Abstract
All companies developing their business on the Web, not only giants like Google or Facebook but also small com- panies focused on niche markets, face scalability issues in data management. The case study of this paper is the content management systems for classified or commercial advertise-ments on the Web. The data involved has a very significant growth rate and a read-intensive access pattern with a reduced update rate. Typically, data is stored in traditional file systems hosted on dedicated servers or Storage Area Network devices due to the generalization and ease of use of file systems. However, this ease in implementation and usage has a disadvantage: the centralized nature of these systems leads to availability, elasticity and scalability problems. The scenario under study, undemanding in terms of the system's consistency and with a simple interaction model, is suitable to a distributed database, such as Cassandra, conceived precisely to dynamically handle large volumes of data. In this paper, we analyze the suitability of Cassandra as a substitute for file systems in content management systems. The evaluation, conducted using real data from a produc- tion system, shows that using Cassandra, one can easily get horizontal scalability of storage, redundancy across multiple independent nodes, and load distribution imposed by the periodic activities of safeguarding data, while ensuring a comparable performance to that of a file system.

Abstract
In cloud environments, resources should be acquired and released automatically and quickly at runtime. Thereby, the implementation of traditional query optimization strategies in cloud platforms can have a poor performance, because they cannot predict future availability and/or release of resources. In such scenarios, adaptive query processing can adapt itself to the available resources to run queries and, consequently, present an acceptable performance in response to a query. However, traditional and adaptive query optimizers main objective is to reduce response time. Moreover, in the context of cloud computing, users and providers of services expect to get answers in time to guarantee the SLA. Therefore, we propose a framework that uses adaptive query processing based on heuristic rules and cost of failing the SLA. It will be implemented on structured data, considering that some cloud computing platforms support SQL queries directly or indirectly, which makes this problem relevant.

Abstract
Digital public displays can have a key role in urban ubiquitous computing infrastructures, but they have not yet managed to fill this role. A key step in that direction would be the emergence of an application model for open display networks that would enable anyone to create applications for display infrastructures. In this work, we study the development of web-based applications for public displays. We report on our experience of application development for real world public deployment and also on an experiment with external web developers to assess their ability to create such applications using our own development tools. The results show that the web-based app model can effectively be used in the context of public displays and that web developers are able to leverage upon their expertise to create this type of applications. © Springer International Publishing 2013.

Abstract
Causality plays a central role as a building block in solving important problems in distributed systems, such as replication, debugging, group communication and global snapshots. To be useful, causality must be realised by actual mechanisms that can track it and encode it. Existing causality tracking mechanisms, such as vector clocks and version vectors, rely on mappings from globally unique identifiers to integer counters. In a system with a well known set of entities these identifiers can be pre-configured and given distinct positions in a vector or distinct names in a mapping. Identity management is more problematic in dynamic systems, with a large and highly variable number of entities, being worsened when network partitions occur. Present solutions for causality tracking are not appropriate to these increasingly common scenarios. This work introduces novel causality tracking mechanisms that can be used in scenarios with a dynamic number of entities. These allow completely decentralised creation of entities (processes or replicas) with no need for global identifiers or global coordination. These mechanisms have a variable size representation that adapts automatically to the number of entities, growing or shrinking appropriately. This book is the published version of the second half of my PhD thesis, and focus its discourse on causality tracking for disconnected and semi-connected distributed systems.

Abstract
Causality plays a central role as a building block in solving important problems in distributed systems, such as replication, debugging, group communication and global snapshots. To be useful, causality must be realised by actual mechanisms that can track it and encode it. Existing causality tracking mechanisms, such as vector clocks and version vectors, rely on mappings from globally unique identifiers to integer counters. In a system with a well known set of entities these identifiers can be pre-configured and given distinct positions in a vector or distinct names in a mapping. Identity management is more problematic in dynamic systems, with a large and highly variable number of entities, being worsened when network partitions occur. Present solutions for causality tracking are not appropriate to these increasingly common scenarios. This work introduces novel causality tracking mechanisms that can be used in scenarios with a dynamic number of entities. These allow completely decentralised creation of entities (processes or replicas) with no need for global identifiers or global coordination. These mechanisms have a variable size representation that adapts automatically to the number of entities, growing or shrinking appropriately. This book is the published version of the first half of my PhD thesis, and focus its discourse on logical clock systems and the challenges of autonomous operation.

Abstract
Interaction constraints are an expressive formalism for describing coordination patterns, such as those underlying the coordination language Reo, that can be efficiently implemented using constraint satisfaction technologies such as SAT and SMT solvers. Existing implementations of interaction constraints interact with external components only in a very simple way: interaction occurs only between rounds of constraint satisfaction. What is missing is any means for the constraint solver to interact with the external world during constraint satisfaction. This paper introduces interactive interaction constraints which enable interaction during constraint satisfaction, and in turn increase the expressiveness of coordination languages based on interaction constraints by allowing a larger class of operations to be considered to occur atomically. We describe how interactive interaction constraints are implemented and detail a number of strategies for guiding constraint solvers. The benefit of interactive interaction constraints is illustrated using two examples, a hotel booking system and a system of transactions with compensations. From a general perspective, our work describes how to open up and exploit constraint solvers as the basis of a coordination engine. © 2013 IFIP International Federation for Information Processing.