortest-path based routing [9]- [11], social gossip [12]- [14], Sybil defenses [15]- [17], anonymous communication systems [18], [19], and information sharing [20], [21], among other technologies. Open-source software package of routing on top of social networks is available in [22], and is based on an ealier work that appeared in [23].…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Collaboration in Social Network-enabled Routing

2016

KSII TIIS

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Connectivity and trust in social networks have been exploited to propose applications on top of these networks, including routing, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-enabled routing applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance of such applications, including random walk-based routing, shortest path based routing, breadth-first-search based routing, and Dijkstra routing. By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterizing Collaboration in Social Network-enabled Routing

2016

KSII TIIS

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“…In the recent literature, there has been a lot of interest in the distributed computing community for exploiting social networks to perform trustworthy computations. Examples of these literature works include exploiting social networks for cryptographic signing services [22], Sybil defenses (i.e., addressing attacks in which a single node creates multiple identities and tries to act as if it is multiple nodes to tamper with the normal operation of a distributed system) [11], [23], and routing in many settings including the delay tolerant networks [24], [25]. In all of these cases, along with the algorithmic property in these social networks, the built designs exploit the trust in social networks.…”

Section: The Case For Socialcloudmentioning

confidence: 99%

“…Systems built on top of social networks include file sharing [32], [7], [41], [26], anonymous communication [42], [33], Sybil defenses [11], [23], [43], [44], [10], [26], routing [24], [25], [45], referral and filtering [46], content distribution [47], [48], and live streaming systems [49], among many others [50]. Most of these systems use social networks' trust and connectivity for their operation.…”

Section: Related Workmentioning

confidence: 99%

Trustworthy Distributed Computing on Social Networks

Mohaisen¹,

Tran

Chandra

et al. 2014

IEEE Trans. Serv. Comput.

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In this paper we investigate a new computing paradigm, called SocialCloud, in which computing nodes are governed by social ties driven from a bootstrapping trust-possessing social graph. We investigate how this paradigm differs from existing computing paradigms, such as grid computing and the conventional cloud computing paradigms. We show that incentives to adopt this paradigm are intuitive and natural, and security and trust guarantees provided by it are solid. We propose metrics for measuring the utility and advantage of this computing paradigm, and using real-world social graphs and structures of social traces; we investigate the potential of this paradigm for ordinary users. We study several design options and trade-offs, such as scheduling algorithms, centralization, and straggler handling, and show how they affect the utility of the paradigm. Interestingly, we conclude that whereas graphs known in the literature for high trust properties do not serve distributed trusted computing algorithms, such as Sybil defensesVfor their weak algorithmic properties, such graphs are good candidates for our paradigm for their self-load-balancing features.

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“…These include random-walk based routing [1], [4], [6], [15], [16], shortest-path based routing [23], [10], Sybil defenses [28], [29], among other technologies.…”

Section: Introductionmentioning

confidence: 99%

Collaboration in social network-based information dissemination

Mohaisen

Abuhmed

Zhu

et al. 2012

2012 IEEE International Conference on Communications (ICC)

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Connectivity and trust within social networks have been exploited to build applications on top of these networks, including information dissemination, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-based information dissemination applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance on such applications.By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.

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Social DTN routing

Cited by 8 publications

References 6 publications

Characterizing Collaboration in Social Network-enabled Routing

Characterizing Collaboration in Social Network-enabled Routing

Trustworthy Distributed Computing on Social Networks

Collaboration in social network-based information dissemination

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