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Today the science communities are facing the issue of having diverse, distributed, and large volumes of data that is a big challenge to access and move over Wide Area Networks (WAN) while using standard utilities. The challenges include heterogeneity of data storage end-systems, non-interoperable data transfer protocols, highly fluctuating shared network links, frequent network outages, difficulty in optimally setting the tunable transfer parameters, accurate prediction of data delivery time, the reliability and security of the file transfers, efficient use of end-system and network resource, fairness of all users accessing the same set of resources, and hiding all of these complexities from the end users. As the need for remote data access and transfer grows, so does the impact of these issues on the science communities who depend on these data sets for their research. OneDataShare (ODS) is a cloud-hosted managed file transfer service that aims to overcome these challenges. It provides (1) optimization of end-to-end data transfers and reduction of the time to delivery of the data; (2) interoperation across heterogeneous data resources and on-the-fly inter-protocol translation; (3) an intuitive web interface that makes file transfer and monitoring very easy from any device and location; and (4) a reliable and secure file transfer service which is open source and free-to-use to democratize access to data. ODS was initially developed as a monolithic Java ODS was initially developed as a monolithic Java application that contained all of its features as a SaaS user could experience [2]. The proposed SaaS architecture could not accommodate users installing the Transfer-Service (TS) on their hosts to enable direct access to the file system and get around low-privileged users. The benefit of this is the ability to deploy the Transfer-Service on the users’ hosts giving it direct access to the file system and more efficient utilization of system resources for the user’s data transfers, as it connects to the ODS back-end and uses the monitoring and optimization service. To address the above challenges, ODS pivoted to a micro-services-based architecture that focuses on maximizing the throughput of heterogeneous file transfers, real-time thread tuning depending on end systems resources usage, retry capabilities, and providing encryption at rest and in transit for all credentials.

Volume 2022, Issue 18, Aufgrund steigender Dynamik und Heterogenität in der Produktion sind auch die Anforderungen an die Intralogistik und im speziellen an Lagersysteme gestiegen. Lagersysteme müssen flexibel sein und einen hohen Durchsatz ermöglichen. Diese Anforderungen werden durch Shuttlesysteme erfüllt. Damit der Durchsatz von Shuttlesystemen softwarebasiert weiter gesteigert werden kann, wurden Konzepte entwickelt, welche mit Deep Reinforcement Learning (DRL) die Blockaden, welche z. B. beim Gassenwechsel oder bei mehreren Auslagerungen in einer Gasse auftreten, durch eine genänderte Auslagerungsreihenfolge minimieren. Die bisher entwickelten Konzepte betrachten ausschließlich eine sehr kleine Anzahl an Lagerplätzen. Reale Shuttlesysteme verfügen teilweise über mehrere tausend Lagerplätze pro Ebene. Daher wird in diesem Beitrag ein DRLKonzept entwickelt, welches in einem realen Shuttlesystem die Auslagerungsreihenfolge anpasst, um durch eine Minimierung der Blockaden eine Durchsatzsteigerung zu erreichen., Due to increasing dynamics and heterogeneity in production, the demands on intralogistics and especially on storage systems have increased. Storage systems must be flexible and enable a high throughput. These requirements are fulfilled by shuttle systems. To be able to increase the throughput of shuttle systems on a software basis, concepts have been developed that use Deep Reinforcement Learning (DRL) to minimise the blockages that arise, e.g. when changing gears or when several withdrawals are made in one gear, by changing the retrieval sequence. These concepts only consider a very small number of storage locations. Real shuttle systems sometimes have several thousand storage locations per level. Therefore, this paper develops a DRL concept that adapts the retrieval sequence in a real shuttle system to minimise blockades and increase throughput.

A significant number of processing cores in any many-core systems nowadays and likely in the future have to be switched off or forced to be idle to become dark cores, in light of ever increasing power density and chip temperature. Although these dark cores cannot make direct contributions to the chip's throughput, they can still be allocated to applications currently running in the system for the sole purpose of heat dissipation enabled by the temperature gradient between the active and dark cores. However, allocating dark cores to applications tends to add extra waiting time to applications yet to be launched, which in return can have adverse implications on the overall system performance. Another big issue related to dark core allocation stems from the fact that application characteristics are prone to undergo rapid changes at runtime, making a fixed dark core allocation scheme less desirable. In this paper, a runtime dark core allocation and dynamic adjustment scheme is thus proposed. Built upon a dynamic programming network (DPN) framework, the proposed scheme attempts to optimize the performance of currently running applications and simultaneously reduce waiting times of incoming applications by taking into account both thermal issues and geometric shapes of regions formed by the active/dark cores. The experimental results show that the proposed approach achieves an average of 61% higher throughput than the two state-of-the-art thermal-aware runtime task mapping approaches, making it the runtime resource management of choice in many-core systems.

This paper studies a full-duplex symbiotic radio network, where a full-duplex access point (FAP) transmits downlink orthogonal frequency division multiplexing signals to a legacy user (LU) and simultaneously receives signals backscattered from multiple passive backscatter devices (BDs) with capability of radio-frequency energy harvesting. A non-orthogonal-multiple-access enhanced dynamic-time-division-multiple-access (NOMA-DTDMA) transmission scheme is proposed to exploit the channel dynamics and further improve the spectrum efficiency. In order to maximize the throughput performance and ensure BD fairness, we maximize the minimum throughput among all BDs by jointly optimizing the FAP's subcarrier power allocation, the BDs' backscatter time allocation and power reflection coefficients, subject to the LU's throughput requirement, the BDs' harvested energy requirements, and other practical constraints. An efficient iterative algorithm is proposed to solve the formulated non-convex problem, by utilizing the block coordinated descent and successive convex optimization techniques. The convergence and complexity of the proposed algorithm are also analyzed. Numerical results show that the proposed NOMA-DTDMA scheme significantly outperforms the benchmark scheme of dynamic TDMA in terms of both throughput performance and BD fairness. Also, the trade-off performances between the BDs' throughput and the LU's throughput requirement as well as the BDs' harvested energy requirements are numerically verified.

The semiconductor etch cluster facility is the most used facility platform in the semiconductor manufacturing process. Optimizing cluster facilities can depend on production schedules and can have a direct impact on productivity. According to the diversity of semiconductor processes, the complexity of optimization is also increasing. Various optimization methods have been studied in many papers for optimizing such a complex cluster facility. However, there is a lack of discussion of how these methods can apply to practical semiconductor manufacturing fabs and the actual performance results. Even now, data analysis and optimal parameter derivation for maximizing the productivity of cluster manufacturing in semiconductor manufacturing fabs are continuing. In this study, we propose an automated method for data collection and analysis of the cluster, which used to be done manually. In addition, the derivation of optimization parameters and application to facilities are addressed. This automated method could improve the manual analysis methods, such as simulation through data analysis using machine learning algorithms. It could also solve the inefficiency caused by manual analysis performed within the network inside the semiconductor manufacturing fabs.

Networks based on IEEE 802.11 standard are one of the main options for deployment in industrial environment. Degradation of throughput in congested networks and short-term unfairness are well-known drawbacks of 802.11 DCF and similar MAC protocols. Those shortcomings represent significant limitation in forecasted growth of wireless usage. This is especially important in industrial wireless networks (IWN) where the scalability of wireless MAC is one of the main requirements. In this paper, a novel self-adapting MAC protocol (SaMAC) is defined and mathematically modeled. SaMAC employs constrained countdown freezing enhanced with shifted window mechanism. As a result, the protocol outperforms 802.11 DCF standard as well as shifted contention window (SCW) and constrained countdown freezing (CPCF) protocols in achieved throughput, fairness, and jitter, while keeping simple implementation. Despite protocol’s simple design, it is shown that its mathematical model is extremely complex. For proposed protocol, the assumption of constant contention loss probability, which is normally used for modeling of MAC schemes, does not hold. In the presented multidimensional Markov chain model, a unique iterative method for determining contention loss probability is developed as well as a method for throughput calculation based on such a chain. Accuracy of the presented model is verified in several network scenarios. Considering the performance of the proposed protocol, authors believe that it could be of benefit to deploy it in heavily loaded wireless networks with timing constraints, such as IWNs.

In Long Range Wide Area Network (LoRaWAN), the data rate of the devices can be adjusted to optimize the throughput by changing the spreading factor. However, the adaptive data rate has to be carefully utilized because the collision probability, which directly affects the throughput, is changed according to the use of spreading factors. Namely, the greater the number of devices using the same spreading factor, the greater the probability of collision, resulting in a decrease of total throughput. Nevertheless, in the current system, the only criteria to determine the data rate to be adjusted is a link quality. Therefore, contention-aware adaptive data rate should be designed for the throughput optimization. Here, the number of devices which can use a specific data rate is restricted, and accordingly the optimization problem can be regarded as constrained optimization. To find an optimal solution, we adopt the gradient projection method. By adjusting the data rate based on the retrieved set of optimal data rate, the system performance can be significantly improved. The numerical results demonstrate that the proposed method outperforms the comparisons regardless of the number of devices and is close to the theoretical upper bound of throughput.

This paper investigates the trade-off between throughput and energy consumption in heterogeneous networks with dual connectivity and backhaul delay. The problem of traffic splitting between the main eNB and secondary eNBs is formulated as a multi-objective optimization problem. Based on some observations, assumptions, and subsequent simplifications, two algorithms are devised. One targets throughput optimization (TO) by transmission delay minimization. The other one does energy savings (ES) by not transmitting on the main eNB depending on the delay allowance defined in the QoS criterion of the transmitted data. The main eNB is in control of the data transfer to the secondary eNB. Simulations show that the TO algorithm performs slightly better than an earlier published algorithm in which the secondary eNBs are in control of the data transfer from the main eNB. The ES algorithm does save energy at the expense of a larger transmission delay.

Cataloged from PDF version of article. Thesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2017. Includes bibliographical references (leaves 62-66). The importance of wireless networking schemes originating from ALOHA has rapidly risen with the wide-spread use of Internet, advancements in the communications systems and increasing number of wireless devices. Internet-of-Things and machine-to-machine communications concepts have drawn further attention to ALOHA since it is a low-complexity protocol. However, the classical ALOHA is not e cient and cannot handle massive number of users in an e cient manner. Therefore, many improvements have been proposed for over the years. Irregular Repetition Slotted ALOHA (IRSA) is an advanced ALOHA protocol in which each user sends a variable number of copies of their packets in each xed length medium access control (MAC) frame. The collisions may be resolved via successive interference cancellation (SIC) using the copies that are received cleanly. In this way, asymptotic throughputs close to the maximum normalized throughput value of one on the collision channel may be achieved. In this thesis, to reap the bene ts of IRSA for energy harvesting sensor networks, we propose an IRSA based uncoordinated random access scheme for energy harvesting (EH) nodes. Speci cally, we consider the case in which each user has a nite-sized battery which is recharged in a probabilistic manner in each slot with harvested energy from the environment. We analyze this scheme by deriving asymptotic throughput expressions, and obtain optimized probability distributions for the number of packet replicas for each user. We demonstrate that the optimized distributions perform considerably better than those of slotted ALOHA (SA), contention resolution diversity slotted ALOHA (CRDSA) and plain IRSA which do not take into account EH for both asymptotic and nite frame length scenarios. by Umut Demirhan. M.S.

The MAC layer of the 802.11 standard, based on the CSMA/CA mechanism, specifies a set of parameters to control the aggressiveness of stations when trying to access the channel. However, these parameters are statically set independently of the conditions of the WLAN (e.g. the number of contending stations), leading to poor performance for most scenarios. To overcome this limitation previous work proposes to adapt the value of one of those parameters, namely the CW, based on an estimation of the conditions of the WLAN. However, these approaches suffer from two major drawbacks: i) they require extending the capabilities of standard devices or ii) are based on heuristics. In this paper we propose a control theoretic approach to adapt the CW to the conditions of the WLAN, based on an analytical model of its operation, that is fully compliant with the 802.11e standard. We use a Proportional Integrator controller in order to drive the WLAN to its optimal point of operation and perform a theoretic analysis to determine its configuration. We show by means of an exhaustive performance evaluation that our algorithm maximizes the total throughput of the WLAN and substantially outperforms previous standard-compliant proposals. European Community's Seventh Framework Program The work described in this article has been partially supported by the European Community’s Seventh Framework Programme under the ICT FP7 Integrated Project CARMEN (INFSO-ICT-214994) and by the Spanish Government under the POSEIDON project (TSI2006-12507-C03). Publicado

This study considers a production cell consisting of two machines and a material handling robot. The robot has a buffer space that moves with it. Identical parts are to be produced repetitively in this flowshop environment. The problem is to determine the cyclic schedule of the robot moves that maximizes the throughput rate. After developing the necessary framework to analyze such cells, we separately consider the single-, double-, and infinite-capacity buffer cases. For single- and double-capacity cases, consistent with the literature, we consider one-unit cycles that produce a single part in one repetition. We compare these cycles with each other and determine the set of undominated cycles. For the single-capacity case, we determine the parameter regions where each cycle is optimal, whereas for the double-capacity case, we determine efficient cycles and their worst-case performance bounds. For the infinite-capacity buffer case, we define a new class of cycles that better utilizes the benefits of the buffer space. We derive all such cycles and determine the set of undominated ones.We perform a computational study where we investigate the benefits of robots with a buffer space and the effects of the size of the buffer space on the performance. We compare the performances of self-buffered robots, dual-gripper robots, and robots with swap ability.

This study considers a production cell consisting of two machines and a material handling robot. The robot has a buffer space that moves with it. Identical parts are to be produced repetitively in this flowshop environment. The problem is to determine the cyclic schedule of the robot moves that maximizes the throughput rate. After developing the necessary framework to analyze such cells, we separately consider the single-, double-, and infinite-capacity buffer cases. For single- and double-capacity cases, consistent with the literature, we consider one-unit cycles that produce a single part in one repetition. We compare these cycles with each other and determine the set of undominated cycles. For the single-capacity case, we determine the parameter regions where each cycle is optimal, whereas for the double-capacity case, we determine efficient cycles and their worst-case performance bounds. For the infinite-capacity buffer case, we define a new class of cycles that better utilizes the benefits of the buffer space. We derive all such cycles and determine the set of undominated ones.We perform a computational study where we investigate the benefits of robots with a buffer space and the effects of the size of the buffer space on the performance. We compare the performances of self-buffered robots, dual-gripper robots, and robots with swap ability.

In this paper, we study cyclic production for throughput optimization in robotic flow-shops. We are focusing on simple production cycles. Robotic cells can have a linear or a circular layout: most classical results on linear cells cannot be extended to circular cells, making it difficult to quantify the potential gain brought by the latter configuration. Moreover, though the problem of finding the best one part production cycle is polynomial for linear cells, it is NP-hard for circular cells. We consider the special case of circular balanced cells. We first consider three basic production cycles, and focus on one which is specific to circular cells, for which we establish the expression of the cycle time. Then, we provide a counterexample to a classical conjecture still open in this configuration. Finally, based on computational experiments, we make a conjecture on the dominance of a family of cycle, which could lead to a polynomial algorithm for finding the best 1-cycle for circular balanced cells.

Large-scale software development companies delivering market-driven products have introduced agile methodologies as the way of working to a big extent. Even though there are many benefits with an agile way of working, problems occur when scaling agile because of the increased complexity. One explicit problem area is to evolve deep product knowledge, which is a domain specific knowledge that cannot be developed anywhere else but at the specific workplace. This research aims to identify impediments for developing domain specific knowledge and provide solutions to overcome these challenges in order to optimize knowledge growth and throughput. The result of the research shows that impediments occur in four different categories, based on a framework for knowledge sharing drivers. These are people-related, task-related, structure-related and technology-related. The challenging element with knowledge growth is to integrate the training into the feature development process, without affecting the feature throughput negatively. The research also shows that by increasing the knowledge sharing, the competence level of the whole organization can be increased, and thereby be beneficial from many perspectives, such as feature-throughput and code quality.

In this paper we state a general framework for radio resource allocation based on a matrix which highlights the trade-offs of complexity and efficiency. This framework is outlined for the systematic definition of scheduling algorithms that are jointly adaptive to traffic and to transmission quality in order to improve the radio resource utilization and the achievable throughput of cellular networks for the support of best-effort traffic. We consider the application of the matrix concept to both time division and code division multiple access, the latter scheme also bringing about mutual interference among competing users. Then we propose a scheduling algorithm for wireless systems, called channel adaptive open scheduling (CHAOS). The CHAOS performance in terms of throughput and delay is extensively compared with those resulting from a load adaptive channel independent scheduling (CIS). A major result of this work is the quantitative assessment of the performance advantage allowed by jointly accounting for traffic congestion and transmission quality. Moreover the main implementation issues related to the proposed algorithms are investigated.

The popularity of the wireless networks is so great that we will soon reach the point where most of the devices work based on that, but new challenges in wireless channel access will be created with these increasingly widespread wireless communications. Multi-channel CSMA protocols have been designed to enhance the throughput of the next generation wireless networks compared to single-channel protocols. However, their performance analysis still needs careful considerations. In this thesis, a set of techniques are proposed to model and analyse the CSMA protocols in terms of channel sensing and channel access. In that respect, the performance analysis of un-slotted multi-channel CSMA protocols is studied through considering the hidden terminals. In the modelling phase, important parameters such as shadowing and path loss impairments are being considered. Following that, due to the high importance of spectrum sensing in CSMA protocols, the Double-Threshold Energy Detector (DTED) is thoroughly investigated in this thesis. An iterative algorithm is also proposed to determine optimum values of detection parameters in a sensing-throughput problem formulation. Vehicle-to-Roadside (V2R) communication, as a part of Intelligent Transportation System (ITS), over multi-channel wireless networks is also modelled and analysed in this thesis. In this respect, through proposing a novel mathematical model, the connectivity level which an arbitrary vehicle experiences during its packet transmission with a RSU is also investigated.

In this article, we consider the goal of achieving high throughput in a wireless sensor network. Our work is set in the context of those wireless sensor network applications which collect and transfer bulk data. We present PIP (Packets in Pipe), a MAC primitive for use by the transport module to achieve high throughput. PIP has a unique set of features: (a) it is a multihop connection-oriented primitive, (b) it is TDMA based, (c) it uses multiple radio channels, and (d) it is centrally controlled. This represents a significant shift from prior MAC protocols for bulk data transfer. PIP has several desirable properties: (a) its throughput degrades only slightly with increasing number of hops, (b) it is robust to variable wireless error rates, (c) it performs well even without any flow control, and (d) requires only small queue sizes to operate well. We substantiate these properties with a prototype implementation of PIP on the Tmote-Sky CC2420-based platform. PIP achieves about eleven times better throughput than the state-of-the-art prior work, over a network depth of 24 hops. We also show that PIP can be interagted with duty cycling, and that PIP can support streaming data from/to flash at little overhead.

In this thesis, we propose a protocol for dynamic reconfiguration of ad-hoc wireless networks with movable base stations in presence of obstacles. Hosts are assigned to base stations according to a probabilistic throughput function based on both the quality of the signal and the base station load. In order to optimize space coverage, base stations cluster hosts using a distributed clustering algorithm. Obstacles may interfere with transmission and obstruct base stations and hosts movement. To overcome this problem, we perform base stations repositioning making use of a motion planning algorithm on the visibility graph based on an extension of the bottleneck matching technique. We implemented the protocol on top of the NS2 simulator as an extension of the AODV. We tested it using both Random Way Point and Reference Point Group mobility models properly adapted to deal with obstacles. Experimental analysis shows that the protocol ensures the total space coverage together with a good throughput on the realistic model (Reference Point Group) outperforming both the standard AODV and DSR. Results of this thesis have been published in the journal Ad-Hoc Net-works, Elsevier.

In this paper, we propose a protocol for dynamic reconfiguration of ad-hoc wireless networks with movable base stations in presence of obstacles. Hosts are assigned to base stations according to a probabilistic throughput function based on both the quality of the signal and the base station load. In order to optimize space coverage, base stations cluster hosts using a distributed clustering algorithm. Obstacles may interfere with transmission and obstruct base stations and hosts movement. To overcome this problem, we perform base stations repositioning making use of a motion planning algorithm on the visibility graph based on an extension of the bottleneck matching technique. We implemented the protocol on top of the NS2 simulator as an extension of the AODV. We tested it using both Random Way Point and Reference Point Group mobility models properly adapted to deal with obstacles. Experimental analysis shows that the protocol ensures the total space coverage together with a good throughput on the realistic model (Reference Point Group) outperforming both the standard AODV and DSR.

ISSN 1976-5541 (Online) Understanding and optimizing the energy consumption of wireless devices is critical to maximize the network lifetime and to provide guidelines for the design of new protocols and interfaces. In this work, we first provide an accurate analysis of the energy performance of an IEEE 802.11 WLAN, and then we derive the configuration to optimize it. We further analyze the impact of the energy configuration of the stations on the throughput performance, and we discuss under which circumstances throughput and energy efficiency can be both jointly maximized and where they constitute different challenges. Our findings are that, although an energy-optimized configuration typically yields gains in terms of throughput as compared against the default configuration, it comes with a reduction in performance as compared against the maximum-bandwidth configuration, a reduction that depends on the energy parameters of the wireless interface. TRUE pub

Proceedings of: 6th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2009 and 3rd International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications, AAA-IDEA 2009, Las Palmas, Gran Canaria, November 23-25, 2009 Understanding and optimizing the energy consumption of wireless devices is critical to maximize network lifetime and to provide guidelines for the design of new protocols and interfaces. In this work we first provide an accurate analysis of the energy performance of an IEEE 802.11 WLAN, and then we derive the configuration to maximize it. We also analyze the impact of the energy configuration of the device on the throughput performance, and discuss in which circumstances throughput and energy efficiency can be both maximized and where they constitute different challenges. European Community's Seventh Framework Program Publicado

International audience; Annealing effects onto the reflow of imprinted resist patterns have been investigated on 250 nm dense line arrays printed with standard hot embossing lithography and thermoplastic polymer. Atomic force microscopy measurements were performed to point out the annealing temperature and time effects, respectively. The reflow velocity with respect to annealing temperature has been determined. Its variation is ascribed to both resist dynamic viscosity and surface free energy. Our approach demonstrated that imprint cycle time could be significantly reduced by saving cooling down time.

Cloud computing promises easy access, low entry cost and elasticity. However, elastic service provisioning is usually delivered via service replication, which must be supervised manually, hand-picking the services to replicate and ensuring their proper load balance. Automated service provisioning, i.e., the function of automatically scaling the services to cope up with their runtime demand, is a research challenge in cloud computing. In this work, we include such scalability analysis early in its development cycle, right at the design stage. We propose a model-driven approach where various QoS parameters can be simulated and analyzed using the e-Motions tool. Additionally, the model is automatically transformed to fit the given throughput requirements by replicating the services which cause the bottleneck. In order to evaluate the proposal, we present some initial experimental results run over the e-Motions tool. Ministerio de Ciencia e Innovación TIN2008-05932 Ministerio de Ciencia e Innovación TIN2008-031087 Ministerio de Ciencia e Innovación TIN2011-23795 Ministerio de Ciencia e Innovación TIN2012-35669 Junta de Andalucía P11-TIC-7659

Robotic cells are serial production systems that consist of a number of machines and a material handling robot that transfers parts between the machines. Energy consumption of a robot during its move between two machines can be decreased by carefully selecting its speed. This paper presents models and algorithms that make robot speed and robot activity sequencing decisions together for a dual-gripper robot that can handle two parts simultaneously. We consider both robot energy consumption and cycle time objectives so that a decision maker can observe the trade off between energy cost and throughput rate of the system, and select the best solution among alternatives. Computational experiments demonstrate that proposed approaches can generate efficient solutions for practical size instances, and speed control can significantly conserve energy.