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The large-scale adoption of the Web 2.0 paradigm has revolutionized the way we interact with the Web today. End-users, so far mainly passive consumers of information are now becoming active information producers, creating, uploading, and commenting on all ...
We present a methodology for enhancing the delivery of user-generated content in online social networks. To this end, we first regularize the social graph via node capacity and link cost information associated with the underlying data network. We then desi ...
In this work we consider a graph G where a common source sends two messages W1 and W2 to several receivers D1, D2, . . . , DK. The first two receivers D1 and D2 would like to receive message W1, while receivers D3, . . . , DK would like to receive both mes ...
Embedded wireless networks find a broad spectrum of applications in transportation, environmental monitoring, logistics, supply chain management, and "pocketswitched" communication. The node mobility patterns in these applications tend to give rise to spat ...
Reinforcement Learning (RL) is an approach for training agent's behavior through trial-and-error interactions with a dynamic environment. An important problem of RL is that in large domains an enormous number of decisions are to be made. Hence, instead of ...
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This paper investigates context-driven flow allocation and media delivery in online social networks. We exploit information on contacts and content preferences found in social networking applications to provide efficient network services and operation at t ...
We consider communication of two degraded mes- sage sets over graphs where a common source sends two prioritized messages (a common and a private message) to several receivers. All receivers require the common message and a subset of the receivers require ...
Since the seminal work of Watts in the late 90s [1], graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures [2]. Most studies have focused on functional connectivity defined between whole brain regions, us ...
We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying th ...
We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying th ...
