Considering Human Aspects on Strategies for Designing and Managing Distributed Human Computation

A human computation system can be viewed as a distributed system in which the processors are humans, called workers. Such systems harness the cognitive power of a group of workers connected to the Internet to execute relatively simple tasks, whose solutions, once grouped, solve a problem that systems equipped with only machines could not solve satisfactorily. Examples of such systems are Amazon Mechanical Turk and the Zooniverse platform. A human computation application comprises a group of tasks, each of them can be performed by one worker. Tasks might have dependencies among each other. In this study, we propose a theoretical framework to analyze such type of application from a distributed systems point of view. Our framework is established on three dimensions that represent different perspectives in which human computation applications can be approached: quality-of-service requirements, design and management strategies, and human aspects. By using this framework, we review human computation in the perspective of programmers seeking to improve the design of human computation applications and managers seeking to increase the effectiveness of human computation infrastructures in running such applications. In doing so, besides integrating and organizing what has been done in this direction, we also put into perspective the fact that the human aspects of the workers in such systems introduce new challenges in terms of, for example, task assignment, dependency management, and fault prevention and tolerance. We discuss how they are related to distributed systems and other areas of knowledge.Comment: 3 figures, 1 tabl

Stochastic scheduling and workload allocation : QoS support and profitable brokering in computing grids

Abstract: The Grid can be seen as a collection of services each of which performs some functionality. Users of the Grid seek to use combinations of these services to perform the overall task they need to achieve. In general this can be seen as aset of services with a workflow document describing how these services should be combined. The user may also have certain constraints on the workflow operations, such as execution time or cost ----t~ th~ user, specified in the form of a Quality of Service (QoS) document. The users . submit their workflow to a brokering service along with the QoS document. The brokering service's task is to map any given workflow to a subset of the Grid services taking the QoS and state of the Grid into account -- service availability and performance. We propose an approach for generating constraint equations describing the workflow, the QoS requirements and the state of the Grid. This set of equations may be solved using Mixed-Integer Linear Programming (MILP), which is the traditional method. We further develop a novel 2-stage stochastic MILP which is capable of dealing with the volatile nature of the Grid and adapting the selection of the services during the lifetime of the workflow. We present experimental results comparing our approaches, showing that the . 2-stage stochastic programming approach performs consistently better than other traditional approaches. Next we addresses workload allocation techniques for Grid workflows in a multi-cluster Grid We model individual clusters as MIMIk. queues and obtain a numerical solutio~ for missed deadlines (failures) of tasks of Grid workflows. We also present an efficient algorithm for obtaining workload allocations of clusters. Next we model individual cluster resources as G/G/l queues and solve an optimisation problem that minimises QoS requirement violation, provides QoS guarantee and outperforms reservation based scheduling algorithms. Both approaches are evaluated through an experimental simulation and the results confirm that the proposed workload allocation strategies combined with traditional scheduling algorithms performs considerably better in terms of satisfying QoS requirements of Grid workflows than scheduling algorithms that don't employ such workload allocation techniques. Next we develop a novel method for Grid brokers that aims at maximising profit whilst satisfying end-user needs with a sufficient guarantee in a volatile utility Grid. We develop a develop a 2-stage stochastic MILP which is capable of dealing with the volatile nature . of the Grid and obtaining cost bounds that ensure that end-user cost is minimised or satisfied and broker's profit is maximised with sufficient guarantee. These bounds help brokers know beforehand whether the budget limits of end-users can be satisfied and. if not then???????? obtain appropriate future leases from service providers. Experimental results confirm the efficacy of our approach.Imperial Users onl

Perfomance Analysis and Resource Optimisation of Critical Systems Modelled by Petri Nets

Un sistema crítico debe cumplir con su misión a pesar de la presencia de problemas de seguridad. Este tipo de sistemas se suele desplegar en entornos heterogéneos, donde pueden ser objeto de intentos de intrusión, robo de información confidencial u otro tipo de ataques. Los sistemas, en general, tienen que ser rediseñados después de que ocurra un incidente de seguridad, lo que puede conducir a consecuencias graves, como el enorme costo de reimplementar o reprogramar todo el sistema, así como las posibles pérdidas económicas. Así, la seguridad ha de ser concebida como una parte integral del desarrollo de sistemas y como una necesidad singular de lo que el sistema debe realizar (es decir, un requisito no funcional del sistema). Así pues, al diseñar sistemas críticos es fundamental estudiar los ataques que se pueden producir y planificar cómo reaccionar frente a ellos, con el fin de mantener el cumplimiento de requerimientos funcionales y no funcionales del sistema. A pesar de que los problemas de seguridad se consideren, también es necesario tener en cuenta los costes incurridos para garantizar un determinado nivel de seguridad en sistemas críticos. De hecho, los costes de seguridad puede ser un factor muy relevante ya que puede abarcar diferentes dimensiones, como el presupuesto, el rendimiento y la fiabilidad. Muchos de estos sistemas críticos que incorporan técnicas de tolerancia a fallos (sistemas FT) para hacer frente a las cuestiones de seguridad son sistemas complejos, que utilizan recursos que pueden estar comprometidos (es decir, pueden fallar) por la activación de los fallos y/o errores provocados por posibles ataques. Estos sistemas pueden ser modelados como sistemas de eventos discretos donde los recursos son compartidos, también llamados sistemas de asignación de recursos. Esta tesis se centra en los sistemas FT con recursos compartidos modelados mediante redes de Petri (Petri nets, PN). Estos sistemas son generalmente tan grandes que el cálculo exacto de su rendimiento se convierte en una tarea de cálculo muy compleja, debido al problema de la explosión del espacio de estados. Como resultado de ello, una tarea que requiere una exploración exhaustiva en el espacio de estados es incomputable (en un plazo prudencial) para sistemas grandes. Las principales aportaciones de esta tesis son tres. Primero, se ofrecen diferentes modelos, usando el Lenguaje Unificado de Modelado (Unified Modelling Language, UML) y las redes de Petri, que ayudan a incorporar las cuestiones de seguridad y tolerancia a fallos en primer plano durante la fase de diseño de los sistemas, permitiendo así, por ejemplo, el análisis del compromiso entre seguridad y rendimiento. En segundo lugar, se proporcionan varios algoritmos para calcular el rendimiento (también bajo condiciones de fallo) mediante el cálculo de cotas de rendimiento superiores, evitando así el problema de la explosión del espacio de estados. Por último, se proporcionan algoritmos para calcular cómo compensar la degradación de rendimiento que se produce ante una situación inesperada en un sistema con tolerancia a fallos

Dynamic fault tolerant grid workflow in the water threat management project

Achieving fault tolerance is an inevitable problem in distributed systems, with it becoming more challenging in decentralized, heterogeneous, and dynamic-environment systems such as a Grid. When deploying applications requires time-criticality, how to allocate resources for jobs in a fault-tolerant manner is an important issue for the delivery of the services. The Water Threat Management project is a research to find solutions for the contamination incidents problems in urban water distribution systems, and it involves the development of the cyberinfrastructure in a Grid environment. To handle such urgent events properly, the deployment of the system demands real-time processing without the failure. Our approach of integrating a fault-tolerant framework into a Water Threat Management system provides fault tolerance at the queuing stage rather than the job-execution stage by scheduling jobs in fault-tolerant ways. This includes the development of the batch queuing system in the Cyberaide Shell project. In addition, we present a dynamic workflow in the Water Threat Management system that can reduce the queue wait time in the changing environment

A manifesto for future generation cloud computing: research directions for the next decade

The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing