Using a desktop grid to support simulation modelling

Simulation is characterized by the need to run multiple sets of computationally intensive experiments. We argue that Grid computing can reduce the overall execution time of such experiments by tapping into the typically underutilized network of departmental desktop PCs, collectively known as desktop grids. Commercial-off-the-shelf simulation packages (CSPs) are used in industry to simulate models. To investigate if Grid computing can benefit simulation, this paper introduces our desktop grid, WinGrid, and discusses how this can be used to support the processing needs of CSPs. Results indicate a linear speed up and that Grid computing does indeed hold promise for simulation

A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresNowadays with the current growth of information exchange, and the increasing mobility of devices, it becomes essential to use technology to monitor this development. For that P2P networks are used, the exchange of information between agencies is facilitated, these now being applied in mobile networks, including MANETs, where they have special features such as the fact that they are semi-centralized, where it takes peers more ability to make a greater role in the network. But those peer with more capacity, which are used in the optimization of various parameters of these systems, such as optimization\to research, are difficult to identify due to the fact that the network does not have a fixed topology, be constantly changing, (we like to go online and offline, to change position, etc.) and not to allow the exchange of large messages. To this end, this thesis proposes a distributed election algorithm of us greater capacity among several possible goals, enhance research in the network. This includes distinguishing characteristics, such as election without global knowledge network, minimal exchange of messages, distributed decision made without dependence on us and the possibility of influencing the election outcome as the special needs of the network

A classification of emerging and traditional grid systems

The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings. However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area

Speeding-up the execution of credit risk simulations using desktop grid computing: A case study

This paper describes a case study that was undertaken at a leading European Investment bank in which desktop grid computing was used to speed-up the execution of Monte Carlo credit risk simulations. The credit risk simulations were modelled using commercial-off-the-shelf simulation packages (CSPs). The CSPs did not incorporate built-in support for desktop grids, and therefore the authors implemented a middleware for desktop grid computing, called WinGrid, and interfaced it with the CSP. The performance results show that WinGrid can speed-up the execution of CSP-based Monte Carlo simulations. However, since WinGrid was installed on non-dedicated PCs, the speed-up achieved varied according to users’ PC usage. Finally, the paper presents some lessons learnt from this case study. It is expected that this paper will encourage simulation practitioners and CSP vendors to experiment with desktop grid computing technologies with the objective of speeding-up simulation experimentation

Grid-enabling FIRST: Speeding up simulation applications using WinGrid

The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrastructures and applications have traditionally been geared towards dedicated, centralized, high performance clusters running on UNIX flavour operating systems (commonly referred to as cluster-based grid computing). This can be contrasted with desktop-based grid computing which refers to the aggregation of non-dedicated, de-centralized, commodity PCs connected through a network and running (mostly) the Microsoft Windowstrade operating system. Large scale adoption of such Windowstrade-based grid infrastructure may be facilitated via grid-enabling existing Windows applications. This paper presents the WinGridtrade approach to grid enabling existing Windowstrade based commercial-off-the-shelf (COTS) simulation packages (CSPs). Through the use of a case study developed in conjunction with Ford Motor Company, the paper demonstrates how experimentation with the CSP Witnesstrade and FIRST can achieve a linear speedup when WinGridtrade is used to harness idle PC computing resources. This, combined with the lessons learned from the case study, has encouraged us to develop the Web service extensions to WinGridtrade. It is hoped that this would facilitate wider acceptance of WinGridtrade among enterprises having stringent security policies in place

Investigating grid computing technologies for use with commercial simulation packages

As simulation experimentation in industry become more computationally demanding, grid computing can be seen as a promising technology that has the potential to bind together the computational resources needed to quickly execute such simulations. To investigate how this might be possible, this paper reviews the grid technologies that can be used together with commercial-off-the-shelf simulation packages (CSPs) used in industry. The paper identifies two specific forms of grid computing (Public Resource Computing and Enterprise-wide Desktop Grid Computing) and the middleware associated with them (BOINC and Condor) as being suitable for grid-enabling existing CSPs. It further proposes three different CSP-grid integration approaches and identifies one of them to be the most appropriate. It is hoped that this research will encourage simulation practitioners to consider grid computing as a technologically viable means of executing CSP-based experiments faster

Supporting simulation in industry through the application of grid computing

An increased need for collaborative research, together with continuing advances in communication technology and computer hardware, has facilitated the development of distributed systems that can provide users access to geographically dispersed computing resources that are administered in multiple computer domains. The term grid computing, or grids, is popularly used to refer to such distributed systems. Simulation is characterized by the need to run multiple sets of computationally intensive experiments. Large scale scientific simulations have traditionally been the primary benefactor of grid computing. The application of this technology to simulation in industry has, however, been negligible. This research investigates how grid technology can be effectively exploited by users to model simulations in industry. It introduces our desktop grid, WinGrid, and presents a case study conducted at a leading European investment bank. Results indicate that grid computing does indeed hold promise for simulation in industry

Towards Practical Access Control and Usage Control on the Cloud using Trusted Hardware

Cloud-based platforms have become the principle way to store, share, and synchronize files online. For individuals and organizations alike, cloud storage not only provides resource scalability and on-demand access at a low cost, but also eliminates the necessity of provisioning and maintaining complex hardware installations. Unfortunately, because cloud-based platforms are frequent victims of data breaches and unauthorized disclosures, data protection obliges both access control and usage control to manage user authorization and regulate future data use. Encryption can ensure data security against unauthorized parties, but complicates file sharing which now requires distributing keys to authorized users, and a mechanism that prevents revoked users from accessing or modifying sensitive content. Further, as user data is stored and processed on remote ma- chines, usage control in a distributed setting requires incorporating the local environmental context at policy evaluation, as well as tamper-proof and non-bypassable enforcement. Existing cryptographic solutions either require server-side coordination, offer limited flexibility in data sharing, or incur significant re-encryption overheads on user revocation. This combination of issues are ill-suited within large-scale distributed environments where there are a large number of users, dynamic changes in user membership and access privileges, and resources are shared across organizational domains. Thus, developing a robust security and privacy solution for the cloud requires: fine-grained access control to associate the largest set of users and resources with variable granularity, scalable administration costs when managing policies and access rights, and cross-domain policy enforcement. To address the above challenges, this dissertation proposes a practical security solution that relies solely on commodity trusted hardware to ensure confidentiality and integrity throughout the data lifecycle. The aim is to maintain complete user ownership against external hackers and malicious service providers, without losing the scalability or availability benefits of cloud storage. Furthermore, we develop a principled approach that is: (i) portable across storage platforms without requiring any server-side support or modifications, (ii) flexible in allowing users to selectively share their data using fine-grained access control, and (iii) performant by imposing modest overheads on standard user workloads. Essentially, our system must be client-side, provide end-to-end data protection and secure sharing, without significant degradation in performance or user experience. We introduce NeXUS, a privacy-preserving filesystem that enables cryptographic protection and secure file sharing on existing network-based storage services. NeXUS protects the confidentiality and integrity of file content, as well as file and directory names, while mitigating against rollback attacks of the filesystem hierarchy. We also introduce Joplin, a secure access control and usage control system that provides practical attribute-based sharing with decentralized policy administration, including efficient revocation, multi-domain policies, secure user delegation, and mandatory audit logging. Both systems leverage trusted hardware to prevent the leakage of sensitive material such as encryption keys and access control policies; they are completely client-side, easy to install and use, and can be readily deployed across remote storage platforms without requiring any server-side changes or trusted intermediary. We developed prototypes for NeXUS and Joplin, and evaluated their respective overheads in isolation and within a real-world environment. Results show that both prototypes introduce modest overheads on interactive workloads, and achieve portability across storage platforms, including Dropbox and AFS. Together, NeXUS and Joplin demonstrate that a client-side solution employing trusted hardware such as Intel SGX can effectively protect remotely stored data on existing file sharing services

Feather forking as a positive force: incentivising green energy production in a blockchain-based smart grid

Climate change represents a serious threat to the health of our planet and imposed a discussion upon energy waste and production. In this paper we propose a smart grid architecture relying on blockchain technology aimed at discouraging the production and distribution of non-renewable energy as the one derived from fossil fuel. Our model relies on a reverse application of a recently introduced attack to the blockchain based on chain forking. Our system involves both a central authority and a number of distributed peers representing the stakeholders of the energy grid. This system preserves those advantages derived from the blockchain and it also address some limitations such as energy waste for mining operations. In addition, the reverse attack we rely on allows to mitigate the behavior of a classic blockchain, which is intrinsecally self-regulated, and to trigger a sort of ethical action which penalizes non-renewable energy producers. Blacklisted stakeholders will be induced to provide their transaction with higher fees in order to preserve the selling rate

Advanced Agent-Based Modeling for Social Networks

Agent-based modeling and simulation have been successfully applied to problems emerging from social sciences and could be profitably used also for the online social networks. However, the tools presently available for agent-based modeling do not offer specific support for social network models. In the present work, we present a unified conceptual framework to develop both novel agent-based and traditional social network models. This conceptual framework is essentially a meta-model to express the other models. In addition, we designed a domain-specific language to formulate the models in an executable way, so that simulations can be performed effortlessly. The language aims at being expressive and powerful for those with a strong background in computing, and yet simple and easy to learn for those with different expertises. We also developed a software platform that can execute such models in an agent-oriented context, providing effective support for large networks. Moreover, the platform hides most of the complexity of running the simulations on remote server-class machines. We validated out approach by translating several traditional models in our meta-model, verifying that the expected features of the models are maintained. The results show that our approach is successful in providing a friendly and easy environment to perform agent-based simulations over social networks, simulations that are of interest both to develop models and to study the results of the models themselves. Then, considering the favorable results we obtained, we applied our platform to the still open problem of creating an entirely distributed social networking system, which, as compared to the centralized ones, yields relevant advantages as far as privacy and resilience are concerned. We developed several models to help us in the understanding of the many issues that a P2P social networking system would have when deployed, and specifically of the well-known issue of the availability of rare resources. Through simulations, we found some criteria for the design of distributed social networks and some operation conditions which may result in a satisfactory user experience in terms of reduced delays in the propagation of information. Consequently, these results allow us to develop now a distributed social networking system optimized by means of our simulations