Journal of Computer and System Sciences Impact Factor & Information

Journal description

The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted. Research Areas Include: Traditional Subjects such as: Theory of algorithms and computability; Formal languages; Automata theory; Contemporary Subjects such as Complexity theory Algorithmic; Complexity; Parallel and distributed computing; Computer networks; Neural networks; Computational learning theory; Database theory and practice Computer modeling of complex systems.

Current impact factor: 1.09

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 1.091
2012 Impact Factor 1
2011 Impact Factor 1.157
2010 Impact Factor 1.631
2009 Impact Factor 1.304
2008 Impact Factor 1.244
2007 Impact Factor 1.185
2006 Impact Factor 1.252
2005 Impact Factor 1.328
2004 Impact Factor 1.03
2003 Impact Factor 0.795
2002 Impact Factor 1.174
2001 Impact Factor 0.661
2000 Impact Factor 0.664
1999 Impact Factor 0.872
1998 Impact Factor 0.577
1997 Impact Factor 0.602
1996 Impact Factor 0.679
1995 Impact Factor 0.723
1994 Impact Factor 0.513
1993 Impact Factor 0.413
1992 Impact Factor 0.536

Impact factor over time

Impact factor
Year

Additional details

5-year impact 1.11
Cited half-life 0.00
Immediacy index 0.29
Eigenfactor 0.01
Article influence 0.97
Website Journal of Computer and System Sciences website
Other titles Journal of computer and system sciences (Online), Journal of computer and system sciences
ISSN 1090-2724
OCLC 36943413
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: NoSQL and especially graph databases are constantly gaining popularity among developers as they promise to deliver superior perfor-mance when handling highly interconnected data compared to relational databases. Apache Shindig is the reference implementation for OpenSocial with a highly interconnected data model. However, it had a relational database as back-end. In this paper we describe our experiences with the graph database Neo4j as back-end and compare Cypher, Gremlin and Java as alternatives for querying data with MySQL. We consider performance as well as usability from a developer’s perspective. Our results show that Cypher is a good query language in terms of code readability and has a moderate overhead for most queries (20-200%). However, it has to be supple-mented with “stored procedures” to make up for some performance deficits in pattern matching queries (>1000%). The RESTful API is unusable slow, whereas our WebSocket connection performs significantly better (>650%).
    Journal of Computer and System Sciences 12/2015; 81(8):forthcoming.
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    ABSTRACT: Security and privacy issues in Radio Frequency Identification (RFID) systems mainly result from limited storage and computation resources of RFID tags and unpredictable communication environment. Although many security protocols for RFID system have been proposed, most of them have various flaws. We propose a random graph-based methodology enabling automated benchmarking of RFID security. First, we formalize the capability of adversaries by a set of atomic actions. Second, Vulnerability Aware Graphs (VAGs) were developed to elaborate the interactions between adversaries and RFID systems, which are used to discover the potential attacks of adversaries via some paths on the graphs. The quantitative analysis on VAGs can predict the probability that the adversary leverages the potential flaws to perform attacks. Moreover, a joint entropy-based method is provided to measure the indistinguishability of RFID tags under passive attacks. Analysis and simulation were conducted to show the validity and effectiveness of VAGs.
    Journal of Computer and System Sciences 09/2015; 81(6). DOI:10.1016/j.jcss.2014.12.015
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    ABSTRACT: We introduce a storage scheme that allows the representation and management of the evolving hierarchical structure of a multi-version ontology in a temporal relational database. The proposed scheme is aimed at supporting ontology-based personalization and temporal access to large collections of resources (data, documents, procedures etc.) stored in a dynamic environment. Whereas in previous works we considered tree-shaped ontologies only, in this work we consider ontologies with a class hierarchy structured as a general directed graph, that is also supporting multiple inheritance and intersection classes. We will also show how multi-version ontologies must be dealt with for the processing of ontology-based personalization queries.
    Journal of Computer and System Sciences 06/2015; DOI:10.1016/j.jcss.2015.06.001
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    ABSTRACT: We study the length of polynomials over finite simple non-Abelian groups needed to realize Boolean functions. We apply the results for bounding the length of 5-permutation branching programs recognizing a Boolean set. Moreover, for Boolean and general functions on these groups, we present upper bounds on the length of shortest polynomials computing an arbitrary n-ary Boolean or general function, or a function given by another polynomial.
    Journal of Computer and System Sciences 06/2015; DOI:10.1016/j.jcss.2015.05.002
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    ABSTRACT: Subshifts of finite type are sets of colorings of the plane defined by local constraints. They can be seen as a discretization of continuous dynamical systems. We investigate here the hardness of deciding factorization, conjugacy and embedding of subshifts in dimensions for subshifts of finite type and sofic shifts and in dimensions for effective shifts. In particular, we prove that the conjugacy, factorization and embedding problems are -complete for sofic and effective subshifts and that they are -complete for SFTs, except for factorization which is also -complete.
    Journal of Computer and System Sciences 06/2015; DOI:10.1016/j.jcss.2015.05.003
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    ABSTRACT: Classical versions of Kolmogorov complexity are incomputable. Nevertheless, in 1975 Solovay showed that there are computable functions such that for infinitely many strings σ, , where K denotes prefix-free Kolmogorov complexity. Such an f is now called a Solovay function. We prove that many classical results about K can be obtained by replacing K by a Solovay function. For example, the three following properties of a function g all hold for the function K.
    Journal of Computer and System Sciences 05/2015; DOI:10.1016/j.jcss.2015.04.004
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    ABSTRACT: We consider a generalisation of the classical problem of pattern avoidance in infinite words with functional dependencies between pattern variables. More precisely, we consider patterns involving permutations. The foremost remarkable fact regarding this new setting is that the notion of avoidability index (the smallest alphabet size for which a pattern is avoidable) is meaningless, since a pattern with permutations that is avoidable in one alphabet can be unavoidable in a larger alphabet. We characterise the (un-)avoidability of all patterns of the form , called cubic patterns with permutations here, for all alphabet sizes in both the morphic and antimorphic case.
    Journal of Computer and System Sciences 04/2015; 81(7). DOI:10.1016/j.jcss.2015.04.001
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    Journal of Computer and System Sciences 03/2015; 78(7). DOI:10.1016/j.jcss.2015.02.002
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    ABSTRACT: This paper studies the problem of finding the path median on a tree in which vertex weights are uncertain and the uncertainty is characterized by given intervals. It is required to find a minmax regret solution, which minimizes the worst-case loss in the objective function. An -time algorithm is presented, improving the previous upper bound from .
    Journal of Computer and System Sciences 02/2015; 127(7). DOI:10.1016/j.jcss.2015.01.002
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    ABSTRACT: Accurate simulation is vital for the proper design and evaluation of any computing architecture. Researchers seek unified simulation frameworks that can model heterogeneous architectures like CPU and GPU devices and their interactions as computing patterns move toward heterogeneous era. In this paper, we introduce MCMG (Multi-CPU Multi-GPU) simulator, a cycle accurate, modular and open-source toolset that enables simulating x86 CPUs and Nvidia G80 like GPUs simultaneously. Targeting heterogeneous architectural exploration, MCMG supports fully configuration of multiple CPUs, GPUs and their memory sub-system. Not only CPUs, relative running frequency of each GPU can be also defined conveniently. Simulation validation is demonstrated with a preliminary architectural exploration study. Then we present shared LLC access results of heterogeneous cores and show reasonable explanation. Finally, we conclude the job.
    Journal of Computer and System Sciences 02/2015; 81(1):57–71. DOI:10.1016/j.jcss.2014.06.017
  • Journal of Computer and System Sciences 02/2015; 81(1):1–2. DOI:10.1016/j.jcss.2014.09.001
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    ABSTRACT: Although Collaborative Filtering (CF) -based recommender systems have received great success in a variety of applications, they still under-perform and are unable to provide accurate recommendations when users and items have few ratings, resulting in reduced coverage. To overcome these limitations, we propose an effective hybrid user-item trust-based (HUIT) recommendation approach in this paper that fuses the users' and items' implicit trust information. We have also considered and computed user and item global reputations into this approach. This approach allows the recommender system to make an increased number of accurate predictions, especially in circumstances where users and items have few ratings. Experiments on four real-world datasets, particularly a business-to-business (B2B) case study, show that the proposed HUIT recommendation approach significantly outperforms state-of-the-art recommendation algorithms in terms of recommendation accuracy and coverage, as well as significantly alleviating data sparsity, cold-start user and cold-start item problems.
    Journal of Computer and System Sciences 01/2015; 81(7). DOI:10.1016/j.jcss.2014.12.029
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    ABSTRACT: Data deduplication is an attractive technology to reduce storage space for increasing vast amount of duplicated and redundant data. In a cloud storage system with data deduplication, duplicate copies of data will be eliminated and only one copy will be kept in the storage. To protect the confidentiality of sensitive data while supporting deduplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing. However, the issue of keyword search over encrypted data in deduplication storage system has to be addressed for efficient data utilization. This paper firstly proposes two constructions which support secure keyword search in this scenario. In these constructions, the integrity of the data can be realized by just checking the convergent key, without other traditional integrity auditing mechanisms. Then, two extensions are presented to support fuzzy keyword search and block-level deduplication. Finally, security analysis is given.
    Journal of Computer and System Sciences 01/2015; DOI:10.1016/j.jcss.2014.12.026
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    ABSTRACT: Motivated by the need for robust and fast distributed computation in highly dynamic Peer-to-Peer (P2P) networks, we study algorithms for the fundamental distributed agreement problem. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to design fast algorithms (running in a small number of rounds) that guarantee, despite high node churn rate, that almost all nodes reach a stable agreement. Our main contributions are randomized distributed algorithms that guarantee stable almost-everywhere agreement with high probability even under high adversarial churn in number of rounds that is polylogarithmic in n, where n is the stable network size. In particular, we present the following results:
    Journal of Computer and System Sciences 01/2015; 81(7). DOI:10.1016/j.jcss.2014.10.005
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    ABSTRACT: Nonlinear feedback shift registers (NFSRs) have been used as the main building blocks in many stream ciphers and convolutional decoders. The linearization of NFSRs is to find their state transition matrices. This paper uses a Boolean network approach to facilitate the linearization of NFSRs. A new state transition matrix is found for an NFSR, which can be simply computed from the truth table of its feedback function. Compared to the existing results, the new state transition matrix is easier to compute and is more explicit. Some properties of the matrix are provided, which are helpful to theoretically analyze NFSRs.
    Journal of Computer and System Sciences 12/2014; 81(4). DOI:10.1016/j.jcss.2014.12.030