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Solving the pickup and delivery problem with time windows (PDPTW) is a vital research topic due to its NP-hardness and its numerous practical applications. In this paper, we propose an island-model parallel memetic algorithm for minimizing the distance in the PDPTW. In this algorithm, the processes execute the same memetic algorithm and co-operate to guide the optimization efficiently. An extensive...
Nowadays, data security is a demand for companies when adopting storage services on public clouds. From long term persistence services, such as Amazon Glacier, to online block storage systems for virtual machines disks, security principles can be part of the cloud context, especially for customer's sensitive data. The confidentiality of storage services considers aspects such as data life-cycle, location,...
As data sets grow rapidly in size and the number, an outlier detection that filters unnecessary normal information becomes important. In this paper, we propose to move the outlier detection from an application layer to a NIC (Network Interface Card). Only anomalous items or events are delivered for a network protocol stack and the other packets are discarded at the NIC. The demands for storage and...
In this paper, we propose a parallel implementation of LDSieve, a recently published sieving algorithm for the SVP, which achieves the best theoretical complexity to this day, on parallel shared-memory systems. In particular, we propose a scalable parallel variant of LDSieve that is probabilistically lock-free and relaxes the properties of the algorithm to favour parallelism. We use our parallel variant...
This paper describes our research to provide high performance I/O for seismic wave propagation simulations. Earthquake early warning systems are designed to provide near real-time prediction of strong ground motion. Such systems are crucial tools for risk mitigation and disaster prevention. The ability to accurately and quickly simulate the propagation of seismic waves in complex media lies at the...
In order to minimise their energy use, data centre operators are constantly exploring new ways to construct computing infrastructures. As low power CPUs, exemplified by ARM-based devices, are becoming increasingly popular, there is a growing trend for the large scale deployment of low power servers in data centres. For example, recent research has shown promising results on constructing small scale...
The performance gap between processors and I/O represents a serious scalability limitation for applications running on computing clusters. Parallel file systems often provide mechanisms that allow programmers to disclose their I/O pattern knowledge to the lower layers of the I/O stack through a hints API. This information can be used by the file system to boost the application performance. Unfortunately,...
This paper presents a hybrid partitioning method used to improve the performance of solving a Satisfiability (SAT) problem. The principle of our approach consist firstly to apply a static partitioning to decompose the search tree in finite set of disjoint sub-trees, than assign each sub-tree to one computing core. However it is not easy to choose the relevant branching variables to partition the search...
High-volume data streams are straining the limits of stream processing frameworks which need advanced parallel processing capabilities to withstand the actual incoming bandwidth. Parallel processing must be synergically integrated with elastic features in order dynamically scale the amount of utilized resources by accomplishing the Quality of Service goals in a cost-effective manner. This paper proposes...
Malicious applications have become increasingly numerous. This demands adaptive, learning-based techniques for constructing malware detection engines, instead of the traditional manual-based strategies. Prior work in learning-based malware detection engines primarily focuses on dynamic trace analysis and byte-level n-grams. Our approach in this paper differs in that we use compiler intermediate representations,...
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