Search

Applications based on event processing are often designed to continuously evaluate set of events defined by sliding time windows. Solutions employing long-running continuous queries executed in-memory show their limits in applications characterized by a staggering growth of available sources that continuously produce new events at high rates (e.g. intrusion detection systems and algorithmic trading). Problems arise due to the complexities in maintaining large amounts of events in memory for continuous elaboration, and due to the difficulties in managing at run-time the network of elaborating nodes. A batch approach to this kind of computation provides a viable solution for scenarios characterized by non frequent computations of very large time windows.In this paper we propose a model for batch processing in time window event computations that allows the definition of multiple metrics for performance optimization. These metrics specifically take into account the organization of input data to minimize its impact on computation latency. The model is then instantiated on Hadoop, a batch processing engine based on the MapReduce paradigm, and a set of strategies for efficiently arranging input data is described and evaluated.

Data Centers are evolving to adapt to emerging IT trends such as Big Data and Cloud Computing, which push for increased scalability and improved service availability. Among the side effects of this kind of evolution, the proliferation of new security breaches represents a major issue that usually does not get properly addressed since the focus tends to be kept on developing an innovative high-performance technology rather than making it secure. Consequently, new distributed applications deployed on Data Centers turn out to be vulnerable to malicious attacks. This paper analyzes the vulnerabilities of the gossip-based membership protocol used by Cassandra, a well-known distributed NoSQL Database. Cassandra is being widely employed as storage service in applications where very large data volumes have to be managed. An attack exploiting such weaknesses is presented, which impacts on Cassandra's availability by affecting both the latency and the successful outcome of requests. A lightweight solution is also proposed that prevents this threat from succeeding at the price of a negligible overhead.

This paper studies the problem of building a byzantine fault tolerant storage service in a distributed system affected by servers join and leave (i.e., servers churn). We show a bound for ensuring both validity of read operations and the persistence of a value written by a write operation. This bound correlates the churn rate, the number of faulty processes and the time taken by register operations (i.e., join, read and write operations).

In the last few years there has been a growing interest in small, low-power hardware platforms that integrate sensing, processing and wireless communication capabilities that can be adopted to quickly deploy powerful wireless sensor networks. Applications for WSNs often apply the event-based interaction paradigm for communication among participants. In this paper we report our experiences with the testing of JORAM, a well known JMS implementation, on top of the Sun SPOT wireless sensor platform.

We propose a new synchronization protocol devised to support multiplayer online games (MOGs) over peer-to-peer architectures. The dissemination of game events is performed through an overlay network. Peers are kept synchronized thanks to an optimistic mechanism which is able to drop obsolete events (i.e., events that lose their importance as the game goes on) and to allow different processing orders for non-correlated events (i.e., events which do not represent competing actions in the virtual world). To allow a fast identification of obsolete events, a gossip protocol is added to the synchronization mechanism, which is in charge of spreading in background information on generated game events. Results coming from extensive simulations confirm the viability of our approach.