Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 8Citation - Scopus: 16QoS-Aware LTE-A Downlink Scheduling Algorithm: A Case Study on Edge Users(Wiley, 2019-07-31) Uyan, Osman Gokhan; Gungor, Vehbi Cagri4G/LTE-A (Long-Term Evolution-Advanced) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high Internet speeds. It makes use of the OFDM technology to offer high speed and provides the system resources both in time and frequency domain. A scheduling algorithm running on the base station holds the allocation of these resources. In this paper, we investigate the performance of existing downlink scheduling algorithms in two ways. First, we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new QoS-aware fairness criterion, which accepts that the system is fair if it can provide the users with the network traffic speeds that they demand and evaluate the performance of the algorithms according to this metric. We also propose a new QoS-aware downlink scheduling algorithm (QuAS) according to these two metrics, which increases the QoS-fairness and overall throughput of the edge users without causing a significant degradation in overall system throughput when compared with other schedulers in the literature.Article Citation - WoS: 8Citation - Scopus: 10On the Performance of LTE Downlink Scheduling Algorithms: A Case Study on Edge Throughput(Elsevier, 2018-08) Deniz, Coskun; Uyan, O. Gokhan; Gungor, Vehbi CagriRadio resource allocation is a crucial task in the LTE networks. To increase the overall user experience, an efficient radio resource allocation algorithm should be utilized. In this work, a new scheduling algorithm has been proposed to increase the edge throughput without sacrificing system throughput. Comparative performance results indicate that the proposed scheduler increases the edge throughput and fairness while limiting degradation in the cell throughput between 0 to 2 percent with respect to the other schedulers.Article Citation - WoS: 177Citation - Scopus: 224A Smart Parking Lot Management System for Scheduling the Recharging of Electric Vehicles(IEEE-Inst Electrical Electronics Engineers Inc, 2015-11) Kuran, Mehmet Sukru; Viana, Aline Carneiro; Iannone, Luigi; Kofman, Daniel; Mermoud, Gregory; Vasseur, Jean P.; Carneiro Viana, AlineIn this paper, we propose a centralized electric vehicles (EVs) recharge scheduling system for parking lots using a realistic vehicular mobility/parking pattern focusing on individual parking lots. We consider two different types of EV based on their mobility/parking patterns: 1) regular EVs; and 2) irregular EVs. An extensive trace-based vehicular mobility model collected from the Canton of Zurich is used for the regular EVs, and a probabilistic pattern built on top of this trace is used for modeling the behavior of irregular EVs. To the extent of our knowledge, this is the first EV charging scheduling study in the literature that takes into account a realistic vehicular mobility pattern focusing on individual parking lots. We compare the performance of our proposed system with two well-known basic scheduling mechanisms, first come first serve and earliest deadline first, with regard to two objective functions: 1) maximizing the total parking lot revenue; and 2) maximizing the total number of EVs fulfilling their requirements. Comparison results show that our proposed system outperforms well-known basic scheduling mechanisms with regards to both objectives. Parking lots managing the recharging of a high number of EVs will greatly benefit from using such recharge scheduling systems in the context of smart cities.Book Part Citation - Scopus: 4A Bi-Criteria Approach to Scheduling in the Face of Uncertainty: Considering Robustness and Stability Simultaneously(Nova Science Publishers, Inc., 2014) Gören, Selçuk; Sabuncuoĝlu, Ihsan; Selcuk, GörenIt is possible to scrutinize impacts of uncertainty on schedules from two different perspectives. The flrst one has to do with the fact that schedules are required to main- tain high performance in the face of uncertainty. In other words, it is desired that their performances are insensitive to negative impacts of disruptions. We refer to this view- point as the robustness perspective. The second viewpoint is about another quality: when a schedule is executed in the shop floor, the realized schedule is required not to deviate much from its initial version. This is because many activities besides pro- duction are planned based on the production schedule. It is important that unforeseen disruptions affect the plans for these activities as little as possible. We refer to this viewpoint as the stability perspective. Even though a considerable body of literature has emerged on hedging schedules against the negative effects of unforeseen disrup- tions in the last two decades, few studies address the problem of scheduling under uncertainty from both the robustness and the stability perspectives at the same time. The nature of the relation between robustness and stability, the trade-off between them, the circumstances under which they conflict or reconcile need to be thoroughly inves- tigated. To this end, we propose a bi-criteria approach to simultaneously investigate the robustness and stability of production schedules. We consider proactive schedul- ing in a single machine environment with random processing times. We use the total expected flow time and the total variance of job completion times as the robustness and stability measures, respectively. The proposed o-constraint variants are exact methods to generate the set of all Pareto-optimal schedules. We also develop an algorithm to generate a flxed number (set by the decision-maker) of near-Pareto-optimal schedules to deflne the characteristics and the shape of the trade-off curve without generating the entire Pareto set. Our computational experiments indicate that the proposed algorithms are efflcient. © 2018 Elsevier B.V., All rights reserved.