Fundamenta Informaticae - Volume 163, issue 2

Authors: Munir, Rana Faisal | Nadal, Sergi | Romero, Oscar | Abelló, Alberto | Jovanovic, Petar | Thiele, Maik | Lehner, Wolfgang

Article Type: Research Article

Abstract: Data-intensive flows deploy a variety of complex data transformations to build information pipelines from data sources to different end users. As data are processed, these workflows generate large intermediate results, typically pipelined from one operator to the following ones. Materializing intermediate results, shared among multiple flows, brings benefits not only in terms of performance but also in resource usage and consistency. Similar ideas have been proposed in the context of data warehouses, which are studied under the materialized view selection problem. With the rise of Big Data systems, new challenges emerge due to new quality metrics captured by service level …agreements which must be taken into account. Moreover, the way such results are stored must be reconsidered, as different data layouts can be used to reduce the I/O cost. In this paper, we propose a novel approach for automatic selection of multi-objective materialization of intermediate results in data-intensive flows, which can tackle multiple and conflicting quality objectives. In addition, our approach chooses the optimal storage data format for selected materialized intermediate results based on subsequent access patterns. The experimental results show that our approach provides 40% better average speedup with respect to the current state-of-the-art, as well as an improvement on disk access time of 18% as compared to fixed format solutions. Show more

Keywords: Big Data, Data-Intensive Flows, Intermediate Results, Data Format, HDFS

DOI: 10.3233/FI-2018-1734

Citation: Fundamenta Informaticae, vol. 163, no. 2, pp. 111-138, 2018

Authors: Aguzzoli, Stefano | Boffa, Stefania | Ciucci, Davide | Gerla, Brunella

Article Type: Research Article

Abstract: We show that finite IUML-algebras, which are residuated lattices arising from an idempotent uninorm, can be interpreted as algebras of sequences of orthopairs whose main operation is defined starting from the three-valued Sobociński operator between rough sets. Our main tool is the representation of finite IUML-algebras by means of finite forests.1

Keywords: Orthopairs, forests, IUML-algebras

DOI: 10.3233/FI-2018-1735

Citation: Fundamenta Informaticae, vol. 163, no. 2, pp. 139-163, 2018

Authors: Michaliszyn, Jakub | Otop, Jan | Witkowski, Piotr

Article Type: Research Article

Abstract: We study variants of the satisfiability problem of elementary modal logics, i.e., modal logic considered over first-order definable classes of frames. The standard semantics of modal logic allows infinite structures, but often practical applications require to restrict our attention to finite structures. A number of decidability and undecidability results for the elementary modal logics were proved separately for general satisfiability and finite satisfiability. In this paper we justify that the results for both kinds of the satisfiability problem must be shown separately – we prove that there is a universal first-order formula that defines an elementary modal logic with decidable …general satisfiability problem, but undecidable finite satisfiability problem, and, the other way round, that there is a universal first-order formula that defines an elementary modal logic with decidable finite satisfiability problem, but undecidable general satisfiability problem. Show more

DOI: 10.3233/FI-2018-1736

Citation: Fundamenta Informaticae, vol. 163, no. 2, pp. 165-188, 2018

Authors: Schiopu, Camelia | Ciurea, Eleonor

Article Type: Research Article

Abstract: This article states and solves the maximum flow in directed (1, n ) planar dynamic networks with lower bounds. We present the case when the planar dynamic network is stationary. Finally, we present an example for this problem.

Keywords: maximum flow, planar network, dynamic network, lower bounds

DOI: 10.3233/FI-2018-1737

Citation: Fundamenta Informaticae, vol. 163, no. 2, pp. 189-204, 2018

Authors: Tong, Lyuyang | Dong, Minggang | Ai, Bing | Jing, Chao

Article Type: Research Article

Abstract: Particle swarm optimization (PSO) is a population-based stochastic optimization technique that can be applied to solve optimization problems. However, there are some defects for PSO, such as easily trapping into local optimum, slow velocity of convergence. This paper presents the simple butterfly particle swarm optimization algorithm with the fitness-based adaptive inertia weight and the opposition-based learning average elite strategy (SBPSO) to accelerate convergence speed and jump out of local optimum. SBPSO has the advantages of the simple butterfly particle swarm optimizer to increase the probability of finding the global optimum in the course of searching. Moreover, SBPSO benefits from the …simple particle swarm (sPSO) to accelerate convergence speed. Furthermore, SBPSO adopts the opposition-based learning average elite to enhance the diversity of the particles in order to jump out of local optimum. Additionally, SBPSO generates the fitness-based adaptive inertia weight ω to adapt to the evolution process. Eventually, SBPSO presents a approach of random mutation location to enhance the diversity of the population in case of the position out of range. Experiments have been conducted with eleven benchmark optimization functions. The results have demonstrated that SBPSO outperforms than that of the other five recent proposed PSO in obtaining the global optimum and accelerating the velocity of convergence. Show more

Keywords: Particle swarm Optimization (PSO), BF-PSO (Butterfly-PSO), adaptive inertia weight, opposition-based learning

DOI: 10.3233/FI-2018-1738

Citation: Fundamenta Informaticae, vol. 163, no. 2, pp. 205-223, 2018