<em>Blockchain</em> technology has the capacity to make digital goods immutable, transparent, externally provable, decentralized, and distributed. Besides the initial experiment or data acquisition, all remaining parts of the research cycle could take place within a <em>blockchain system</em>. Attribution, data, data postprocessing, publication, research evaluation, incentivisation, and research fund distribution would thereby become comprehensible, open (at will) and provable to the external world. Currently, scientists must be trusted to provide a true and useful representation of their research results in their final publication; <em>blockchain</em> would make much larger parts of the research cycle open to scientific self-correction. This bears the potential to be a technical solution to the current reproducibility crisis in science, and could âreduce waste and make more research results trueâ.
Decentralized enactment of workflows is generally advocated for data intensive scientific applications. This approach offers a number of advantages including avoiding a single (centralized) point of failure, and associated (centralized) performance bottlenecks. However, such services are often assumed to be openly available with little or no security. This is increasingly not the case. Instead organizations and the services they offer require autonomous ways of defining and enforcing their own access control policies supporting fine-grained authorization. Tackling such scenarios raises many issues regarding workflow definition, enactment and potential re-enactment. This research explores the issues related to security-oriented decentralized workflow definition and enactment. The solution is respectful of the need for autonomy of service providers and allows each participating service to define their own access control policies. We also show how different security delivery models can be supported leveraging the pulling and pushing of security credentials.
Enas Al Kawasmi, Edin ArnautoviÄ, Davor SvetinoviÄ
ABSTRACT This paper presents a systemâofâsystems architecture model for a Decentralized Carbon Emissions Trading Infrastructure (DâCETI) 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 DâCETI. The decentralized structure of multiple systems and distributed behavior are the two main features of DâCETI that distinguish it from the traditional carbon trading schemes and protocols. DâCETI is based on Bitcoin, a peerâtoâpeer digital currency with no central authority, and Open Transactions, a system that simplifies the use of cryptography in financial transactions. The architecture of DâCETI is evaluated and compared with the architecture of five other carbon emissions trading platforms.
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 âcomputing utilitiesâ 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 â 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 âEstablishing Composite SLAs through Concurrent QoS Negotiation with Surplus Redistributionâ, 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 âA data dependency based strategy for intermediate data storage in scientific cloud workflow systemsâ, 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 setsâ usages. Meanwhile, the strategy also takes the usersâ 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 âPure exchange markets for resource sharing in federated cloudsâ 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 âTowards autonomic management for Cloud services based upon volunteered resourcesâ, 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 âExploring self-optimization and self-stabilization properties in bio-inspired autonomic cloud computingâ, 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.
Abstract Distributed applications are difficult to program reliably and securely. Dependently typed functional languages promise to prevent broad classes of errors and vulnerabilities, and to enable program verification to proceed side-by-side with development. However, as recursion, effects, and rich libraries are added, using types to reason about programs, specifications, and proofs becomes challenging. We present F*, a full-fledged design and implementation of a new dependently typed language for secure distributed programming. Our language provides arbitrary recursion while maintaining a logically consistent core; it enables modular reasoning about state and other effects using affine types; and it supports proofs of refinement properties using a mixture of cryptographic evidence and logical proof terms. The key mechanism is a new kind system that tracks several sub-languages within F* and controls their interaction. F* subsumes two previous languages, F7 and Fine. We prove type soundness (with proofs mechanized in Coq) and logical consistency for F*. We have implemented a compiler that translates F* to .NET bytecode, based on a prototype for Fine. F* provides access to libraries for concurrency, networking, cryptography, and interoperability with C#, F#, and the other .NET languages. The compiler produces verifiable binaries with 60% code size overhead for proofs and types, as much as a 45x improvement over the Fine compiler, while still enabling efficient bytecode verification. We have programmed and verified nearly 50,000 lines of F* including new schemes for multi-party sessions; a zero-knowledge privacy-preserving payment protocol; a provenance-aware curated database; a suite of web-browser extensions verified for authorization properties; a cloud-hosted multi-tier web application with a verified reference monitor; the core F* typechecker itself; and programs translated to F* from other languages such as F7 and JavaScript.
Chen Su, Tiejian Luo, Wei Liu, Jinliang Song · 5 authors
In an e-Science environment, large-scale distributed resources in autonomous domains are aggregated by unified collaborative platforms to support scientific research across organizational boundaries. In order to enhance the scalability of access management, an integrated approach for decentralizing the task from resource owners to administrators on the platform is needed. We propose an extensible access management framework to meet this requirement by supporting an administrative delegation policy. This feature allows administrators on the platform to make new policies based on the original policies made by resources owners. An access protocol that merges SAML and XACML is also included in the framework. It defines how distributed parties operate with each other to make decentralized authorization decisions.
In the past, the problem of semantic interoperability in information systems was mostly solved by means of centralization, both at a system and at a logical level. This approach has been successful to a certain extent, but offers limited scalability and flexibility. Peer-to-Peer systems as a new brand of system architectures indicate that the principles of decentralization and self-organization might offer new solutions to many problems that scale well to very large numbers of users, or to systems where central authorities do not prevail. Therefore, we suggest a new way of building global agreements, i.e., semantic interoperability, based on decentralized, self-organizing interactions only. In the first part of this thesis, we discuss traditional data integration techniques relying on global schemas, perfect schema mappings and contained query rewritings. We elaborate on the current ecology of the World Wide Web, where autonomous information sources come and go in dynamic and unpredictable ways. In the current environment, data, schemas and schema mappings can all be generated without human intervention and get encoded in syntactic structures with limited expressivity. We argue that traditional top-down integration techniques are inapplicable to that new context and propose a new integration architecture based on decentralized mappings and dynamic self-organization. In the second part of this thesis, we propose a set of principles to foster semantic interoperability in very large scale information systems. We start by introducing new metrics for the schema mappings, based on both syntactic losses (completeness) and semantic mismatch (soundness) to selectively reformulate queries in a decentralized network of heterogeneous parties. We detail analytical methods to evaluate our metrics, and show how to take advantage of those methods to gradually alleviate mapping inconsistencies across the network. We describe a totally decentralized message passing scheme using belief propagation on transitive closures of schema mapping operations to efficiently evaluate the degree of semantic mismatch between pairs of acquainted information systems. Finally, we propose a graph-theoretic analysis of the network of mappings to quantify the quality of the global agreement that can be achieved in that way. The third and last part of this thesis is devoted to the presentation of two systems illustrating the practical applicability of our ideas. The first system we introduce, GridVine, is a Semantic Overlay Network supporting decentralized data integration techniques through pairwise schema mappings and monotonic schema inheritance. GridVine follows the principle of data independence by separating a logical layer, the semantic overlay for managing and mapping data and schemas, from a physical layer consisting of a self-organizing Peer-to-Peer overlay network for efficient routing of messages. The second system, called PicShark, takes advantage of semi-structured metadata to meaningfully share pictures in collaborative settings. PicShark builds on our principles to dynamically create both annotations and mappings, and to gradually minimize information entropy â in terms of missing metadata and schematic heterogeneity â in a self-organizing and decentralized context. Throughout this thesis, we advocate a holistic view on semantics in large-scale information systems: we model semantics as bottom-up and dynamic agreements among heterogeneous parties. We consider both the representation of semantics and the discovery of the interpretation of symbols as the result of a self-organizing process performed by distributed agents whose utility functions depend on the proper interpretation of the symbols. Our view sharply contrasts with previous top-down contributions analyzing data sources in isolation or focusing on global vocabularies and rigid sets of interpretations curated off-line. In a world where digital information is abundant but human attention remains scarce, we believe that autonomous, best-effort processes such as the ones proposed throughout this thesis will play an ever increasing role in complementing traditional top-down integration approaches to handle massive amounts of digitalized and heterogeneous information assets.
Arshad Ali, A. Anjum, Tahir Azim, M. Thomas · 9 authors
In this paper we describe JClarens; a Java based implementation of the Clarens remote data server. JClarens provides Web services for an interactive analysis environment to dynamically access and analyze the tremendous amount of data scattered across various locations. Additionally this research is aimed to develop a service oriented grid enabled portal (GEP) that provides interface and access to several grid services to give a homogeneous and optimized view of the distributed and heterogeneous environment. Other than showing platform independent behavior provided by Java, the use of XML-RPC based Web services enabled JClarens to be a language neutral server and demonstrated interoperability with its Python variant. Extreme care has been taken in the usage and manipulation of various Java libraries to cater the needs of high performance computing. The overall exercise has yielded in a prototype with strong emphasis on security and virtual organization management (VOM). This shall provide a common platform to support development of larger, more flexible framework with future aims to integrate it with a loosely coupled, decentralized, and autonomous framework for grid enabled analysis environment (GAE).
Kenneth M. Anderson, Aaron Andersen, Neet Wadhwani, Laura M. Bartolo
The Metis project is developing workflow technology designed for use in digital libraries by avoiding the assumptions made by traditional workflow systems. In particular, digital libraries have highly distributed sets of stake-holders who nevertheless must work together to perform shared activities. Hence, traditional assumptions that all members of a workflow belong to the same organization, work in the same fashion, or have access to similar computing platforms are invalid. The Metis approach makes use of event-based workflows to support the distributed nature of digital library workflow and employs techniques to make the resulting technology lightweight, flexible, and integrated with the Web. This paper describes the conceptual framework behind the Metis approach as well as a prototype which implements the framework. The prototype represents a proof-of-concept of the Metis framework and approach as we show how it can both model and execute a peer review workflow drawn from a real-world digital library. After describing related work, the paper concludes with a discussion of future research opportunities in the area of digital library workflow and outlines how Metis is being deployed to a small set of digital libraries for additional evaluation.
Michael Gillmann, Jeanine WeiĂenfels, German Shegalov, Wolfgang Wonner · 5 authors
The Mentor-lite prototype has been developed within the research project âArchitecture, Configuration, and Administration of Large Workflow Management Systemsâ funded by the German Science Foundation (DFG). It has evolved from its predecessor Mentor [1], but aims at a simpler architecture. The main goal of Mentor-lite has been to build a light-weight, extensible, and tailorable workflow management system (WFMS) with small footprint and easy-to-use administration capabilities. Our approach is to provide only kernel functionality inside the workflow engine, and consider system components like history management and worklist management as extensions on top of the kernel. The key point to retain the light-weight nature is that these extensions are implemented as workflows themselves. The workflow specifications are interpreted at runtime, which is a crucial prerequisite for flexible exception handling and dynamic modifications during runtime. The interpreter performs a stepwise execution of the workflow specification according to its formal semantics. For each step, the activities to be performed by the step are determined and started. Mentor-lite supports a protocol for distributed execution of workflows spread across multiple workflow engines. This support is crucial for workflows that span large, decentralized enterprises with largely autonomous organizational units or even cross multiple enterprises to form so-called âvirtual enterprisesâ. A communication manager is responsible for sending and receiving synchronization messages between the engines. In order to guarantee a consistent global state even in the presence of site or network failures, we have built reliable message queues using the CORBA Object Transaction Services. For administration, Mentor-lite provides a Java-based workbench for workflow design, workflow partitioning across multiple workflow servers, and a Java-based runtime monitoring tool.