International Journal Papers

Permanent URI for this collectionhttp://dl.cerist.dz/handle/CERIST/17

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Author: search.filters.author.Yahiaoui, SaïdStart date: 1997

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Now showing 1 - 10 of 13
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    Smart Mobility in Smart Cities: Emerging challenges, recent advances and future directions
    (Taylor & Francis, 2023-08-13) Goumiri, Soumia; Yahiaoui, Saïd; Djahel, Soufiene
    The world is witnessing a vivid race toward developing advanced solutions to enable smart, fast, affordable and environment friendly mobility for Smart Cities inhabitants. This led to the emergence of the Smart Mobility concept, attracting significant attention from major actors in the mobility sector including policy makers and traffic authorities. Therefore, this survey paper presents an overview of Smart Mobility and discusses the main challenges associated with its key building blocks, parking and traffic management, traffic routing in addition to emissions and road safety implications. Then, the most important works that attempted to address these challenges are presented, and their strengths and limitations are analyzed. Finally, the lessons learned from this study and the most promising future directions to tackle these challenges are presented.
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    Lifetime-Aware Backpressure : A New Delay-Enhanced Backpressure-Based Routing Protocol
    (IEEE, 2019-03) Kabou, Abdelbaset; Nouali-Taboudjemat, Nadia; Djahel, Soufiene; Yahiaoui, Saïd; Nouali, Omar
    Dynamic backpressure is a highly desirable family of routing protocols known for their attractive mathematical properties. However, these protocols suffer from a high end-to-end delay making them inefficient for real-time traffic with strict end-to-end delay requirements. In this paper, we address this issue by proposing a new adjustable and fully distributed backpressure-based scheme with low queue management complexity, named Lifetime-Aware Backpressure (LTA-BP). The novelty in the proposed scheme consists in introducing the urgency level as a new metric for service differentiation among the competing traffic flows in the network. Our scheme not just significantly improves the quality of service provided for real-time traffic with stringent end-to-end delay constraints, but interestingly protects also the flows with softer delay requirements from being totally starved. The proposed scheme has been evaluated and compared against other state-of-the-art routing protocol, using computer simulation, and the obtained results show its superiority in terms of the achieved end-to-end delay and throughput.
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    Fast parallel algorithms for finding elementary circuits of a directed graph: a GPU-based approach
    (Springer Science+Business Media, 2023-03) Benachour, Amira; Yahiaoui, Saïd; El Baz, Didier; Nouali‑Taboudjemat, Nadia; Kheddouci, Hamamache
    Circuits in a graph are interesting structures and identifying them is of an important relevance for many applications. However, enumerating circuits is known to be a difficult problem, since their number can grow exponentially. In this paper, we propose fast parallel approaches for enumerating elementary circuits of directed graphs based on graphics processing unit (GPU). Our algorithms are based on a massive exploration of the graph in a breadth-first search strategy. Algorithm V-FEC explores the graph starting from different vertices simultaneously. To further reduce the search space, we present T-FEC, another algorithm that uses triplets as an initial set to start exploring. To the best of our knowledge, those are the first parallel GPU-based algorithms for finding all circuits of a given graph. In addition, they find circuits of a given length and circuits with a specific vertex or edge. The evaluation results show that the proposed approaches achieve up to 190x speed-up over Johnson’s algorithm, one of the most efficient sequential algorithms for finding circuits.
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    Coloring based approach for matching unrooted and/or unordered trees
    (Elsevier, 2013-04) Yahiaoui, Saïd; Haddad, Mohammed; Effantin, Brice; Kheddouci, Hamamache
    We consider the problem of matching unrooted unordered labeled trees, which refers to the task of evaluating the distance between trees. One of the most famous formalizations of this problem is the computation of the edit distance defined as the minimum-cost sequence of edit operations that transform one tree into another. Unfortunately, this problem has been proved to be NP-complete. In this paper, we propose a new algorithm to measure distance between unrooted unordered labeled trees. This algorithm uses a specific graph coloring to decompose the trees into small components (stars and bistars). Then, it determines a distance between two trees by computing the edit distance between their components. We prove that the proposed distance is a pseudo-metric and we analyze its time complexity. Our experimental evaluations on large synthetic and real world datasets confirm our analytical results and suggest that the distance we propose is accurate and its algorithm is scalable.
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    Reachability in big graphs : A distributed indexing and querying approach
    (Elsevier, 2021-09) Hocine, Imane; Yahiaoui, Saïd; Bendjoudi, Ahcene; Nouali-Taboudjemat, Nadia
    The advent of Big graphs characterized by their enormous number of nodes, with multiple edges between them makes the existing reachability query indexing approaches unable to guarantee a reasonable time for both the index construction and query steps. Therefore a novel approach that takes into account these new characteristics during the graph processing is needed. In this paper, we propose an Overlay Graph-based Distributed Reachability Indexing approach (ODRI), an indexing scheme through which the index construction and reachability query are processed in a parallel and distributed manner. The key idea of ODRI is to process a Big graph as a set of smaller subgraphs (partitions) interconnected to each other through an overlay graph. In this way, the partitions can be indexed in parallel and, at the same time, the reachability information can also be extracted. Hence, the index construction and query processing time will be reduced significantly. Therefore, ODRI ensures the scalability of Big graphs, which is a challenge for the existing reachability approaches. Besides, we formally prove that this strategy preserves the reachability properties. Using real-life data, we experimentally verify that our approach outperforms the state-of-the-art methods, and is scalable in terms of the number of partitions, regardless of how graphs are distributed.
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    Efficient parallel branch-and-bound approaches for exact graph edit distance problem
    (Elsevier, 2022-12) Dabah, Adel; Chegrane, Ibrahim; Yahiaoui, Saïd; Bendjoudi, Ahcene
    Graph Edit Distance (GED) is a well-known measure used in the graph matching to measure the similarity/dissimilarity between two graphs by computing the minimum cost of edit operations needed to transform one graph into another. This process, Which appears to be simple, is known NP-hard and time consuming since the search space is increasing exponentially. One way to optimally solve this problem is by using Branch and Bound (B&B) algorithms, Which reduce the computation time required to explore the whole search space by performing an implicit enumeration of the search space instead of an exhaustive one based on a pruning technique. nevertheless, They remain inefficient when dealing with large problem instances due to the impractical running time needed to explore the whole search space. To overcome this issue, We propose in this paper three parallel B&B approaches based on shared memory to exploit the multi-core CPU processors: First, a work-stealing approach where several instances of the B&B algorithm explore a single search tree concurrently achieving speedups up to 24 faster than the sequential version. Second, a tree-based approach where multiple parts of the search tree are explored simultaneously by independent B&B instances achieving speedups up to 28. Finally, Due to the irregular nature of the GED problem, two load-balancing strategies are proposed to ensure a fair workload between parallel processes achieving impressive speedups up to 300. all experiments have been carried out on well-known datasets
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    A Survey on Distributed Graph Pattern Matching in Massive Graphs
    (ACM, 2021-02) Bouhenni, Sarra; Yahiaoui, Saïd; Nouali-Taboudjemat, Nadia; Kheddouci, Hamamache
    Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed GPM models have emerged as they yield interesting results in a polynomial time. However, massive graphs generated by mostly social networks require a distributed storing and processing of the data over multiple machines, thus, requiring GPM to be revised by adopting new paradigms of big graphs processing, e.g., Think-Like-A-Vertex and its derivatives. This article discusses and proposes a classification of distributed GPM approaches with a narrow focus on the relaxed models.
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    Distributed graph pattern matching via bounded dual simulation
    (Elsevier, 2022-09) Bouhenni, Sarra; Yahiaoui, Saïd; Nouali-Taboudjemat, Nadia; Kheddouci, Hamamache
    Graph Pattern Matching (GPM) finds subgraphs of a large data graph that are similar to an input query graph. It has many applications, such as pattern recognition, detecting plagiarism, and finding communities in social networks. Current real-world applications generate massive amounts of data that cannot be stored on the memory of a single machine, which raises the need for distributed storage and processing. Recent relaxed GPM models, although of polynomial time complexity, are nevertheless not distributed by nature. Moreover, the existing relaxed GPM algorithms are limited in terms of scalability. In this paper, we propose Bounded Dual Simulation (BDSim) as a new relaxed model for a scalable evaluation of GPM in massive graphs. BDSim captures more semantic similarities compared to graph simulation, dual simulation, and even strong simulation. It preserves the vertices’ proximity by eliminating cycles of unbounded length from the resulting match graph. Furthermore, we propose distributed vertex-centric algorithms to evaluate BDSim. We prove their effectiveness and efficiency through detailed theoretical validation and extensive experiments conducted on real-world and synthetic datasets. To the best of our knowledge, BDSim is the first relaxed GPM model that captures the cyclic structure of the query graph while being feasible in cubic time.
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    Efficient approximate approach for graph edit distance problem
    (Elsevier, 2021-11) Dabah, Adel; Chegrane, Ibrahim; Yahiaoui, Saïd
    Graph Edit Distance (GED) problem is a well-known tool used to measure the similarity/dissimilarity between two graphs. It searches for the best set of edit operations (in terms of cost) that transforms one graph into another. Due to the NP-hardness nature of the problem, the search space increases exponentially making exact approaches impossible to use for large graphs. In this context, there is a huge need for approaches that give near-optimal results in reasonable time. In this paper, we propose a tree-based approximate approach for dealing with GED problem. It operates on a search tree that models all possible solutions of the problem. Since exploring the whole tree is impractical; this approach keeps only the best nodes at each level of the tree for further exploration. This reduces enormously the execution time without scarifying the solution quality. Experiments using small and medium size data-sets show the low deviation of our results as compared to the optimal results of a Depth First Search algorithm. Moreover, our approach show a strong scalability potential by dealing with large data-sets in low execution time.
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    Multi-objective offline and online path planning for UAVs under dynamic urban environment
    (2022-03) Sadallah, Nassim; Yahiaoui, Saïd; Bendjoudi, Ahcene; Nouali-Taboudjemat, Nadia
    This paper presents a multi-objective hybrid path planning method MOHPP for unmanned aerial vehicles (UAVs) in urban dynamic environments. Several works have been proposed to find optimal or near-optimal paths for UAVs. However, most of them did not consider multiple decision criteria and/or dynamic obstacles. In this paper, we propose a multi-objective offline/online path planning method to compute an optimal collision-free path in dynamic urban environment, where two objectives are considered: the safety level and the travel time. First, we construct two models of obstacles; static and dynamic. The static obstacles model is based on Fast Marching Square (FM2) method to deal with the uncertainty of the geography map, and the unexpected dynamic obstacles model is constructed using the perception range and the safety distance of the UAV. Then, we develope a jointly offline and online search mechanism to retrieve the optimal path. The offline search is applied to find an optimal path vis-a-vis the static obstacles, while the online search is applied to quickly avoid unexpected dynamic obstacles. Several experiments have been performed to prove the efficiency of the proposed method. In addition, a Pareto front is extracted to be used as a tool for decision making.