Blockchain Papers

Morné Pretorius, Nelisiwe Dlamini, Sthembile Mthethwa

No abstract is available for this record.

Anish Jindal, Jakob Kronawitter, Ramona Kühn, Martin Bor · 10 authors

Abstract With the increased penetration of distributed renewable energy sources (DRES) in the grid, new pathways are required to keep the electricity distribution system stable. The provision of ancillary services (AS) by the DRES can contribute in this regard. However, it is necessary to communicate the need for AS from the third party providers such as distribution system operator (DSO) to the DRES in an efficient and scalable manner. To this end, a flexible information and communication technology (ICT) architecture is presented in this paper, and the requirements for the architecture are elaborated. We argue that this architecture is capable of supporting the present and future needs of electricity distribution networks. To illustrate its utility and effectiveness, an accounting use case for DSOs has been presented; it describes a remuneration scheme for the AS provision. A dashboard has been developed to enable communication via this architecture and to allow control of the grid. In addition, a distributed ledger technology for the realization of accounting has been analysed with respect to its scalability and performance capabilities.

Sergio Rajsbaum, Michel Raynal

Modern computing systems are highly concurrent. Threads run concurrently in shared-memory multi-core systems, and programs run in different servers communicating by sending messages to each other. Concurrent programming is hard because it requires to cope with many possible, unpredictable behaviors of the processes, and the communication media. The article argues that right from the start in 1960's, the main way of dealing with concurrency has been by reduction to sequential reasoning. It traces this history, and illustrates it through several examples, from early ideas based on mutual exclusion (which was initially introduced to access shared physical resources), passing through consensus and concurrent objects (which are immaterial data), until today distributed ledgers. A discussion is also presented, which addresses the limits that this approach encounters, related to fault-tolerance, performance, and inherently concurrent problems.

Phani Chitti

Distributed ledgers are a new type of database technology that allows open access to data stored across distributed, decentralised, publicly maintained infrastructures. Current implementations of the such ledgers expect competition between participants, are often energy hungry, poor in maintaining the natural structure of data and suffer from scalability constraints. The aim of my research work is to develop a distributed ledger-based middleware for data modelling and collection on household energy generation and use, while addressing scalability and energy inefficiency concerns of the ledger for this particular application domain. The energy data collected and made available through this middleware will be used for digital energy service delivery (e.g., automated peer to peer energy trading, topological estimations, etc.). The middleware also provides a platform for a consumer focused digital energy service delivery, as well as service model evaluation. The model evaluation will enable the prospective service users to evaluate the suitability of the given service for their needs before making a decision of service subscription.

Authors unavailable

There are many consensus algorithms that exist in parallel computing that involve multiple computing units like virtual machines which make use of available resources and arrive at a single agreeable state for the combined system. This is done on the basis of voting which itself branches into several arrangements like voting, functions of central tendencies, weighted functions of central tendencies etc. Some applications that consensus algorithms try to cover are: deciding on transaction operations (read, write, commit); deciding on node leaders of a system; maintaining replicas in the state of a machine (also called a state machine) and creating consistency between them. Some common algorithms of this type are Proof of Work algorithm (PoW), the practical Byzantine fault tolerance algorithm (PBFT), the proof-of-stake algorithm (PoS) and the delegated proof-of-stake algorithm (DPoS), Paxos algorithm and the Raft consensus algorithm.

Robert Šajina

Blockchain je u proteklih nekoliko godina dobio široku pozornost zbog njegove primjene na kripto valutama i tehnologijama distribuiranih knjiga (Distributed Ledger), kao što su Bitcoin i Ethereum. Složena i decentralizirana priroda blockchain tehnologija otežava razumijevanje ponašanja pojedinih komponenata i njihovog učinka na blockchain sustav. Dolaskom novih konsenzus algoritama, kao što je Proof of Authority (PoA), razumijevanje ovog složenog sustava postaje izazovan zadatak. U ovom radu predlažemo PoASim, podesiv, diskretni simulacijski alat za simulaciju dvaju glavnih PoA algoritama, nazvanih Clique i Aura. PoASim može pomoći korisnicima da bolje razumiju temeljne slojeve Ethereum blockchain-a, kao i razumijevanje razlika konsenzusa i nedostataka između dva konsenzus algoritma. PoASim tako može poslužiti kao koristan alat za bolje razumijevanje ponašanja svakog konsenzusa pokretanjem simulacija s različitim parametrima i analizom ponašanja sustava.

Pamela Hui Ting Chua, Yingjiu Li, Wei He

The EPCglobal Network is a computer network used to share product data between trading partners. The EPC Information Services (EPCIS) is an event record repository that allows disparate applications to access and query for data both within and across enterprises. Ultimately, this data sharing is aimed at enabling participants in the EPCglobal Network to gain a shared view of the disposition of EPC-bearing objects within a relevant business context [1].Despite the potential benefits, enterprises are reluctant to integrate into the EPCglobal Network due to the financial and manpower resources required to set up, operate and maintain the EPCIS and to adopt the standards. Issues like security, computation and storage overheads would also have to be managed. To solve the problem, this paper advocates a blockchain solution using Hyperledger Fabric to serve as a shared EPCIS across trading partners. The blockchain can be queried directly to facilitate information sharing subjected to access control rules. It also adheres to the EPCglobal Network standards. This approach provides several important benefits including eliminating the need for enterprises to maintain their own EPCIS while still being able to participate and benefit from the network. As the blockchain can be queried directly, the provision of EPC Discovery Services (EPCDS) may also be unnecessary. To explore this idea, we constructed a prototype using Hyperledger Composer and Hyperledger Fabric while adhering to the data elements, structures and formats as stated in the standards to ensure interoperability with existing architecture both upstream and downstream.

Ross Guttromson, Stephen Verzi, Lon Andrew Dawson, Drew Levin · 10 authors

This project explored coupling modeling and analysis methods from multiple domains to address complex hybrid (cyber and physical) attacks on mission critical infrastructure. Robust methods to integrate these complex systems are necessary to enable large trade-space exploration including dynamic and evolving cyber threats and mitigations. Reinforcement learning employing deep neural networks, as in the AlphaGo Zero solution, was used to identify "best" (or approximately optimal) resilience strategies for operation of a cyber/physical grid model. A prototype platform was developed and the machine learning (ML) algorithm was made to play itself in a game of 'Hurt the Grid'. This proof of concept shows that machine learning optimization can help us understand and control complex, multi-dimensional grid space. A simple, yet high-fidelity model proves that the data have spatial correlation which is necessary for any optimization or control. Our prototype analysis showed that the reinforcement learning successfully improved adversary and defender knowledge to manipulate the grid. When expanded to more representative models, this exact type of machine learning will inform grid operations and defense - supporting mitigation development to defend the grid from complex cyber attacks! This same research can be expanded to similar complex domains.

Cristian PĂUNA

When dot.com has become a quaint idea, when electronic shops have lost the mass attention, while classical and margin trading has become obsolete, something new is coming: cryptocurrencies. Hundreds of virtual coins have been invented for a single reason: the profit. The high price volatility of these new markets and the fact that the virtual coins price is not regulated by a central bank or a single exchange, gives us opportunities for arbitrage trading. The existence of important price differences makes possible the profit when an automated system buy cheaper and sell more expensive in the same time. This paper will present the general principles underpinning the implementation of arbitrage trading software for virtual coins market. The very large number of cryptocurrencies and exchanges fundamentally change the server architecture of the trading software. The distributed price data in hundreds of sources and the technical differences of each of these data providers make all the things difficult to be implemented in a single application. The low-latency order calculation needed for the fast delivery before a significant price change, in the presence of thousands of price quotes coming from hundreds of distributed servers makes everything special.

Jong-Ki Lee

4차산업혁명시대에 블록체인기술이 각광 받고 있다

Riccardo Sibani

The recent emergence of a distributed technology named blockchain, clearly created a new point of view in the data storing and data distribution fields. If on one hand blockchain is mainly known for Bitcoin (an auto-regulated decentralized digital currency), on the other hand it has the potential to set up an auto regulated economy.In this thesis, the blockchain technology will be analyzed and described starting from P2P architecture and its origin in 2009 Satoshi Nakamoto’s whitepaper, and leading to the most up to date blockchains. The advantages and disadvantages of such architecture will be pointed out keeping in mind the security, speed and cost of such infrastructure.While Real Estate companies have often anticipated the technological innovations, land registries, instead, derive and keep a working manner which is extremely old and out of date: made of unclear procedures and wet signatures. The market needs and legislation will be researched mainly referring to other works and integrated with a technical point of view with particular focus on the decentralization of such systems.After analyzing the flow, problems and flaws of the current system, a new proposal will be researched, in particular trying to minimize the dead time in between the different steps of the mortgage, increase transparency, as well as reducing dependence on the central authorities, leading to more convenient interactions among the properties’ stakeholders. An attractive low capitalization decentralized financial product will also be proposed and implemented able to lower the interest rate and create a profitable investment with low risk, low interest and durable in time.Secure and ad-hoc algorithms will be presented and, in a later section, analyzed in combination with different blockchain technologies. Scalability and performance will also be evaluated, taking into account all the current technology limitations and the near future opportunities.

Merla Kubli

Renewable energies, especially photovoltaic (PV), have started a trend towards a decentralization of energy systems. With decreasing levelized costs of energy of new renewable energies, self-consumption concepts become increasingly attractive and have even reached grid parity in some countries already. So called "prosumers" (households that are producers and consumers at the same time) start to replace grid consumers, conducting self-consumption with their locally produced electricity by the PV plants. Since complete autarky cannot be reached with a PV plant for a household, prosumers still consume electricity from the main grid. This on-going diffusion of self-consumption concepts is significantly influenced by the interplay of network externalities within the system, such as learning from peers, altering the perceived utility by households of the investment into decentral generation. The increasing penetration of PV significantly contributes to the creation of a more sustainable power supply in Europe and is considered and supported in many nations by governmental energy strategies. Nevertheless, such decentralization dynamics also lead to multiple challenges in the energy system. New investors enter the energy market, utility companies are forced to adjust their business models and grid operators face technical as well as financial challenges. The presented paper focusses on the financial challenges of grid operators caused by decentralization trends of the electricity system.

Mateusz Guzek, Xavier Besseron, Sébastien Varrette, Grégoire Danoy · 5 authors

The growing parallelism and heterogeneity of modern computing infrastructures such as High Performance Computing (HPC) platforms raises new challenges to their programmers and users. Additional requirements have emerged nowadays, such as minimizing the consumed energy, reducing the utilized system resources, or providing built-in reliability mechanisms. Therefore High Performance Computing (HPC) applications require adaptation mechanisms and then must avoid traditional monolithic centralized approaches in favor of novel autonomous, flexible and decentralized decision systems. In this context, we describe here a dynamic and flexible adaptation scheme based on a Multi-Agent System (MAS) to handle parallel or distributed executions in an HPC environment. More precisely, we model and extend the existing HPC middleware Kaapi to offer the power of the ParaMoise multi-agent organizational framework. Our proposed solution, named ParaMASK, relies on the similarities between ParaMoise workflow-based functional specifications and the Direct Acyclic Graph (DAG) representation of the distributed execution within Kaapi. As a result, ParaMASK permits to analyze and reorganize the scheduling of tasks that compose a program in an autonomous and decentralized way, while additionally handling dynamic adaptations (using task migration to fulfill energy consumption goals for example). The proposed solution was implemented on top of the existing Kaapi middleware and includes an optimized algorithm for the agent coordination. ParaMASK has been validated with a series of experiments on a real computational grid. Experimental results show a good scalability and an exceptional low overhead induced by the approach: less than 1.5% execution time increase with periodic coordinations every 15 seconds on 2662 cores.

Enas Al Kawasmi, Edin Arnautović, Davor Svetinović

ABSTRACT This paper presents a system‐of‐systems architecture model for a Decentralized Carbon Emissions Trading Infrastructure (D‐CETI) with focus on privacy and system security goals. The structure and behavior are implemented as a solution to the problem of trading carbon emissions anonymously among the trading agents. Privacy and security of the trading agents and their carbon credits are the main requirements behind the architecture of D‐CETI. The decentralized structure of multiple systems and distributed behavior are the two main features of D‐CETI that distinguish it from the traditional carbon trading schemes and protocols. D‐CETI is based on Bitcoin, a peer‐to‐peer digital currency with no central authority, and Open Transactions, a system that simplifies the use of cryptography in financial transactions. The architecture of D‐CETI is evaluated and compared with the architecture of five other carbon emissions trading platforms.

Paul L. Snyder, Giuseppe Valetto

Describing, understanding, and modeling the emergent behavior of self-organizing software systems remains an open challenge. Such systems can solve problems in computing domains where traditional, centralized models are impractical or problematic, including ubiquitous and pervasive computing, peer-to-peer networks, large-scale grids, and Ultra-Large-Scale Systems. Self-organizing approaches have demonstrated great promise in building adaptive behavior into decentralized systems, enabling cooperative, autonomous self-management and the exploitation of the heterogeneity of system components. My investigation of self-organizing software systems has revolved around Myconet, an unstructured overlay protocol for peer-to-peer networks. Myconet takes inspiration from fungal growth patterns in order to build an efficient self-optimizing superpeer topology that can also rapidly self-heal in response to damage orattacks. Myconet has proven to be flexible, and has been used as a platform for the development of other self-organizing applications in large-scale distributed systems, including load-balancing in distributed service networks (Mycoload), and detection and mitigation of attacks against the overlay (Hormone-Inspired Topology Adaptation Protection [HITAP] and Self-Organized Degree Adaptation Protection [SODAP]). Each extension has given additional insights into the self-organizing dynamics of such systems, but has also shown the limitations of ad hoc approaches to the design and analysis of new applications. These experiences have led me to investigate formal tools and models that may provide the designer of a self-organizing system with early and accurate insight through augmented analytical power. This research selects a small set of synergistic modeling techniques, and builds an integrated approach to modeling for the design and validation of self-organizing software systems. These tools are used to model the core Myconet platform and its currently developed extensions, particularly focusing on the SODAP layer which provides self-protection features to a superpeer-based P2P overlay network. Once established, this modeling approach can be applied to the principled design of further Myconet extensions, as well as other self-organizing systems, thus advancing the understanding of how to model and engineer self-organization in software systems.

Amar Bahadur Patel

Grid computing is the computing paradigm that is concerned with coordinated resource sharing and problem solving in dynamic, autonomous multi-institutional virtual organizations. Data exchange and service allocation between virtual organizations are challenging problems in the field of Grid computing, due to the decentralization of Grid systems. The resource management in a Grid system ensures efficiency and usability. The required efficiency and usability of Grid systems can be achieved by building a decentralized multi-virtual Grid system. In this thesis we present a decentralized multi-virtual resource management framework in which the system is divided into virtual organizations, each controlled by a broker. An overlay network of brokers is responsible for global resource management and managing the allocation of services. We address two main issues for both local and global resource management: 1) decentralized allocation of tasks to suitable nodes to achieve both local and global load balancing; and 2) handling of both regular and broker failures. Experimental results verify that the system achieves dependable performance with various loads of services and broker failures.

Rajiv Ranjan, Rajkumar Buyya, Manish Parashar

Welcome to the special issue of Concurrency and Computation: Practice and Experience (CCPE) journal. This special issue compiles a number of excellent technical contributions that significantly advance the state-of-the-art in autonomic cloud computing. Cloud computing 1, 2 is an emerging utility computing model that allows users to dynamically access, select, and configure a large pool of IT resources (virtual machine templates, storage, and networking elements) and deliver them as ‘computing utilities’ to consumers in a pay-as-you-go manner. Several vendors have emerged in this space including IBM, VMware, Microsoft, Manjrasoft, and Yahoo. This model of computing is quite attractive, especially for small and medium sized enterprises, as it allows them to focus on consuming or offering services on top of cloud infrastructure. At high-level, cloud computing might not seem radically different from the existing paradigms: World Wide Web, grid computing, and cluster computing. However, key differentiators of cloud computing are its technical characteristics such as on-demand resource pooling or rapid elasticity, self-service, almost infinite scalability, end-to-end virtualization support, and robust support of resource usage metering and billing. Additionally, nontechnical differentiators include services that are offered under pay-as-you-go-model, guaranteed Service Level Agreement (SLA), faster time to deployments, lower upfront costs, little or no maintenance overhead, and environment friendliness. Unpredictability is a fact in a distributed computing environment, and the Cloud is no exception. Performance unpredictability 3 in the Cloud is in fact a major issue for many users and it is coined as one of the major obstacles for cloud computing. For instance, researchers (biologists, physicists, finance analysts, etc.) expect guaranteed performance for their experiments, independent of the current workload and state 4 of IT resources of the Cloud, because this is key to repeatability of results. Other examples are small and medium sized enterprises (gaming company, web application providers) that want strict assurance on SLA; for example, an end-user request for a web page or multimedia content has to be served within the agreed time-limit. Hence, it is highly important for Cloud vendors that they have the ability to offer guaranteed SLAs based on performance metrics — such as response time and throughput. Interestingly, vendors seem to base their SLAs on availability of their offering, while completely ignoring response time and throughput. Hence, it is clear that dealing with performance unpredictability is critical to exploiting the full potential of clouds. In this special issue, we have tried to compile some high quality papers that exhaustively deal with some of the aforementioned issues. Next, we briefly describe the technical contributions, which were selected for publication in this special issue. All of the selected papers underwent a rigorous peer-review process. The end-to-end QoS negotiation for SLA establishment for composite services involves compound multiparty negotiations in which the composite service provider concurrently negotiates with multiple candidates for each atomic service, selecting the one that best satisfies the atomic service QoS preferences while ensuring that the end-to-end QoS requirements are also fulfilled. It is necessary to derive the atomic utility boundaries from the global utility boundary to be able to negotiate with potential candidates. Additionally, there has to be a mechanism for updating these boundaries in subsequent negotiation rounds based upon the individual negotiation outcomes. To counter these complexities, in paper 5 titled ‘Establishing Composite SLAs through Concurrent QoS Negotiation with Surplus Redistribution’, Richter et al. propose an algorithm for the decomposition of global utility boundary into atomic service utility boundaries, and the surplus redistribution from successful negotiation outcomes among the remaining negotiations. The proposed mechanism is a practical approach to efficiently coordinate concurrent service negotiations within complex workflows, enabling the iterative and interactive adjustment of the negotiation boundaries for each atomic service in a composition based on the performance of other atomic negotiations. They demonstrate the feasibility of our approach by evaluating it with some popular negotiation strategies using the Specialised Property Search Scenario. Many scientific workflows are data intensive where large volumes of intermediate data are generated during their execution. Some valuable intermediate data need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity determined manually. As doing science in the Cloud has become popular nowadays, more intermediate data can be stored in scientific cloud workflows based on a pay-for-use model. In the paper in 6 titled ‘A data dependency based strategy for intermediate data storage in scientific cloud workflow systems’, Yuan et al. build an intermediate data dependency graph (IDG) from the data provenance in scientific workflows. With the IDG, deleted intermediate data can be regenerated, and as such they develop a novel intermediate data storage strategy that can reduce the cost of scientific cloud workflow systems by automatically storing appropriate intermediate data sets with one Cloud service provider. The strategy has significant research merits, that is, it achieves a cost-effective trade-off of computation cost and storage cost and is not strongly impacted by the forecasting inaccuracy of data sets’ usages. Meanwhile, the strategy also takes the users’ tolerance of data accessing delay into consideration. Authors utilize Amazon's cost model and apply the strategy to general random and specific astrophysics pulsar searching scientific workflows for evaluation. The results show that our strategy can reduce the overall cost of scientific cloud workflow execution significantly. Recall that, one of the biggest premises of cloud computing is the flexibility of delivering IT resources and virtual appliances as an utility such as phone, electricity, gas, and water services. It enables users to have access to computing infrastructure, platform, and software as services over the Internet. To be competitive, however, Cloud providers need to be able to adapt to the dynamic loads from users, not only optimizing the local usage and costs but also engaging into agreements with other clouds to complement local capacity. The infrastructure in which competing clouds are able to cooperate to maximize their benefits is called a Federated Cloud. Just as clouds enable users to cope with unexpected demand loads, a Federated Cloud will enable individual clouds to cope with unforeseen variations of demand. The definition of the mechanism to ensure mutual benefits for the individual clouds composing the federation, however, is one of its main challenges. Gomes et al. in their paper 7 ‘Pure exchange markets for resource sharing in federated clouds’ propose and investigate the application of market-oriented mechanisms based on the General Equilibrium Theory of Microeconomics to coordinate the sharing of resources between the clouds in a Federated Cloud. Several research institutions and universities own computational capacity that is not effectively utilized, thereby providing an opportunity for such institutions to use such capacity to offer Cloud services (to both internal and external users). However, the unreliability and unpredictability of these resources mean that their use in the context of an SLA is high risk, leading to a reduction in reputation and economic penalties in case of SLA violation. To overcome these challenges, in the paper 8 titled ‘Towards autonomic management for Cloud services based upon volunteered resources’, Caton and Rana propose a methodology that addresses the issues of unreliability and unpredictability such that Cloud software services could be hosted upon volunteered resources. To enable the harnessing of these resources, they rely on autonomic fault management techniques that allow such systems to independently adapt to the resources they use based upon their perception of individual resource reliability. Using the proposed approach they were able to scale out the backend infrastructure of the Cloud service elastically (minimum 30 s per worker), opportunistically, and autonomically. To summarize, the authors address two key questions in their paper: Can a campus volunteer infrastructure be used in Cloud provisioning? and What measures are necessary to ensure reliability at the resource level? To improve the hosting and delivery of applications through cloud-based IT resources, Champrasert et al. in the paper 9 titled ‘Exploring self-optimization and self-stabilization properties in bio-inspired autonomic cloud computing’, describe architecture to build self-optimizable and self-stabilizable applications. The design of the proposed architecture, SymbioticSphere, is inspired by key biological principles such as decentralization, evolution, and symbiosis. In SymbioticSphere, each cloud application consists of application services and middleware platforms. Each service and platform is designed as a biological entity, and implements biological behaviors such as energy exchange, migration, reproduction, and death. Each service/platform possesses behavior policies, as genes, each of which defines when and how to invoke a particular behavior. SymbioticSphere allows services and platforms to autonomously adapt to dynamic network conditions by optimizing their behavior policies with a multi-objective genetic algorithm. Moreover, SymbioticSphere allows services and platforms to autonomously seek stable adaptation decisions as equilibria (or symbiosis) between them with a game theoretic algorithm. This symbiosis augments evolutionary optimization to expedite the adaptation of agents and platforms. It also contributes to stable performance that contains a very limited amount of fluctuations. Simulation results demonstrate that agents and platforms successfully attain self-optimization and self-stabilization properties in their adaptation processes. We hope that the readers will find the articles of this special issue to be informative and useful.

Hesham Ali, Mofreh Salem, A.A. Hamza

Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.

Laura Kang, David C. Parkes

Computational grids enable the sharing, aggregation, and selection of (geographically distributed) computational resources and can be used for solving large scale and data intensive computing applications. Computational grids are an appealing target application for market-based resource allocation especially given the attention in recent years to “virtual organizations ” and policy requirements. In this paper, we present a framework for truthful, decentralized, dynamic auctions in computational grids. Rather than a fullyspecified auction, we propose an open, extensible framework that is sufficient to promote simple, truthful bidding by endusers while supporting distributed and autonomous control by resource owners. Our auction framework incorporates resource prediction in enabling an expressive language for end-users, and highlights the role of infrastructure in enforcing rules that balance the goal of simplicity for end users with autonomy for resource owners. The technical analysis leverages simplifying assumptions of “uniform failure” and “threshold-reliability” beliefs.

J.M. Marques, Leandro Navarro, Τhanasis Daradoumis

Asynchronous collaborative applications and systems have to deal with complexities associated with interaction nature, idiosyncrasy of groups and technical and administrative issues. Inclusion of requirements derived from them is costly (in time, resources and economically). Existing solutions addresses asynchronous collaboration via simplification of requirements and by using centralized models. In this paper we present LaCOLLA, a fully decentralized infrastructure for building collaborative applications that provides general purpose collaborative functionalities. The provision of those functionalities will avoid applications deal with most of complexities derived from groups and its members, what will help inclusion of collaborative aspects. The implementation of LaCOLLA follows the peer-to-peer paradigm and pays special attention to autonomy of its members and to self-organization of the components of the infrastructure. Another key aspect is that resources (e.g. storage) and services (e.g. authorization) are provided by its members (avoiding dependency from agents not belonging to group).