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Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process;...
This paper considers a widely studied stochastic control problem arising from opportunistic spectrum access in a multichannel system, with the goal of providing a unifying analytical framework whereby a number of prior results may be viewed as special cases. Specifically, we consider a single wireless transceiver/user with access to \(N\) channels, each modeled as an independent identically distributed...
This paper introduces a novel use of concepts from combinatorial group testing and Kalman filtering in detecting faulty sensors in a network when faults are relatively rare. By assigning sensors to specific groups and performing Kalman filter based fault detection over these groups, we can obtain a small binary detection outcome, which can be decoded to reveal the fault state of all sensors in the...
In this paper we introduce the problem of dynamic pricing of power for smart-grid networks. We consider a network utility maximization (NUM) framework in a deterministic setting with a single provider, multiple users and a finite horizon. The provider produces power or buys power in a (deterministic) spot market, and determines a dynamic price to charge the users. The users then adjust their demand...
Combinatorial network optimization algorithms that compute optimal structures taking into account edge weights form the foundation for many network protocols. Examples include shortest path routing, minimal spanning tree computation, maximum weighted matching on bipartite graphs, etc. We present CLRMR, the first online learning algorithm that efficiently solves the stochastic version of these problems...
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