Alexandros Labrinidis

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In-network aggregation has been proposed as one method for reducing energy consumption in sensor networks. In this paper, we explore two ideas related to further reducing energy consumption in the context of in-network aggregation. The first is by influencing the construction of the routing trees for sensor networks with the goal of reducing the size of(More)
Stream processing has become the dominant processing model for monitoring and real-time analytics. Modern Parallel Stream Processing Engines (pSPEs) have made it feasible to increase the performance in both monitoring and analytical queries by parallelizing a query’s execution and distributing the load on multiple workers. A determining factor for the(More)
The elasticity brought by cloud infrastructure provides a promising solution for a data stream management system to handle its incoming workload, which can be highly variable: the system can scale out when heavily loaded, and scale in otherwise. In such a solution, the efficiency of the mechanism used to migrate a query from one node to another is very(More)
The use of smartphone devices over the past years seems to follow a growing trend. This great acceptance along with the endless possibilities that go hand to hand with having a mini computer at all times within reach, can explain this vast interest shown by solo developers and major companies in the mobile industry. As a result, many innovative applications(More)
More and more organizations (commercial, health, government and security) currently base their decisions on real-time analysis of fast arriving, large volumes of data streams. For such analysis to lead to actionable information in real-time and at the right time, the most recent data needs to be processed within a specified delay target. Effective solutions(More)
Large graph datasets have caused renewed interest for graph partitioning. However, existing well-studied graph partitioners often assume that vertices of the graph are always active during the computation, which may lead to time-varying skewness for traversal-style graph workloads, like Breadth First Search, since they only explore part of the graph in each(More)
The rapid growth of monitoring applications has led to unprecedented amounts of generated time series data. Data analysts typically explore such large volumes of time series data looking for valuable insights. One such insight is finding pairs of time series, in which subsequences of values exhibit certain levels of correlation. However, since exploratory(More)
Data stream processing is becoming essential in most current advanced scientific or business applications as data production rates are increasing. Different companies compete to efficiently ingest high velocity data and apply some form of computation in order to make better business decisions. In order to successfully compete in this environment, companies(More)