An epidemic model for information diffusion in MANETs
MSWiM '02 Proceedings of the 5th ACM international workshop on Modeling analysis and simulation of wireless and mobile systems
Randomized Broadcast in Networks
SIGAL '90 Proceedings of the International Symposium on Algorithms
Probabilistic Reliable Dissemination in Large-Scale Systems
IEEE Transactions on Parallel and Distributed Systems
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Location-based Services: Fundamentals and Operation
Location-based Services: Fundamentals and Operation
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Proceedings of the 5th international conference on Information processing in sensor networks
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On the application of epidemical spreading in collaborative context-aware computing
ACM SIGMOBILE Mobile Computing and Communications Review
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A comparison of epidemic algorithms in wireless sensor networks
Computer Communications
Modeling of epidemic diffusion in peer-to-peer file-sharing networks
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
Collaborative context determination to support mobile terminal applications
IEEE Wireless Communications
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IEEE Transactions on Neural Networks
An adaptive epidemic information dissemination model for wireless sensor networks
Pervasive and Mobile Computing
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Contemporary distributed systems usually involve the spreading of information by means of ad-hoc dialogs between nodes (peers). This paradigm resembles the spreading of a virus in the biological perspective (epidemics). Such abstraction allows us to design and implement information dissemination schemes with increased efficiency. In addition, elementary information generated at a certain node can be further processed to obtain more specific, higher-level and more valuable information. Such information carries specific semantic value that can be further interpreted and exploited throughout the network. This is also reflected in the epidemical framework through the idea of virus transmutation which is a key component in our model. We establish an analytical framework for the study of a multi-epidemical information dissemination scheme in which diverse 'transmuted epidemics' are spread. We validate our analytical model through simulations. Key outcomes of this study include the assessment of the efficiency of the proposed scheme and the prediction of the characteristics of the spreading process (multi-epidemical prevalence and decay).