30,526 research outputs found
Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators
Given the rapid rise of electric vehicles (EVs) worldwide, and the ambitious
targets set for the near future, the management of large EV fleets must be seen
as a priority. Specifically, we study a scenario where EV charging is managed
through self-interested EV aggregators who compete in the day-ahead market in
order to purchase the electricity needed to meet their clients' requirements.
With the aim of reducing electricity costs and lowering the impact on
electricity markets, a centralised bidding coordination framework has been
proposed in the literature employing a coordinator. In order to improve privacy
and limit the need for the coordinator, we propose a reformulation of the
coordination framework as a decentralised algorithm, employing the Alternating
Direction Method of Multipliers (ADMM). However, given the self-interested
nature of the aggregators, they can deviate from the algorithm in order to
reduce their energy costs. Hence, we study the strategic manipulation of the
ADMM algorithm and, in doing so, describe and analyse different possible attack
vectors and propose a mathematical framework to quantify and detect
manipulation. Importantly, this detection framework is not limited the
considered EV scenario and can be applied to general ADMM algorithms. Finally,
we test the proposed decentralised coordination and manipulation detection
algorithms in realistic scenarios using real market and driver data from Spain.
Our empirical results show that the decentralised algorithm's convergence to
the optimal solution can be effectively disrupted by manipulative attacks
achieving convergence to a different non-optimal solution which benefits the
attacker. With respect to the detection algorithm, results indicate that it
achieves very high accuracies and significantly outperforms a naive benchmark
Overview of Polkadot and its Design Considerations
In this paper we describe the design components of the heterogenous
multi-chain protocol Polkadot and explain how these components help Polkadot
address some of the existing shortcomings of blockchain technologies. At
present, a vast number of blockchain projects have been introduced and employed
with various features that are not necessarily designed to work with each
other. This makes it difficult for users to utilise a large number of
applications on different blockchain projects. Moreover, with the increase in
number of projects the security that each one is providing individually becomes
weaker. Polkadot aims to provide a scalable and interoperable framework for
multiple chains with pooled security that is achieved by the collection of
components described in this paper
Bounded Decentralised Coordination over Multiple Objectives
We propose the bounded multi-objective max-sum algorithm (B-MOMS), the first decentralised coordination algorithm for multi-objective optimisation problems. B-MOMS extends the max-sum message-passing algorithm for decentralised coordination to compute bounded approximate solutions to multi-objective decentralised constraint optimisation problems (MO-DCOPs). Specifically, we prove the optimality of B-MOMS in acyclic constraint graphs, and derive problem dependent bounds on its approximation ratio when these graphs contain cycles. Furthermore, we empirically evaluate its performance on a multi-objective extension of the canonical graph colouring problem. In so doing, we demonstrate that, for the settings we consider, the approximation ratio never exceeds 2, and is typically less than 1.5 for less-constrained graphs. Moreover, the runtime required by B-MOMS on the problem instances we considered never exceeds 30 minutes, even for maximally constrained graphs with agents. Thus, B-MOMS brings the problem of multi-objective optimisation well within the boundaries of the limited capabilities of embedded agents
Labour market institutions and labour market performance: A survey of the literature
This paper presents a selective survey of the recent literature on labour market institutions. It describes the different empirical approaches used to explore the nexus between labour market institutions and labour market performance. It stresses that the effect of institutions is complex in both stock and flow models and that it is also crucial to take into account the interactions they generate among themselves and with macroeconomic shocks.labour market performance, labour market institutions, redistributive policies, unemployment dynamics, Arpaia, Mourre
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