Achieving Causal Consistency under Partial Replication for Geo-distributed Cloud Storage

Causal consistency has emerged as an attractive middle-ground to architecting cloud storage systems, as it allows for high availability and low latency, while supporting stronger-than-eventual-consistency semantics. However, causally-consistent cloud storage systems have seen limited deployment in practice. A key factor is these systems employ full replication of all the data in all the data centers (DCs), incurring high cost. A simple extension of current causal systems to support partial replication by clustering DCs into rings incurs availability and latency problems. We propose Karma, the first system to enable causal consistency for partitioned data stores while achieving the cost advantages of partial replication without the availability and latency problems of the simple extension. Our evaluation with 64 servers emulating 8 geo-distributed DCs shows that Karma (i) incurs much lower cost than a fully-replicated causal store (obviously due to the lower replication factor); and (ii) offers higher availability and better performance than the above partial-replication extension at similar costs

Contention in multicore hardware shared resources: Understanding of the state of the art

The real-time systems community has over the years devoted considerable attention to the impact on execution timing that arises from contention on access to hardware shared resources. The relevance of this problem has been accentuated with the arrival of multicore processors. From the state of the art on the subject, there appears to be considerable diversity in the understanding of the problem and in the “approach” to solve it. This sparseness makes it difficult for any reader to form a coherent picture of the problem and solution space. This paper draws a tentative taxonomy in which each known approach to the problem can be categorised based on its specific goals and assumptions.Postprint (published version

Building global and scalable systems with atomic multicast

The rise of worldwide Internet-scale services demands large distributed systems. Indeed, when handling several millions of users, it is common to operate thousands of servers spread across the globe. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this thesis, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. Internet-scale services rely on data partitioning and replication to provide scalable performance and high availability. Moreover, to reduce user-perceived response times and tolerate disasters (i.e., the failure of a whole datacenter), services are increasingly becoming geographically distributed. Data partitioning and replication, combined with local and geographical distribution, introduce daunting challenges, including the need to carefully order requests among replicas and partitions. One way to tackle this problem is to use group communication primitives that encapsulate order requirements. While replication is a common technique used to design such reliable distributed systems, to cope with the requirements of modern cloud based ``always-on'' applications, replication protocols must additionally allow for throughput scalability and dynamic reconfiguration, that is, on-demand replacement or provisioning of system resources. We propose a dynamic atomic multicast protocol which fulfills these requirements. It allows to dynamically add and remove resources to an online replicated state machine and to recover crashed processes. Major efforts have been spent in recent years to improve the performance, scalability and reliability of distributed systems. In order to hide the complexity of designing distributed applications, many proposals provide efficient high-level communication abstractions. Since the implementation of a production-ready system based on this abstraction is still a major task, we further propose to expose our protocol to developers in the form of distributed data structures. B-trees for example, are commonly used in different kinds of applications, including database indexes or file systems. Providing a distributed, fault-tolerant and scalable data structure would help developers to integrate their applications in a distribution transparent manner. This work describes how to build reliable and scalable distributed systems based on atomic multicast and demonstrates their capabilities by an implementation of a distributed ordered map that supports dynamic re-partitioning and fast recovery. To substantiate our claim, we ported an existing SQL database atop of our distributed lock-free data structure. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this thesis, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. Internet-scale services rely on data partitioning and replication to provide scalable performance and high availability. Moreover, to reduce user-perceived response times and tolerate disasters (i.e., the failure of a whole datacenter), services are increasingly becoming geographically distributed. Data partitioning and replication, combined with local and geographical distribution, introduce daunting challenges, including the need to carefully order requests among replicas and partitions. One way to tackle this problem is to use group communication primitives that encapsulate order requirements. While replication is a common technique used to design such reliable distributed systems, to cope with the requirements of modern cloud based ``always-on'' applications, replication protocols must additionally allow for throughput scalability and dynamic reconfiguration, that is, on-demand replacement or provisioning of system resources. We propose a dynamic atomic multicast protocol which fulfills these requirements. It allows to dynamically add and remove resources to an online replicated state machine and to recover crashed processes. Major efforts have been spent in recent years to improve the performance, scalability and reliability of distributed systems. In order to hide the complexity of designing distributed applications, many proposals provide efficient high-level communication abstractions. Since the implementation of a production-ready system based on this abstraction is still a major task, we further propose to expose our protocol to developers in the form of distributed data structures. B- trees for example, are commonly used in different kinds of applications, including database indexes or file systems. Providing a distributed, fault-tolerant and scalable data structure would help developers to integrate their applications in a distribution transparent manner. This work describes how to build reliable and scalable distributed systems based on atomic multicast and demonstrates their capabilities by an implementation of a distributed ordered map that supports dynamic re-partitioning and fast recovery. To substantiate our claim, we ported an existing SQL database atop of our distributed lock-free data structure

Precautionary Effect and Variations of the Value of Information

For a sequential, two-period decision problem with uncertainty and under broad conditions (non-finite sample set, endogenous risk, active learning and stochastic dynamics), a general sufficient condition is provided to compare the optimal initial decisions with or without information arrival in the second period. More generally the condition enables the comparison of optimal decisions related to different information structures. It also ties together and clarifies many conditions for the so-called irreversibility effect that are scattered in the environmental economics literature. A numerical illustration with an integrated assessment model of climate-change economics is provided.Value of Information, Uncertainty, Irreversibility effect, Climate change

Innovativeness of Ideas from Crowdsourcing Discussions

La innovació oberta pretén que les organitzacions siguin més competitives mitjançant la gestió dels recursos de les entrades i sortides de la organització. Aquestes organitzacions utilitzen discussions participatives com un mecanisme per estimular idees innovadores. No obstant això, els resultats de la major part d'aquestes discussions participatives no són tan innovadores com s'espera. Alguns acadèmics tracten d'abordar aquest problema, centrant-se principalment en la identificació d'incentius adequats per fomentar les idees, però no han prestat atenció a les característiques estructurals de la discussió participativa. Aquesta tesi es basa en teories sobre la gestió i la creativitat per tal de desenvolupar un nou marc sobre l'efecte que provoca la diversitat en la innovació de les discussions participatives. El marc proposat és validat utilitzant dades obtingudes en múltiples discussions participatives. D'altra banda, una nova metodologia es proposada per tal de evaluar el grau de consens quan es mesura la innovació de les idees, el qual està adaptat a la naturalesa difusa d'idees innovadores. En suma, les tres preguntes d'investigació abordades en aquesta tesi són: 1) Com la diversitat de la discussió participativa afecta a la capacitat d'innovació? 2) Com les característiques estructurals de la discussió participativa afecten la capacitat d'innovació? 3) Com es pot mesurar el consens a la hora de valorar la capacitat d'innovació de les idees, tenint en compte els diferents graus d'experiència dels qui prenen les decisions?. Els resultats indiquen que els antecedents de la innovació son: 1) Quan hi ha menys diversitat de l'individu abans de la idea, 2) Quan hi ha més diversitat del individu en la idea actual i 3) Si es la primera vegada que es presenta una idea.  La innovación abierta pretende que las organizaciones sean más competitivas mediante la gestión de los recursos de las entradas y salidas de la organización. Estas organizaciones utilizan discusiones participativas como un mecanismo para estimular ideas innovadoras. Sin embargo, los resultados de la mayor parte de estas discusiones participativas no son tan innovadoras como se espera. Algunos académicos tratan de abordar este problema, centrándose principalmente en la identificación de incentivos adecuados para fomentar las ideas, pero no han prestado atención a las características estructurales de la discusión participativa. Esta tesis se basa en teorías sobre la gestión y la creatividad para desarrollar un nuevo marco sobre el efecto que provoca la diversidad en la innovación de las discusiones participativas. El marco propuesto es validado utilizando datos obtenidos en múltiples discusiones participativas. Por otra parte, una nueva metodología se propuesta para evaluar el grado de consenso cuando se mide la innovación de las ideas, el cual está adaptado a la naturaleza difusa de ideas innovadoras. En suma, las tres preguntas de investigación abordadas en esta tesis son: 1) Como la diversidad de la discusión participativa afecta a la capacidad de innovación? 2) ¿Cómo las características estructurales de la discusión participativa afectan la capacidad de innovación? 3) ¿Cómo se puede medir el consenso a la hora de valorar la capacidad de innovación de las ideas, teniendo en cuenta los diferentes grados de experiencia de quienes toman las decisiones ?. Los resultados indican que los antecedentes de la innovación son: 1) Cuando hay menos diversidad del individuo antes de la idea, 2) Cuando hay más diversidad del individuo en la idea actual y 3) Si es la primera vez que se presenta una idea.Open innovation seeks to make organizations more competitive by managing the inflows and outflows of their organization. These organizations use crowdsourced discussions as a mechanism to encourage innovative ideas. However, the results of most of these crowdsourced discussions are not as innovative as expected. Some scholars seek to address this problem by mainly focusing on identifying appropriate incentives to encourage ideas, but they have not paid attention to how the structural characteristics of the crowdsourced discussion generate innovative ideas. This thesis draws from theories on management and creativity to develop a new framework about the effect of knowledge diversity on innovation in crowdsourced discussions. The proposed framework is validated using data obtained from multiple crowdsourced discussions. Moreover, a new methodology is presented for assessing the innovativeness of the ideas generated during crowdsourced discussions that is suited to the fuzzy nature of novel ideas. In sum, the three research questions addressed in this thesis are: 1) how does the diversity of the crowdsourced discussion affect innovativeness? 2) how do the characteristics of the crowdsourced discussion affect innovativeness? 3) how can the innovativeness of ideas be rated in crowdsourced discussion to take into consideration the different degrees of expertise from the decision-makers? The results indicate that less prior individual diversity, more current individual diversity, collaboration among participants, and first time posters foster innovation in crowdsourced discussion