Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940

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Author: search.filters.author.Arslan, Şuayb ŞefikPublication Index: search.filters.publicationIndex.Scopus

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Now showing 1 - 10 of 27
  • Article
    Citation - WoS: 12
    Citation - Scopus: 20
    Compress-Store on Blockchain: a Decentralized Data Processing and Immutable Storage for Multimedia Streaming
    (Springer, 2022-03-25) Arslan, Şuayb Şefik; Turguy, Göker; Goker, Turguy
    Decentralization for data storage is a challenging problem for blockchain-based solutions as the blocksize plays a key role for scalability. In addition, specific requirements of multimedia data call for various changes in the blockchain technology internals. Considering one of the most popular applications of secure multimedia streaming, i.e., video surveillance, it is not clear how to judiciously encode incentivization, immutability, and compression into a viable ecosystem. In this study, we provide a genuine scheme that achieves this encoding for a video surveillance application. The proposed scheme provides a novel integration of data compression, immutable off-chain data storage using a new consensus protocol namely, Proof-of-WorkStore (PoWS) in order to enable fully useful work to be performed by the miner nodes of the network. The proposed idea is the first step towards achieving greener application of a blockchain-based environment to the video storage business that utilizes system resources efficiently.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Array Bp-Xor Codes for Hierarchically Distributed Matrix Multiplication
    (IEEE, 2022-03-01) Arslan, Şuayb Şefik
    A 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: 3
    Citation - Scopus: 3
    Exact Construction of Bs-Assisted Mscr Codes With Link Constraints
    (IEEE Communications Letters, 2022-02-01) Arslan, Şuayb Şefik
    It 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: 4
    Citation - Scopus: 6
    Data Repair-Efficient Fault Tolerance for Cellular Networks Using Ldpc Codes
    (IEEE, 2022-01-01) Haytaoglu, Elif; Kaya, Erdi; Arslan, Şuayb Şefik
    The 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: 3
    Citation - Scopus: 3
    Data Repair in Bs-Assisted Distributed Data Caching
    (IEEE, 2020-10-05) Kaya, Erdi; Haytaoğlu, Elif; Arslan, Şuayb Şefik
    In 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: 1
    Citation - Scopus: 1
    Adaptive 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 Şefik
    Steady-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: 2
    Citation - Scopus: 1
    Average 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, Massoud
    In 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.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 7
    On the Distribution Modeling of Heavy-Tailed Disk Failure Lifetime in Big Data Centers
    (IEEE, 2021-06-01) Arslan, Şuayb Şefik; Zeydan, Engin
    It has become commonplace to observe frequent multiple disk failures in big data centers in which thousands of drives operate simultaneously. Disks are typically protected by replication or erasure coding to guarantee a predetermined reliability. However, in order to optimize data protection, real life disk failure trends need to be modeled appropriately. The classical approach to modeling is to estimate the probability density function of failures using nonparametric estimation techniques such as kernel density estimation (KDE). However, these techniques are suboptimal in the absence of the true underlying density function. Moreover, insufficient data may lead to overfitting. In this article, we propose to use a set of transformations to the collected failure data for almost perfect regression in the transform domain. Then, by inverse transformation, we analytically estimated the failure density through the efficient computation of moment generating functions, and hence, the density functions. Moreover, we developed a visualization platform to extract useful statistical information such as model-based mean time to failure. Our results indicate that for other heavy-tailed data, the complex Gaussian hypergeometric distribution and classical KDE approach can perform best if the overfitting problem can be avoided and the complexity burden is overtaken. On the other hand, we show that the failure distribution exhibits less complex Argus-like distribution after performing the Box–Cox transformation up to appropriate scaling and shifting operations.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 7
    Founsure 1.0: an Erasure Code Library With Efficient Repair and Update Features
    (Elsevier, 2021-01-01) Arslan, Şuayb Şefik
    Founsure is an open-source software library that implements a multi-dimensional graph-based erasure coding entirely based on fast exclusive OR (XOR) logic. Its implementation utilizes compiler optimizations and multi-threading to generate the right assembly code for the given multi-core CPU architecture with vector processing capabilities. Founsure possesses important features that shall find various applications in modern data storage, communication, and networked computer systems, in which the data needs protection against device, hardware, and node failures. As data size reached unprecedented levels, these systems have become hungry for network bandwidth, computational resources, and average consumed power. To address that, the proposed library provides a three-dimensional design space that trades off the computational complexity, coding overhead, and data/node repair bandwidth to meet different requirements of modern distributed data storage and processing systems. Founsure library enables efficient encoding, decoding, repairs/rebuilds, and updates while all the required data storage and computations are distributed across the network nodes.
  • Article
    Citation - WoS: 13
    Citation - Scopus: 22
    Advancements in Distributed Ledger Technology for Internet of Things
    (Elsevier, 2020-03-01) Jurdak, Raja; Arslan, Şuayb Şefik; Krishnamachari, Bhaskar; Jelitto, Jens
    Internet of Things (IoT) is paving the way for different kinds of devices to be connected and properly communicated at a mass scale. However, conventional mechanisms used to sustain security and privacy cannot be directly applied to IoT whose topology is increasingly becoming decentralized. Distributed Ledger Technologies (DLT) on the other hand comprise varying forms of decentralized data structures that provide immutability through cryptographically linking blocks of data. To be able to build reliable, autonomous and trusted IoT platforms, DLT has the potential to provide security, privacy and decentralized operation while adhering to the limitations of IoT devices. The marriage of IoT and DLT technology is not very recent. In fact many projects have been focusing on this interesting combination to address the challenges of smart cities, smart grids, internet of everything and other decentralized applications, most based on blockchain structures. In this special issue, the focus is on the new and broader technical problems associated with the DLT-based security and backend platform solutions for IoT devices and applications.