226,063 research outputs found
A Stochastic Resource-Sharing Network for Electric Vehicle Charging
We consider a distribution grid used to charge electric vehicles such that
voltage drops stay bounded. We model this as a class of resource-sharing
networks, known as bandwidth-sharing networks in the communication network
literature. We focus on resource-sharing networks that are driven by a class of
greedy control rules that can be implemented in a decentralized fashion. For a
large number of such control rules, we can characterize the performance of the
system by a fluid approximation. This leads to a set of dynamic equations that
take into account the stochastic behavior of EVs. We show that the invariant
point of these equations is unique and can be computed by solving a specific
ACOPF problem, which admits an exact convex relaxation. We illustrate our
findings with a case study using the SCE 47-bus network and several special
cases that allow for explicit computations.Comment: 13 pages, 8 figure
On Formal Methods for Collective Adaptive System Engineering. {Scalable Approximated, Spatial} Analysis Techniques. Extended Abstract
In this extended abstract a view on the role of Formal Methods in System
Engineering is briefly presented. Then two examples of useful analysis
techniques based on solid mathematical theories are discussed as well as the
software tools which have been built for supporting such techniques. The first
technique is Scalable Approximated Population DTMC Model-checking. The second
one is Spatial Model-checking for Closure Spaces. Both techniques have been
developed in the context of the EU funded project QUANTICOL.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200
Spectrum Sharing in mmWave Cellular Networks via Cell Association, Coordination, and Beamforming
This paper investigates the extent to which spectrum sharing in mmWave
networks with multiple cellular operators is a viable alternative to
traditional dedicated spectrum allocation. Specifically, we develop a general
mathematical framework by which to characterize the performance gain that can
be obtained when spectrum sharing is used, as a function of the underlying
beamforming, operator coordination, bandwidth, and infrastructure sharing
scenarios. The framework is based on joint beamforming and cell association
optimization, with the objective of maximizing the long-term throughput of the
users. Our asymptotic and non-asymptotic performance analyses reveal five key
points: (1) spectrum sharing with light on-demand intra- and inter-operator
coordination is feasible, especially at higher mmWave frequencies (for example,
73 GHz), (2) directional communications at the user equipment substantially
alleviate the potential disadvantages of spectrum sharing (such as higher
multiuser interference), (3) large numbers of antenna elements can reduce the
need for coordination and simplify the implementation of spectrum sharing, (4)
while inter-operator coordination can be neglected in the large-antenna regime,
intra-operator coordination can still bring gains by balancing the network
load, and (5) critical control signals among base stations, operators, and user
equipment should be protected from the adverse effects of spectrum sharing, for
example by means of exclusive resource allocation. The results of this paper,
and their extensions obtained by relaxing some ideal assumptions, can provide
important insights for future standardization and spectrum policy.Comment: 15 pages. To appear in IEEE JSAC Special Issue on Spectrum Sharing
and Aggregation for Future Wireless Network
Rational Trust Modeling
Trust models are widely used in various computer science disciplines. The
main purpose of a trust model is to continuously measure trustworthiness of a
set of entities based on their behaviors. In this article, the novel notion of
"rational trust modeling" is introduced by bridging trust management and game
theory. Note that trust models/reputation systems have been used in game theory
(e.g., repeated games) for a long time, however, game theory has not been
utilized in the process of trust model construction; this is where the novelty
of our approach comes from. In our proposed setting, the designer of a trust
model assumes that the players who intend to utilize the model are
rational/selfish, i.e., they decide to become trustworthy or untrustworthy
based on the utility that they can gain. In other words, the players are
incentivized (or penalized) by the model itself to act properly. The problem of
trust management can be then approached by game theoretical analyses and
solution concepts such as Nash equilibrium. Although rationality might be
built-in in some existing trust models, we intend to formalize the notion of
rational trust modeling from the designer's perspective. This approach will
result in two fascinating outcomes. First of all, the designer of a trust model
can incentivise trustworthiness in the first place by incorporating proper
parameters into the trust function, which can be later utilized among selfish
players in strategic trust-based interactions (e.g., e-commerce scenarios).
Furthermore, using a rational trust model, we can prevent many well-known
attacks on trust models. These two prominent properties also help us to predict
behavior of the players in subsequent steps by game theoretical analyses
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