Bilgisayar Mühendisliği Bölümü Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940
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Article Minimum Repair Bandwidth Ldpc Codes for Distributed Storage Systems(IEEE, 2023) Pourmandi, Massoud; Pusane, Ali Emre; Arslan , Şuayb Şefik; Haytaoğlu, ElifIn distributed storage systems (DSS), an optimal code design must meet the requirements of efficient local data regeneration in addition to reliable data retention. Recently, lowdensity parity-check (LDPC) codes have been proposed as a promising candidate that can secure high data rates as well as low repair bandwidth while maintaining low complexity in data reconstruction. The main objective of this study is to optimize the repair bandwidth characteristics of LDPC code families for a DSS application while meeting the data reliability requirements. First, a data access scenario in which nodes contact other available nodes randomly to download data is examined. Later, a minimum-bandwidth protocol is considered in which nodes make their selections based on the degree numbers of check nodes. Through formulating optimization problems for both protocols, a fundamental trade-off between the decoding threshold and the repair bandwidth is established for a given code rate. Finally, conclusions are confirmed by numerical results showing that irregular constructions have a large potential for establishing optimized LDPC code families for DSS applications.Article Citation - Scopus: 1A New Benchmark Dataset for P300 Erp-Based Bci Applications(Academic Press Inc Elsevier Science, 2023-04-01) Çakar, Tuna; Özkan, Hüseyin; Musellim, Serkan; Arslan, Suayb S.; Yağan, Mehmet; Alp, NihanBecause of its non-invasive nature, one of the most commonly used event-related potentials in brain -computer interface (BCI) system designs is the P300 electroencephalogram (EEG) signal. The fact that the P300 response can easily be stimulated and measured is particularly important for participants with severe motor disabilities. In order to train and test P300-based BCI speller systems in more realistic high-speed settings, there is a pressing need for a large and challenging benchmark dataset. Various datasets already exist in the literature but most of them are not publicly available, and they either have a limited number of participants or utilize relatively long stimulus duration (SD) and inter-stimulus intervals (ISI). They are also typically based on a 36 target (6 x 6) character matrix. The use of long ISI, in particular, not only reduces the speed and the information transfer rates (ITRs) but also oversimplifies the P300 detection. This leaves a limited challenge to state-of-the-art machine learning and signal processing algorithms. In fact, near-perfect P300 classification accuracies are reported with the existing datasets. Therefore, one certainly needs a large-scale dataset with challenging settings to fully exploit the recent advancements in algorithm design (machine learning and signal processing) and achieve high-performance speller results. To this end, in this article we introduce a new freely-and publicly-accessible P300 dataset obtained using 32-channel EEG, in the hope that it will lead to new research findings and eventually more efficient BCI designs. The introduced dataset comprises 18 participants performing a 40 -target (5 x 8) cued-spelling task, with reduced SD (66.6 ms) and ISI (33.3 ms) for fast spelling. We have also processed, analyzed, and character-classified the introduced dataset and we presented the accuracy and ITR results as a benchmark. The introduced dataset and the codes of our experiments are publicly accessible at https://data .mendeley.com /datasets /vyczny2r4w.(c) 2023 Elsevier Inc. All rights reserved.Conference Object Citation - Scopus: 1Improved Bounds on the Moments of Guessing Cost(IEEE, 2022-06-26) Arslan, Suayb S.; Haytaoglu, ElifGuessing a random variable with finite or countably infinite support in which each selection leads to a positive cost value has recently been studied within the context of "guessing cost". In those studies, similar to standard guesswork, upper and lower bounds for the rho-th moment of guessing cost are described in terms of the known measure Renyi's entropy. In this study, we non-trivially improve the known bounds using previous techniques along with new notions such as balancing cost. We have demonstrated that the novel lower bound proposed in this work, achieves 5.84%, 18.47% higher values than that of the known lower bound for rho = 1 and rho = 5, respectively. As for the upper bound, the novel expression provides 10.93%, 5.54% lower values than that of the previously presented bounds for rho = 1 and rho = 5, respectively.Article Citation - WoS: 3Citation - Scopus: 3Array Bp-Xor Codes for Hierarchically Distributed Matrix Multiplication(IEEE, 2022-03-01) Arslan, Şuayb ŞefikA novel fault-tolerant computation technique based on array Belief Propagation (BP)-decodable XOR (BP-XOR) codes is proposed for distributed matrix-matrix multiplication. The proposed scheme is shown to be configurable and suited for modern hierarchical compute architectures such as Graphical Processing Units (GPUs) equipped with multiple nodes, whereby each has many small independent processing units with increased core-to-core communications. The proposed scheme is shown to outperform a few of the well–known earlier strategies in terms of total end-to-end execution time while in presence of slow nodes, called stragglers. This performance advantage is due to the careful design of array codes which distributes the encoding operation over the cluster (slave) nodes at the expense of increased master-slave communication. An interesting trade-off between end-to-end latency and total communication cost is precisely described. In addition, to be able to address an identified problem of scaling stragglers, an asymptotic version of array BP-XOR codes based on projection geometry is proposed at the expense of some computation overhead. A thorough latency analysis is conducted for all schemes to demonstrate that the proposed scheme achieves order-optimal computation in both the sublinear as well as the linear regimes in the size of the computed product from an end-to-end delay perspective.Article Citation - WoS: 3Citation - Scopus: 3Exact Construction of Bs-Assisted Mscr Codes With Link Constraints(IEEE Communications Letters, 2022-02-01) Arslan, Şuayb ŞefikIt is clear that 5G network resources would be consumed by heavy data traffic owing to increased mobility, slicing, and layered/distributed storage system architecture. The problem is elevated when multiple node failures are repaired to address service quality requirements. Typical approaches include individual or cooperative data regeneration to efficiently utilize the available bandwidth. It is observed that storage systems of 5G and beyond technologies shall have a multi–layer architecture in which base stations (BS) would be present. Moreover, communication with each layer would be subject to various communication costs and link constraints. Under limited BS assistance and cooperation, the trade-off between storage per node and communication bandwidth has been established. In this trade–off, two operating points, namely minimum storage, and bandwidth regeneration are particularly important. In this study, we first identify the optimal number of BS use at the minimum storage regeneration point. An explicit code construction is provided subsequently for the exact minimum storage regeneration whereby each layer may help the repair process subject to a communication link constraint.Article Citation - WoS: 4Citation - Scopus: 6Data Repair-Efficient Fault Tolerance for Cellular Networks Using Ldpc Codes(IEEE, 2022-01-01) Haytaoglu, Elif; Kaya, Erdi; Arslan, Şuayb ŞefikThe base station-mobile device communication traffic has dramatically increased recently due to mobile data, which in turn heavily overloaded the underlying infrastructure. To decrease Base Station (BS) interaction, intra-cell communication between local devices, known as Device-to-Device, is utilized for distributed data caching. Nevertheless, due to the continuous departure of existing nodes and the arrival of newcomers, the missing cached data may lead to permanent data loss. In this study, we propose and analyze a class of LDPC codes for distributed data caching in cellular networks. Contrary to traditional distributed storage, a novel repair algorithm for LDPC codes is proposed which is designed to exploit the minimal direct BS communication. To assess the versatility of LDPC codes and establish performance comparisons to classic coding techniques, novel theoretical and experimental evaluations are derived. Essentially, the theoretical/numerical results for repair bandwidth cost in presence of BS are presented in a distributed caching setting. Accordingly, when the gap between the cost of downloading a symbol from BS and from other local network nodes is not dramatically high, we demonstrate that LDPC codes can be considered as a viable fault-tolerance alternative in cellular systems with caching capabilities for both low and high code rates.Conference Object Citation - WoS: 3Citation - Scopus: 3Data Repair in Bs-Assisted Distributed Data Caching(IEEE, 2020-10-05) Kaya, Erdi; Haytaoğlu, Elif; Arslan, Şuayb ŞefikIn this paper, centralized and independent repair approaches based on device-to-device communication for the repair of the lost nodes have been investigated in a cellular network where distributed caching is applied whose fault tolerance is provided by erasure codes. The caching mechanisms based on Reed-Solomon codes and minimum bandwidth regenerating codes are adopted. The proposed approaches are analyzed in a simulation environment in terms of base station utilization load during the repair process. Based on the intuitive assumption that the base station is usually more costly than device-to-device communication, the centralized repair approach demonstrates a better performance than the independent repair approaches on the number of symbols retrieved from the base station. On the other hand, the centralized approach has not achieved a dramatic reduction in the number of symbols downloaded from the other devices.Conference Object Citation - WoS: 1Citation - Scopus: 1Adaptive Boosting of Dnn Ensembles for Brain-Computer Interface Spellers(IEEE, 2021-06-09) Çatak, Yiğit; Aksoy, Can; Özkan, Hüseyin; Güney, Osman Berke; Koç, Emirhan; Arslan, Şuayb ŞefikSteady-state visual evoked potentials (SSVEP) are commonly used in brain computer interface (BCI) applications such as spelling systems, due to their advantages over other paradigms. In this study, we develop a method for SSVEP-based BCI speller systems, using a known deep neural network (DNN), which includes transfer and ensemble learning techniques. We test performance of our method on publicly available benchmark and BETA datasets with leave-one-subject-out procedure. Our method consists of two stages. In the first stage, a global DNN is trained using data from all subjects except one subject that is excluded for testing. In the second stage, the global model is fine-tuned to each subject whose data are used in the training. Combining the responses of trained DNNs with different weights for each test subject, rather than an equal weight, provide better performance as brain signals may differ significantly between individuals. To this end, weights of DNNs are learnt with SAMME algorithm with using data belonging to the test subject. Our method significantly outperforms canonical correlation analysis (CCA) and filter bank canonical correlation analysis (FBCCA) methods.Conference Object Citation - WoS: 2Citation - Scopus: 1Average Bandwidth-Cost Vs. Storage Trade-Off for Bs-Assisted Distributed Storage Networks(IEEE, 2021-06-09) Tengiz, Ayse Ceyda; Haytaoğlu, Elif; Pusane, Ali Emre; Arslan, Şuayb Şefik; Pourmandi, MassoudIn this study, we consider a hierarchically structured base station (BS)-assisted cellular system equipped with a backend distributed data storage in which nodes randomly arrive and depart the cell. We numerically motivate and characterize the fundamental trade-off between the average repair bandwidth cost versus storage space where BS communication cost (higher than that of local) and link capacity constraints exist while the number of failed nodes can vary dynamically. We establish the capacity region that is most relevant to 5G and beyond networks, which are layered by design. We hope that this study shall motivate novel regeneration code constructions that will be able to achieve the presented limits.Conference Object Fault-Tolerant Strassen-Like Matrix Multiplication(IEEE, 2020) Arslan, Şuayb Şefik; Güney, Osman B.; Oblokulov, MuhtashamIn this study, we propose a simple method for fault-tolerant Strassen-like matrix multiplications. The proposed method is based on using two distinct Strassen-like algorithms instead of replicating a given one. We have realized that using two different algorithms, new check relations arise resulting in more local computations. These local computations are found using computer aided search. To improve performance, special parity (extra) sub-matrix multiplications (PSMMs) are generated (two of them) at the expense of increasing communication/computation cost of the system. Our preliminary results demonstrate that the proposed method outperforms a Strassen-like algorithm with two copies and secures a very close performance to three copy version using only 2 PSMMs, reducing the total number of compute nodes by around 24% i.e., from 21 to 16.