Spanders

Tzachar, Nir

doi:10.1145/1774088.1774369

Proceedings of the 2010 ACM Symposium on Applied Computing 2010

DOI: 10.1145/1774088.1774369

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Spanders

Nir Tzachar

Abstract: We consider self-stabilizing and self-organizing distributed construction of a spanner that forms an expander. We use folklore results to randomly define an expander graph. Given the randomized nature of our algorithms, a monitoring technique is presented for ensuring the desired results. The monitoring is based on the fact that expanders have a rapid mixing time and the possibility of examining the rapid mixing time by O(nlogn) short (O(log 4 n) length) random walks even for non regular expanders. We then emp… Show more

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Cited by 15 publications

References 19 publications

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TTLed Random Walks for Collaborative Monitoring in Mobile and Social Networks

Altshuler

Elovici

2011

Handbook of Optimization in Complex Networks

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Complex network and complex systems research has been proven to have great implications in practice in many scopes including Social Networks, Biology, Disease Propagation, and Information Security. One can use complex network theory to optimize resource locations and optimize actions. Randomly constructed graphs and probabilistic arguments lead to important conclusions with a possible great social and financial influence. Security in online social networks has recently become a major issue for network designers and operators. Being "open" in their nature and offering users the ability to compose and share information, such networks may involuntarily be used as an infection platform by viruses and other kinds of malicious software. This is specifically true for mobile social networks, that allow their users to download millions of applications created by various individual programmers, some of which may be malicious or flawed. In order to detect that an application is malicious, monitoring its operation in a real environment for a significant period of time is often required. As the computation and power resources of mobile devices are very limited, a single device can monitor only a limited number of potentially malicious applications locally. In this work, we propose an efficient collaborative monitoring scheme that harnesses the collective resources of many mobile devices, generating a "vaccination"-like effect in the network. We suggest a new local information flooding algorithm called agation (TPP). The algorithm is implemented in any mobile device, periodically monitors one or more applications and reports its conclusions to a small number of other mobile devices, who then propagate this information onwards, whereas each message has a predefined "Time-to-Live" (TTL) counter. The algorithm is analyzed, and is shown to outperform the existing state of the art information propagation algorithms, in terms of convergence time as well as network overhead. We then show both analytically and experimentally that implementing the proposed algorithm significantly reduces the number of infected mobile devices. Finally, we analytically prove that the algorithm is tolerant to the presence of adversarial agents that inject false information into the system.

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TTLed Random Walks for Collaborative Monitoring in Mobile and Social Networks

Altshuler

Elovici

2011

Handbook of Optimization in Complex Networks

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Monitorability Bounds via Expander, Sparsifier and Random Walks

Khankin

2017

Networked Systems

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Self-Stabilizing and Self-Organizing Virtual Infrastructures for Mobile Networks

Tzachar

2010

Monographs in Theoretical Computer Science. An EATCS Series

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Spanders

Cited by 15 publications

References 19 publications

TTLed Random Walks for Collaborative Monitoring in Mobile and Social Networks

TTLed Random Walks for Collaborative Monitoring in Mobile and Social Networks

Monitorability Bounds via Expander, Sparsifier and Random Walks

Self-Stabilizing and Self-Organizing Virtual Infrastructures for Mobile Networks

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