Supermodular mechanism design

This paper introduces a mechanism design approach that allows dealing with the multiple equilibrium problem, using mechanisms that are robust to bounded rationality. This approach is a tool for constructing supermodular mechanisms, i.e. mechanisms that induce games with strategic complementarities. In quasilinear environments, I prove that if a social choice function can be implemented by a mechanism that generates bounded strategic substitutes - as opposed to strategic complementarities - then this mechanism can be converted into a supermodular mechanism that implements the social choice function. If the social choice function also satisfies some efficiency criterion, then it admits a supermodular mechanism that balances the budget. Building on these results, I address the multiple equilibrium problem. I provide sufficient conditions for a social choice function to be implementable with a supermodular mechanism whose equilibria are contained in the smallest interval among all supermodular mechanisms. This is followed by conditions for supermodular implementability in unique equilibrium. Finally, I provide a revelation principle for supermodular implementation in environments with general preferences.Implementation, mechanisms, learning, strategic complementarities, supermodular games

SkyCDS: A resilient content delivery service based on diversified cloud storage

Cloud-based storage is a popular outsourcing solution for organizations to deliver contents to end-users. However, there is a need for contingency plans to ensure service provision when the provider either suffers outages or is going out of business. This paper presents SkyCDS: a resilient content delivery service based on a publish/subscribe overlay over diversified cloud storage. SkyCDS splits the content delivery into metadata and content storage flow layers. The metadata flow layer is based on publish-subscribe patterns for insourcing the metadata control back to content owner. The storage layer is based on dispersal information over multiple cloud locations with which organizations outsource content storage in a controlled manner. In SkyCDS, the content dispersion is performed on the publisher side and the content retrieving process on the end-user side (the subscriber), which reduces the load on the organization side only to metadata management. SkyCDS also lowers the overhead of the content dispersion and retrieving processes by taking advantage of multi-core technology. A new allocation strategy based on cloud storage diversification and failure masking mechanisms minimize side effects of temporary, permanent cloud-based service outages and vendor lock-in. We developed a SkyCDS prototype that was evaluated by using synthetic workloads and a study case with real traces. Publish/subscribe queuing patterns were evaluated by using a simulation tool based on characterized metrics taken from experimental evaluation. The evaluation revealed the feasibility of SkyCDS in terms of performance, reliability and storage space profitability. It also shows a novel way to compare the storage/delivery options through risk assessment. (C) 2015 Elsevier B.V. All rights reserved.The work presented in this paper has been partially supported by EU under the COST programme Action IC1305, Network for Sustainable Ultrascale Computing (NESUS)

Power System Stabilizer Design Based on a Particle Swarm Optimization Multiobjective Function Implemented Under Graphical Interface

Power system stability considered a necessary condition for normal functioning of an electrical network. The role of regulation and control systems is to ensure that stability by determining the essential elements that influence it. This paper proposes a Particle Swarm Optimization (PSO) based multiobjective function to tuning optimal parameters of Power System Stabilizer (PSS); this later is used as auxiliary to generator excitation system in order to damp electro mechanicals oscillations of the rotor and consequently improve Power system stability. The computer simulation results obtained by developed graphical user interface (GUI) have proved the efficiency of PSS optimized by a Particle Swarm Optimization, in comparison with a conventional PSS, showing stable system responses almost insensitive to large parameter variations.Our present study was performed using a GUI realized under MATLAB in our work

Refactoring GrPPI:Generic Refactoring for Generic Parallelism in C++

Funding: EU Horizon 2020 project, TeamPlay (https://www.teamplay-xh2020.eu), Grant Number 779882, UK EPSRC Discovery, grant number EP/P020631/1, and Madrid Regional Government, CABAHLA-CM (ConvergenciA Big dAta-Hpc: de Los sensores a las Aplicaciones) Grant Number S2018/TCS-4423.The Generic Reusable Parallel Pattern Interface (GrPPI) is a very useful abstraction over different parallel pattern libraries, allowing the programmer to write generic patterned parallel code that can easily be compiled to different backends such as FastFlow, OpenMP, Intel TBB and C++ threads. However, rewriting legacy code to use GrPPI still involves code transformations that can be highly non-trivial, especially for programmers who are not experts in parallelism. This paper describes software refactorings to semi-automatically introduce instances of GrPPI patterns into sequential C++ code, as well as safety checking static analysis mechanisms which verify that introducing patterns into the code does not introduce concurrency-related bugs such as race conditions. We demonstrate the refactorings and safety-checking mechanisms on four simple benchmark applications, showing that we are able to obtain, with little effort, GrPPI-based parallel versions that accomplish good speedups (comparable to those of manually-produced parallel versions) using different pattern backends.Publisher PDFPeer reviewe

Content Delivery and Sharing in Federated Cloud Storage

Cloud-based storage is becoming a cost-effective solution for agencies, hospitals, government instances and scientific centers to deliver and share contents to/with a set of end-users. However, reliability, privacy and lack of control are the main problems that arise when contracting content delivery services with a single cloud storage provider. This paper presents the implementation of a storage system for content delivery and sharing in federated cloud storage networks. This system virtualizes the storage resources of a set of organizations as a single federated system, which is in charge of the content storage. The architecture includes a metadata management layer to keep the content delivery control in-house and a storage synchronization worker/monitor to keep the state of storage resources in the federation as well as to send contents near to the end-users. It also includes a redundancy layer based on a multi-threaded engine that enables the system to withstand failures in the federated network. We developed a prototype based on this scheme as a proof of concept. The experimental evaluation shows the benefits of building content delivery systems in federated cloud environments, in terms of performance, reliability and profitability of the storage space.The work presented in this paper has been partially supported by EU under the COST programme Action IC1305, Network for Sustainable Ultrascale Computing (NESUS)

Restoration of legacy parallelism : transforming pthreads into farm and pipeline patterns

Funding: This work was generously supported by the EU Horizon 2020 project, TeamPlay (https://www.teamplay-h2020.eu), grant number 779882, and UK EPSRC Discovery, grant number EP/P020631/1.Parallel patterns are a high-level programming paradigm that enables non-experts in parallelism to develop structured parallel programs that are maintainable, adaptive, and portable whilst achieving good performance on a variety of parallel systems. However, there still exists a large base of legacy-parallel code developed using ad-hoc methods and incorporating low-level parallel/concurrency libraries such as pthreads without any parallel patterns in the fundamental design. This code would benefit from being restructured and rewritten into pattern-based code. However, the process of rewriting the code is laborious and error-prone, due to typical concurrency and pthreading code being closely intertwined throughout the business logic of the program. In this paper, we present a new software restoration methodology, to transform legacy-parallel programs implemented using pthreads into structured farm and pipeline patterned equivalents. We demonstrate our restoration technique on a number of benchmarks, allowing the introduction of patterned farm and pipeline parallelism in the resulting code; we record improvements in cyclomatic complexity and speedups on a number of representative benchmarks.Publisher PDFPeer reviewe

StochKit-FF: Efficient Systems Biology on Multicore Architectures

The stochastic modelling of biological systems is an informative, and in some cases, very adequate technique, which may however result in being more expensive than other modelling approaches, such as differential equations. We present StochKit-FF, a parallel version of StochKit, a reference toolkit for stochastic simulations. StochKit-FF is based on the FastFlow programming toolkit for multicores and exploits the novel concept of selective memory. We experiment StochKit-FF on a model of HIV infection dynamics, with the aim of extracting information from efficiently run experiments, here in terms of average and variance and, on a longer term, of more structured data.Comment: 14 pages + cover pag

Tourist trip planning functionalities : state-of-the-art and future

When tourists visit a city or region, they cannot visit every point of interest available, as they are constrained in time and budget. Tourist recommender applications help tourists by presenting a personal selection. Providing adequate tour scheduling support for these kinds of applications is a daunting task for the application developer. The objective of this paper is to demonstrate how existing models from the field of Operations Research (OR) fit this scheduling problem, and enable a wide range of tourist trip planning functionalities. Using the Orienteering Problem (OP) and its extensions to model the tourist trip planning problem, allows to deal with a vast number of practical planning problems