Stronger trust and privacy in social networks via local cooperation1

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Krzysztof Grining ◽  
Marek Klonowski ◽  
Malgorzata Sulkowska
Keyword(s):  
Social Networks ◽  
Real World ◽  
High Performance ◽  
Preferential Attachment ◽  
Formal Analysis ◽  
Real Life ◽  
Communication Overhead ◽  
Power Law Distribution ◽  
Large Groups ◽  
Performance Computing

Abstract In our article, we present several protocols that allow to efficiently construct large groups of users based only on local relations of trust. What is more, our approach proves to need only very small computational and communication overhead. Moreover, we give guarantees that a trusted core of the network is defended, even facing a powerful adversary capable of controlling a vast majority of users. This is non-trivial property in real-life networks, as those are usually modelled using preferential attachment graphs, which are extremely prone to attacks on the hub nodes. We show that using our protocols we can achieve similar robustness as Erdős–Renyí graphs, which, on the contrary, are very resistant against attacks focused on chosen nodes. Our protocols have been tested on graphs representing real-world social networks using high performance computing due to the size of the networks. In addition for some protocols, we provided a formal analysis to prove some phenomena in random graphs following power-law distribution, which we use as a network model. Finally, we explicitly demonstrate how our approach can be used to amplify security offered by some privacy-preserving protocols. We believe however that our results can be also seen as a contribution to fundamental observation about the nature of social networks. These results may help to design protocols, whenever it is necessary to gather a big group of users in highly dynamic or even adversarial settings.

scholarly journals Improving speed of models for improved real-world decision-making

2021 ◽  
Author(s):  
Jason Thompson ◽  
Haifeng Zhao ◽  
Sachith Seneviratne ◽  
Rohan Byrne ◽  
Rajith Vidanaarachichi ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Real World ◽  
High Performance ◽  
Time Pressure ◽  
Practical Importance ◽  
Model Development ◽  
Sudden Onset ◽  
Health Crisis ◽  
Performance Improvements ◽  
Performance Computing

The sudden onset of the COVID-19 global health crisis and as-sociated economic and social fall-out has highlighted the im-portance of speed in modeling emergency scenarios so that ro-bust, reliable evidence can be placed in policy and decision-makers’ hands as swiftly as possible. For computational social scientists who are building complex policy models but who lack ready access to high-performance computing facilities, such time-pressure can hinder effective engagement. Popular and ac-cessible agent-based modeling platforms such as NetLogo can be fast to develop, but slow to run when exploring broad param-eter spaces on individual workstations. However, while deploy-ment on high-performance computing (HPC) clusters can achieve marked performance improvements, transferring models from workstations to HPC clusters can also be a technically challenging and time-consuming task. In this paper we present a set of generic templates that can be used and adapted by NetLogo users who have access to HPC clusters but require ad-ditional support for deploying their models on such infrastruc-ture. We show that model run-time speed improvements of be-tween 200x and 400x over desktop machines are possible using 1) a benchmark ‘wolf-sheep predation’ model in addition to 2) an example drawn from our own work modeling the spread of COVID-19 in Victoria, Australia. We describe how a focus on improving model speed is non-trivial for model development and discuss its practical importance for improved policy and de-cision-making in the real world. We provide all associated doc-umentation in a linked git repository.

scholarly journals GLOBAL OPTIMIZATION OF GRILLAGES USING SIMULATED ANNEALING AND HIGH PERFORMANCE COMPUTING

2010 ◽  
Vol 16 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Dmitrij Šešok ◽  
Jonas Mockus ◽  
Rimantas Belevičius ◽  
Arnas Kačeniauskas
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
High Performance ◽  
Practical Problem ◽  
Real Life ◽  
Optimization Methods ◽  
Medium Size ◽  
Reactive Force ◽  
Standard Medium ◽  
Performance Computing

The aim is to investigate ways of increasing the efficiency of grillage optimization. Following this general aim, two well‐known optimization methods, namely the Genetic Algorithm (GA) and Simulated Annealing (SA), were compared using some standard medium size (10 and 15 piles) examples. The objective function was the maximal vertical reactive force at a support. Coordinates of piles were optimization variables. SA wins and was applied to real‐life problem (55 piles) by parallel computations performed using a powerful cluster. New element is comparison of SA with GA and application of SA to a practical problem of grillage optimization. Santrauka Straipsnio tikslas - ištirti galimus rostverkiniu pamatu optimizavimo būdus. Siekiant šio tikslo du gerai žinomi optimizavimo metodai ‐ genetiniai algoritmai ir atkaitinimo modeliavimo algoritmas ‐ buvo palyginti vidutinio dydžio (10 ir 15 poliu) pavyzdžiams išspresti. Tikslo funkcija imama didžiausia atraminI poliaus reakcija. Projektavimo kintamieji ‐ poliu koordinatIs. Atkaitinimo modeliavimo metodas laimi, todel jis buvo pritaikytas praktiniam uždaviniui (55 poliai) spresti. Spresti buvo naudojamas klasteris. Naujumas ‐ genetiniu algoritmu palyginimas su atkaitinimo modeliavimo metodu bei atkaitinimo modeliavimo metodo pritaikymas sprendžiant praktini uždavini.

scholarly journals Experiences Using Hybrid MPI/OpenMP in the Real World: Parallelization of a 3D CFD Solver for Multi-Core Node Clusters

2010 ◽  
Vol 18 (3-4) ◽  
pp. 127-138 ◽  
Author(s):  
Gabriele Jost ◽  
Bob Robins
Keyword(s):  
Real World ◽  
High Performance ◽  
Programming Model ◽  
Hybrid Approach ◽  
Underwater Vehicles ◽  
Core Node ◽  
Real World Application ◽  
Hardware Platforms ◽  
Control Surfaces ◽  
Performance Computing

Today most systems in high-performance computing (HPC) feature a hierarchical hardware design: shared-memory nodes with several multi-core CPUs are connected via a network infrastructure. When parallelizing an application for these architectures it seems natural to employ a hierarchical programming model such as combining MPI and OpenMP. Nevertheless, there is the general lore that pure MPI outperforms the hybrid MPI/OpenMP approach. In this paper, we describe the hybrid MPI/OpenMP parallelization of IR3D (Incompressible Realistic 3-D) code, a full-scale real-world application, which simulates the environmental effects on the evolution of vortices trailing behind control surfaces of underwater vehicles. We discuss performance, scalability and limitations of the pure MPI version of the code on a variety of hardware platforms and show how the hybrid approach can help to overcome certain limitations.

High-Performance Computing for Theoretical Study of Nanoscale and Molecular Interconnects

2014 ◽  
pp. 513-532
Author(s):  
Rasit O. Topaloglu ◽  
Swati R. Manjari ◽  
Saroj K. Nayak
Keyword(s):  
Integrated Circuits ◽  
High Performance Computing ◽  
Real World ◽  
High Performance ◽  
Quantum Effects ◽  
Accurate Analysis ◽  
Graphical Processing Units ◽  
Graphical Processing ◽  
Silicon Based ◽  
Performance Computing

Interconnects in semiconductor integrated circuits have shrunk to nanoscale sizes. This size reduction requires accurate analysis of the quantum effects. Furthermore, improved low-resistance interconnects need to be discovered that can integrate with biological and nanoelectronic systems. Accurate system-scale simulation of these quantum effects is possible with high-performance computing (HPC), while high cost and poor feasibility of experiments also suggest the application of simulation and HPC. This chapter introduces computational nanoelectronics, presenting real-world applications for the simulation and analysis of nanoscale and molecular interconnects, which may provide the connection between molecules and silicon-based devices. We survey computational nanoelectronics of interconnects and analyze four real-world case studies: 1) using graphical processing units (GPUs) for nanoelectronic simulations; 2) HPC simulations of current flow in nanotubes; 3) resistance analysis of molecular interconnects; and 4) electron transport improvement in graphene interconnects. In conclusion, HPC simulations are promising vehicles to advance interconnects and study their interactions with molecular/biological structures in support of traditional experimentation.

scholarly journals Online Social Networks (OSN) Evolution Model Based on Homophily and Preferential Attachment

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 654 ◽  
Author(s):  
Jebran Khan ◽  
Sungchang Lee
Keyword(s):  
Social Networks ◽  
Structural Properties ◽  
Online Social Networks ◽  
Large Scale ◽  
Preferential Attachment ◽  
Real Life ◽  
Synthetic Data ◽  
Evolution Model ◽  
Scale Invariant ◽  
Scale Free

In this paper, we propose a new scale-free social networks (SNs) evolution model that is based on homophily combined with preferential attachments. Our model enables the SN researchers to generate SN synthetic data for the evaluation of multi-facet SN models that are dependent on users’ attributes and similarities. Homophily is one of the key factors for interactive relationship formation in SN. The synthetic graph generated by our model is scale-invariant and has symmetric relationships. The model is dynamic and sustainable to changes in input parameters, such as number of nodes and nodes’ attributes, by conserving its structural properties. Simulation and evaluation of models for large-scale SN applications need large datasets. One way to get SN data is to generate synthetic data by using SN evolution models. Various SN evolution models are proposed to approximate the real-life SN graphs in previous research. These models are based on SN structural properties such as preferential attachment. The data generated by these models is suitable to evaluate SN models that are structure dependent but not suitable to evaluate models which depend on the SN users’ attributes and similarities. In our proposed model, users’ attributes and similarities are utilized to synthesize SN graphs. We evaluated the resultant synthetic graph by analyzing its structural properties. In addition, we validated our model by comparing its measures with the publicly available real-life SN datasets and previous SN evolution models. Simulation results show our resultant graph to be a close representation of real-life SN graphs with users’ attributes.

Abstractions and Middleware for Petascale Computing and Beyond

2012 ◽  
pp. 161-178
Author(s):  
Ivo F. Sbalzarini
Keyword(s):  
Numerical Simulations ◽  
High Performance Computing ◽  
Data Structures ◽  
High Performance ◽  
Source Code ◽  
Limiting Factors ◽  
Communication Overhead ◽  
Parallel Data ◽  
Petascale Computing ◽  
Performance Computing

As high-performance computing moves to the petascale and beyond, a number of algorithmic and software challenges need to be addressed. This paper reviews the main performance-limiting factors in today’s high-performance computing software and outlines a possible new programming paradigm to address them. The proposed paradigm is based on abstract parallel data structures and operations that encapsulate much of the complexity of an application, but still make communication overhead explicit. The authors argue that all numerical simulations can be formulated in terms of the presented abstractions, which thus define an abstract semantic specification language for parallel numerical simulations. Simulations defined in this language can automatically be translated to source code containing the appropriate calls to a middleware that implements the underlying abstractions. Finally, the structure and functionality of such a middleware are outlined while demonstrating its feasibility on the example of the parallel particle-mesh library (PPM).

Super Leaders

2015 ◽  
pp. 351-377
Author(s):  
Kim Grover-Haskin
Keyword(s):  
High Performance Computing ◽  
Baby Boomers ◽  
Real World ◽  
High Performance ◽  
Leadership Studies ◽  
Talent Pool ◽  
Real World Problem ◽  
The Future ◽  
It Leadership ◽  
Performance Computing

Present day and projected labor demands forecast a need for minds to comprehend in algorithm in order to leverage computing developments for real world problem resolutions. This chapter focuses not so much on solutions to the preparation of the learners and the scientists, but on the future leadership that will advocate and open doors for the high performance computing community to be funded, supported, and practiced. Supercomputing's sustainable future lies in its future of leadership. Studies over the last ten years identify a shift in leadership as the Baby Boomers enter retirement. The talent pool following the Baby Boomers will shrink in numbers between 2010-2020. Women continue to be under represented in IT leadership. This chapter provides information on the talent pool for supercomputing, discusses leadership and organizational culture as influenced by gender, and explores how a mentoring community fosters leaders for the future.

Abstractions and Middleware for Petascale Computing and Beyond

2010 ◽  
Vol 1 (2) ◽  
pp. 40-56 ◽  
Author(s):  
Ivo F. Sbalzarini
Keyword(s):  
Numerical Simulations ◽  
High Performance Computing ◽  
High Performance ◽  
Source Code ◽  
Limiting Factors ◽  
Communication Overhead ◽  
Programming Paradigm ◽  
Parallel Data ◽  
Petascale Computing ◽  
Performance Computing

As high-performance computing moves to the petascale and beyond, a number of algorithmic and software challenges need to be addressed. This paper reviews the main performance-limiting factors in today’s high-performance computing software and outlines a possible new programming paradigm to address them. The proposed paradigm is based on abstract parallel data structures and operations that encapsulate much of the complexity of an application, but still make communication overhead explicit. The authors argue that all numerical simulations can be formulated in terms of the presented abstractions, which thus define an abstract semantic specification language for parallel numerical simulations. Simulations defined in this language can automatically be translated to source code containing the appropriate calls to a middleware that implements the underlying abstractions. Finally, the structure and functionality of such a middleware are outlined while demonstrating its feasibility on the example of the parallel particle-mesh library (PPM).

Topology properties of a weighted multi-local-world evolving network

2015 ◽  
Vol 93 (3) ◽  
pp. 353-360 ◽  
Author(s):  
Meifeng Dai ◽  
Danping Zhang ◽  
Lei Li
Keyword(s):  
Real World ◽  
Weight Distribution ◽  
Preferential Attachment ◽  
Mean Field ◽  
Field Method ◽  
Strength Distribution ◽  
Power Law Distribution ◽  
World Model ◽  
The Mean ◽  
Theoretical Results

Many real-world networks, ranging from the world trade web to the Internet network, have been described by multi-local-worlds. It is obvious that the nodes within a local world are much more connected to each other than to the others outside the local world. A multi-local-world model can capture and describe these real-world networks’ topological properties. Based on the local-world model, a weighted multi-local-world evolving network model is presented. This model combines selected nodes with preferential attachment and three kinds of local changes of weights. Using a rate equation and the mean-field method, we study the network’s properties: the weight distribution and the strength distribution. We theoretically prove that the weight distribution and the strength distribution follow a power-law distribution in some conditions. Numerical simulations are in agreement with the theoretical results.

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