1,219 research outputs found
Cost-aware caching: optimizing cache provisioning and object placement in ICN
Caching is frequently used by Internet Service Providers as a viable
technique to reduce the latency perceived by end users, while jointly
offloading network traffic. While the cache hit-ratio is generally considered
in the literature as the dominant performance metric for such type of systems,
in this paper we argue that a critical missing piece has so far been neglected.
Adopting a radically different perspective, in this paper we explicitly account
for the cost of content retrieval, i.e. the cost associated to the external
bandwidth needed by an ISP to retrieve the contents requested by its customers.
Interestingly, we discover that classical cache provisioning techniques that
maximize cache efficiency (i.e., the hit-ratio), lead to suboptimal solutions
with higher overall cost. To show this mismatch, we propose two optimization
models that either minimize the overall costs or maximize the hit-ratio,
jointly providing cache sizing, object placement and path selection. We
formulate a polynomial-time greedy algorithm to solve the two problems and
analytically prove its optimality. We provide numerical results and show that
significant cost savings are attainable via a cost-aware design
A Distributed Demand-Side Management Framework for the Smart Grid
This paper proposes a fully distributed Demand-Side Management system for
Smart Grid infrastructures, especially tailored to reduce the peak demand of
residential users. In particular, we use a dynamic pricing strategy, where
energy tariffs are function of the overall power demand of customers. We
consider two practical cases: (1) a fully distributed approach, where each
appliance decides autonomously its own scheduling, and (2) a hybrid approach,
where each user must schedule all his appliances. We analyze numerically these
two approaches, showing that they are characterized practically by the same
performance level in all the considered grid scenarios. We model the proposed
system using a non-cooperative game theoretical approach, and demonstrate that
our game is a generalized ordinal potential one under general conditions.
Furthermore, we propose a simple yet effective best response strategy that is
proved to converge in a few steps to a pure Nash Equilibrium, thus
demonstrating the robustness of the power scheduling plan obtained without any
central coordination of the operator or the customers. Numerical results,
obtained using real load profiles and appliance models, show that the
system-wide peak absorption achieved in a completely distributed fashion can be
reduced up to 55%, thus decreasing the capital expenditure (CAPEX) necessary to
meet the growing energy demand
Defeating jamming with the power of silence: a game-theoretic analysis
The timing channel is a logical communication channel in which information is
encoded in the timing between events. Recently, the use of the timing channel
has been proposed as a countermeasure to reactive jamming attacks performed by
an energy-constrained malicious node. In fact, whilst a jammer is able to
disrupt the information contained in the attacked packets, timing information
cannot be jammed and, therefore, timing channels can be exploited to deliver
information to the receiver even on a jammed channel.
Since the nodes under attack and the jammer have conflicting interests, their
interactions can be modeled by means of game theory. Accordingly, in this paper
a game-theoretic model of the interactions between nodes exploiting the timing
channel to achieve resilience to jamming attacks and a jammer is derived and
analyzed. More specifically, the Nash equilibrium is studied in the terms of
existence, uniqueness, and convergence under best response dynamics.
Furthermore, the case in which the communication nodes set their strategy and
the jammer reacts accordingly is modeled and analyzed as a Stackelberg game, by
considering both perfect and imperfect knowledge of the jammer's utility
function. Extensive numerical results are presented, showing the impact of
network parameters on the system performance.Comment: Anti-jamming, Timing Channel, Game-Theoretic Models, Nash Equilibriu
Good Models and Good Representations are a Support for Learners’ Risk Assessment
When learners have to make sense of risky situations, they can use mathematical models and representations which facilitate successful risk assessment. Based on theoretical considerations on the benefits of specific models and specific representations in such contexts, we present empirical findings of a study which examined whether students use such models and representations in their risk assessment. We conclude that the availability of adequate models to learners may help them gain transparency when facing risks and thus foster their decision-making
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