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

Adaptive Load Balancing: A Study in Multi-Agent Learning

We study the process of multi-agent reinforcement learning in the context of load balancing in a distributed system, without use of either central coordination or explicit communication. We first define a precise framework in which to study adaptive load balancing, important features of which are its stochastic nature and the purely local information available to individual agents. Given this framework, we show illuminating results on the interplay between basic adaptive behavior parameters and their effect on system efficiency. We then investigate the properties of adaptive load balancing in heterogeneous populations, and address the issue of exploration vs. exploitation in that context. Finally, we show that naive use of communication may not improve, and might even harm system efficiency.Comment: See http://www.jair.org/ for any accompanying file

Privacy preserving distributed optimization using homomorphic encryption

This paper studies how a system operator and a set of agents securely execute a distributed projected gradient-based algorithm. In particular, each participant holds a set of problem coefficients and/or states whose values are private to the data owner. The concerned problem raises two questions: how to securely compute given functions; and which functions should be computed in the first place. For the first question, by using the techniques of homomorphic encryption, we propose novel algorithms which can achieve secure multiparty computation with perfect correctness. For the second question, we identify a class of functions which can be securely computed. The correctness and computational efficiency of the proposed algorithms are verified by two case studies of power systems, one on a demand response problem and the other on an optimal power flow problem.Comment: 24 pages, 5 figures, journa

Ant colony system-based applications to electrical distribution system optimization

Chapter 16, February 201

Blackboard Rules for Coordinating Context-aware Applications in Mobile Ad Hoc Networks

Thanks to improvements in wireless communication technologies and increasing computing power in hand-held devices, mobile ad hoc networks are becoming an ever-more present reality. Coordination languages are expected to become important means in supporting this type of interaction. To this extent we argue the interest of the Bach coordination language as a middleware that can handle and react to context changes as well as cope with unpredictable physical interruptions that occur in opportunistic network connections. More concretely, our proposal is based on blackboard rules that model declaratively the actions to be taken once the blackboard content reaches a predefined state, but also that manage the engagement and disengagement of hosts and transient sharing of blackboards. The idea of reactiveness has already been introduced in previous work, but as will be appreciated by the reader, this article presents a new perspective, more focused on a declarative setting.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

Statistical structures for internet-scale data management

Efficient query processing in traditional database management systems relies on statistics on base data. For centralized systems, there is a rich body of research results on such statistics, from simple aggregates to more elaborate synopses such as sketches and histograms. For Internet-scale distributed systems, on the other hand, statistics management still poses major challenges. With the work in this paper we aim to endow peer-to-peer data management over structured overlays with the power associated with such statistical information, with emphasis on meeting the scalability challenge. To this end, we first contribute efficient, accurate, and decentralized algorithms that can compute key aggregates such as Count, CountDistinct, Sum, and Average. We show how to construct several types of histograms, such as simple Equi-Width, Average-Shifted Equi-Width, and Equi-Depth histograms. We present a full-fledged open-source implementation of these tools for distributed statistical synopses, and report on a comprehensive experimental performance evaluation, evaluating our contributions in terms of efficiency, accuracy, and scalability

Fault Tolerant Adaptive Parallel and Distributed Simulation through Functional Replication

This paper presents FT-GAIA, a software-based fault-tolerant parallel and distributed simulation middleware. FT-GAIA has being designed to reliably handle Parallel And Distributed Simulation (PADS) models, which are needed to properly simulate and analyze complex systems arising in any kind of scientific or engineering field. PADS takes advantage of multiple execution units run in multicore processors, cluster of workstations or HPC systems. However, large computing systems, such as HPC systems that include hundreds of thousands of computing nodes, have to handle frequent failures of some components. To cope with this issue, FT-GAIA transparently replicates simulation entities and distributes them on multiple execution nodes. This allows the simulation to tolerate crash-failures of computing nodes. Moreover, FT-GAIA offers some protection against Byzantine failures, since interaction messages among the simulated entities are replicated as well, so that the receiving entity can identify and discard corrupted messages. Results from an analytical model and from an experimental evaluation show that FT-GAIA provides a high degree of fault tolerance, at the cost of a moderate increase in the computational load of the execution units.Comment: arXiv admin note: substantial text overlap with arXiv:1606.0731