8,526 research outputs found
Optimal deployment of resources for maximizing impact in spreading processes
The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of "influential spreaders" for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings the problem is often characterized by heterogeneous interactions and requires interventions over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. We show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples
A Cost-effective Shuffling Method against DDoS Attacks using Moving Target Defense
Moving Target Defense (MTD) has emerged as a newcomer into the asymmetric
field of attack and defense, and shuffling-based MTD has been regarded as one
of the most effective ways to mitigate DDoS attacks. However, previous work
does not acknowledge that frequent shuffles would significantly intensify the
overhead. MTD requires a quantitative measure to compare the cost and
effectiveness of available adaptations and explore the best trade-off between
them. In this paper, therefore, we propose a new cost-effective shuffling
method against DDoS attacks using MTD. By exploiting Multi-Objective Markov
Decision Processes to model the interaction between the attacker and the
defender, and designing a cost-effective shuffling algorithm, we study the best
trade-off between the effectiveness and cost of shuffling in a given shuffling
scenario. Finally, simulation and experimentation on an experimental software
defined network (SDN) indicate that our approach imposes an acceptable
shuffling overload and is effective in mitigating DDoS attacks
Technological Revolutions and Financial Innovations
In this paper, we study the symbiotic relationship between financial innovation and technological innovation. In particular, we construct a theoretical macroeconomic growth model that correspond to the thesis presented in Perez (2002) that all the technological revolutions and their associated development surges since the Industrial Revolution have been both beneficiaries and stimulants of financial development. We explain the microeconomic foundations of the model and present its steady state solution, emphasizing how the growth rate of the economy depends on parameters characterising the R&D and financial sectors. We then analyze the impact of specific types of financial innovations that predominate in each phase of the technological cycle on the optimum allocation of resources in the economy.Financial Innovation, Technological Revolutions, Economic Growth
Optimal vaccination in a stochastic epidemic model of two non-interacting populations
Developing robust, quantitative methods to optimize resource allocations in
response to epidemics has the potential to save lives and minimize health care
costs. In this paper, we develop and apply a computationally efficient
algorithm that enables us to calculate the complete probability distribution
for the final epidemic size in a stochastic Susceptible-Infected-Recovered
(SIR) model. Based on these results, we determine the optimal allocations of a
limited quantity of vaccine between two non-interacting populations. We compare
the stochastic solution to results obtained for the traditional, deterministic
SIR model. For intermediate quantities of vaccine, the deterministic model is a
poor estimate of the optimal strategy for the more realistic, stochastic case.Comment: 21 pages, 7 figure
Notes on Cloud computing principles
This letter provides a review of fundamental distributed systems and economic
Cloud computing principles. These principles are frequently deployed in their
respective fields, but their inter-dependencies are often neglected. Given that
Cloud Computing first and foremost is a new business model, a new model to sell
computational resources, the understanding of these concepts is facilitated by
treating them in unison. Here, we review some of the most important concepts
and how they relate to each other
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