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Dynamic capacity allocation control for resource sharing networks (RSN) is studied when the networks are in heavy traffic. The goal is to minimize an ergodic cost with a linear holding cost function. Our main result shows that the optimal cost associated with an associated Brownian control problem provides a lower bound for the asymptotic ergodic cost in the RSN for any sequence of control policies. A similar result for an infinite horizon discounted cost has been previously shown for general resource sharing networks in Budhiraja and Conroy (in Modeling, stochastic control, optimization, and applications, 2019) and for general 'unitary networks' in Budhiraja and Ghosh (Ann Appl Probab 16:1962–2006, 2006). The study of an ergodic cost criterion requires different ideas as bounds on ergodic costs only yield an estimate on the controls in a time-averaged sense which makes the time-rescaling ideas of Budhiraja and Conroy (in Modeling, stochastic control, optimization, and applications, 2019) and Budhiraja and Ghosh (Ann Appl Probab 16:1962–2006, 2006) hard to implement. Proofs rely on working with a weaker topology on the space of controlled processes that is more amenable to an analysis for the ergodic cost. As a corollary of the main result, we show that the explicit policies constructed in Budhiraja and Johnson (Math Oper Res 45:797–832, 2020; Ann Appl Probab 34:851–916, 2024) for general RSN are asymptotically optimal for the ergodic cost when the underlying cost per unit time has certain monotonicity properties. [ABSTRACT FROM AUTHOR]

In this article, we address the online resource allocation problem in service queuing systems under uncertainty. In particular, the optimal control policy is derived by using the real-time data, i.e., without fully knowing information about the system state. We employ the conditional value-at-risk to achieve the minimum long-run average cost subject to the constraints on the risk of instability. Then, we can ensure the service ability of the system at a high level under such on-the-fly uncertainty. We show that the proposed model naturally leads to a minmax saddle point optimization problem. We first present an intuitive offline primal–dual learning method, which can achieve a desirable convergence rate. Then, we further improve the algorithm by learning the optimal Lagrange multiplier concerning the instantaneous system state, i.e., online primal–dual learning algorithm, to achieve the same convergence rate as the offline algorithm. Besides, we demonstrate that the proposed method outperforms classical models in providing the lower average delay under uncertainty, which means it can improve the stability and provide a better quality of service under the ambiguity of uncertainty. A real case of inpatient bed allocation for hospital operations is presented to show the performance in applications. The results show that our model can reduce the average wait with certain total available beds under uncertain arrivals. [ABSTRACT FROM AUTHOR]

We study the well-posedness of a class of dynamical flow network systems describing the dynamical mass balance among a finite number of cells exchanging flow of traffic between themselves and with the external environment. Dynamical systems in the considered class are described as differential inclusions whereby the routing matrix is constant and the outflow from each cell in the network is limited by a control that is a Lipschitz continuous function of the state of the network. This framework finds application in particular within traffic signal control, whereby it is common that an empty queue can be allowed to have more outflow than vehicles in the queue. While models for this scenario have previously been presented for open-loop outflow controls, our result ensures the existence and uniqueness of solutions for the network flow dynamics in the case Lipschitz continuous feedback controllers. • A queuing network model with feedback that allows service to empty queues. • Prove existence and uniqueness of solutions when the controller is Lipschitz. • Show how dynamic flow propagation can be incorporated into the model. [ABSTRACT FROM AUTHOR]

Age of Information (AoI) is a critical metric for several Internet of Things (IoT) applications, where sensors keep track of the environment by sending updates that need to be as fresh as possible. The development of edge computing solutions has moved the monitoring process closer to the sensor, reducing the communication delays, but the processing time of the edge node needs to be taken into account. Furthermore, a reliable system design in terms of freshness requires the knowledge of the full distribution of the Peak AoI (PAoI), from which the probability of occurrence of rare, but extremely damaging events can be obtained. In this work, we model the communication and computation delay of such a system as two First Come First Serve (FCFS) queues in tandem, analytically deriving the full distribution of the PAoI for the M/M/1 – M/D/1 and the M/M/1 – M/M/1 tandems, which can represent a wide variety of realistic scenarios. [ABSTRACT FROM AUTHOR]

A real-world topological network consists of multiple entrances along its source nodes. Routing appropriate percentages of pedestrians from these entrances to the particular available routes with relevant arrival rates will improve the network's performance. This paper presents a framework for finding the optimal arrival rates of pedestrians from all available entrances and routes to downstream nodes maximising the network's throughput. The calculation of the arrival rates and movement directions is based on M/G/C/C analytical and simulation models and the network flow model and considers the real distances of the entrances along the source nodes. The framework was tested on the Tuanku Syed Putra Hall, Universiti Sains Malaysia, Malaysia. Extensive analyses of the performances of its available nodes especially on the achievable optimal throughputs were documented and discussed. Quantitative results show that the hall's throughput is optimised when pedestrians' arrival rates to all the available entrances and their movement directions are controlled within certain ranges. [ABSTRACT FROM AUTHOR]

We study a new multiple-lift compact automated parking system, which is a new technology with a circular structure using carousel equipped with the shuttles for the horizontal movement and multiple lifts equipped with the platforms for the vertical movement. This paper investigates dedicated and random shuttles operating policies. We divided the carousel into areas based on the number of lifts. We propose a dedicated shuttle operating policy under which each area shuttles can only serve one dedicated lift. A random shuttle operating policy under which shuttles can serve any lift. We get expected throughput time models for the two shuttle operating policies under the same system physical configurations based on queuing network models. We compare the analytical models with simulation models, and the results show that the proposed models provide accurate estimates. A numerical experiment is conducted to illustrate the trade-offs between dedicated shuttle and random shuttle operating policies. The results show that the retrieval time in random shuttle operating policy is larger than the retrieval time in dedicated shuttle operating policy. We also get the optimal system structure, including the number of the lifts. [ABSTRACT FROM AUTHOR]

Abstract The objective of this paper is to propose and then validate a new method for simulating molecular diffusion in a 3-D environment. Diffusion governing principles of Brownian motion have been discovered by Einstein and Smoluchowski. In a classical approach, diffusion is modeled using partial differential equations. However, solving those, even using numerical methods is usually time consuming, particularly in the case of an inhomogeneous environment. In this paper, we propose to use queueing networks to model diffusion of molecules as governed by Fick's law. The proposed model has been validated using the Kolmogorov-Smirnov test to compare results obtained from a simulation with theoretical standard deviations resulting from Einstein-Smoluchowski's approach. [ABSTRACT FROM AUTHOR]

In this paper we present a queuing network approach to the problem of routing and rebalancing a fleet of self-driving vehicles providing on-demand mobility within a capacitated road network. We refer to such systems as autonomous mobility-on-demand (AMoD) systems. We first cast an AMoD system into a closed, multi-class Baskett–Chandy–Muntz–Palacios (BCMP) queuing network model capable of capturing the passenger arrival process, traffic, the state-of-charge of electric vehicles, and the availability of vehicles at the stations. Second, we propose a scalable method for the synthesis of routing and charging policies, with performance guarantees in the limit of large fleet sizes. Third, we explore the applicability of our theoretical results on a case study of Manhattan. Collectively, this paper provides a unifying framework for the analysis and control of AMoD systems, which provides a large set of modeling options (e.g. the inclusion of road capacities and charging constraints), and subsumes earlier Jackson and network flow models. [ABSTRACT FROM AUTHOR]

Robotic compact storage and retrieval systems (RCSRS) have seen many implementations over the last few years. In such a system, the inventory items are stored in bins, organized in a grid. In each cell of the grid, a certain number of bins are stored on top of each other. Robots with transport and lifting capabilities move on the grid roof to transport bins between manual workstations and storage stacks. We estimate performance and evaluate storage policies of RCSRS, considering both dedicated and shared storage policies coupled with random and zoned storage stacks. Semi-open queuing networks (SOQNs) are built to estimate the system performance, which can handle both immediate and delayed reshuffling processes. We approximate the models by reduced SOQNs with two load-dependent service nodes and use the matrix-geometric method to solve them. Both simulations and a real case are used to validate the analytical models. Assuming a given number of stored products, our models can be used to optimize not only the length-to-width ratio of the system but also the stack height, depending on the storage strategy used. For a given inventory and optimal system configuration, we demonstrate that the dedicated storage policy outperforms the shared storage policy when the objective is to minimize dual command throughput time. However, from a cost perspective, with a maximum dual command throughput time as a constraint, we show that shared storage substantially outperforms dedicated storage. The annualized costs of dedicated storage are up to twice as large as those of shared storage, as a result of the larger number of storage positions required by dedicated storage and the relatively lower filling degree of storage stacks. The online appendix is available at https://doi.org/10.1287/trsc.2017.0786. [ABSTRACT FROM AUTHOR]

Consideration was given to the model of a queuing network with resource queuing systems—the multi-server systems with losses where servicing of the accepted customer occupies random volumes of resources with the given distribution function depending on the customer class and the type of required servicing. Customer servicing in a node can be interrupted by a signal arriving at an exponential time from the start of servicing, and during the time of customer sojourn in the network it may be interrupted more than once. Analytical formulas for calculation of the fundamental probability-time model characteristics—including the joint distribution functions of the number of customers in the nodes and the volumes of resources occupied by them—were proposed on the assumption of the Poisson flows incoming to the nodes and arbitrary servicing. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) utilisation is characterised by its dense deployment in order to fulfil the monitoring tasks. This density of communication leads to interference and congestion. In a previous work, a schedule scheme dubbed REFIACC (Reliable, Efficient, Fair and Interference Aware Congestion Control), that takes into account interferences and different links capacities in order to avoid packet loss due congestion, was proposed. REFIACC idea was validated using comparative simulations. In this study, REFIACC scheduling scheme was modelled using Markov chains. The modelling concerns queue length evolution and global system throughput. Different hypothesis details for queue length monitoring, according to application motivation, have led to many variants of models. The evaluation of the model using MATLAB has shown its effectiveness concerning packet reception ratio and reception overhead. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are autonomous wireless systems consists of a variety of collaborative sensor nodes forming a self-configuring network with or without any pre-defined infrastructure. The common challenges of a WSN are network connectivity, node mobility, energy consumption, data computation and aggregation at sensor nodes. In this paper we focus on intermittency in network connectivity due to mobility of sensor nodes. We propose a new mathematical model to capture a given entire WSN as is with intermittency introduced between the communication links due to mobility. The model involves open GI/ G/1/ N queuing networks whereby intermittency durations in communication links are captured in terms of mobility models. The analytical formulas for the performance measures such as average end-to-end delay, packet loss probability, throughput, and average number of hops are derived using the queuing network analyzer and expansion method for models with infinite- and finite-buffer nodes, respectively. For models with 2-state intermittency, we analyze the performance measures by classifying these models into three types: namely, model with intermittent reception, model with intermittent transmission and/or reception, and model with intermittent transmission. We extend the analysis to multi-state intermittency models. We demonstrate the gained insight of WSNs through extensive numerical results. [ABSTRACT FROM AUTHOR]

The analysis of a queue that serves batches of customers with a novel service policy is presented in this paper, showing that a closed steady-state distribution of the number of customers in the queue can be derived for a very general setting of its parameters. Two output processes are flowing out of this queue depending on the fact that single customers are removed from the queue upon completion of a service, or bulks of customers of a fixed size are departing from the queue at the completion of the service's. Based on the expression of the steady-state distribution which assumes a Poisson arrival process, specific parameter configurations are identified that make the queue quasi-reversible, depending on the output process of interest. Since quasi-reversible queues are very important in the context of product form queueing networks, these results have relevant impacts on their own as well as when considered as the basis for possible computationally efficient approximations. Comparisons among the results obtained for different parameter settings are provided using both stochastic order arguments and numerical experiments. Future research directions are proposed considering also the many practical applications of this model ranging from flexible manufacturing, to logistics, to transportation systems. [ABSTRACT FROM PUBLISHER]

Parallel and concurrent structures are widely used both as standalone components and as building blocks of larger systems. Efficient models of parallelism and concurrency are therefore necessary to understand the impact of parallelism in system performance. These models become more critical with the proliferation of adaptive systems that require solving a large number of performance models in a short amount of time to facilitate configuration decisions dynamically. This paper presents efficient response time approximations for parallel constructs modeled as fork and join queues. These approximations can be used by practitioners and performance engineers to quickly compare the performance of contending configurations. The contributions over previous work are twofold. First, this paper considers heterogeneous multiclass fork and join open and closed queuing networks. Second, the paper also presents models for fork and join where each class of jobs might fork to different queues in a probabilistic manner. [ABSTRACT FROM AUTHOR]

As an important component of flow type production systems, assembly lines are widely used from automotive, appliance to apparel industry. In this research, the aim is finding the optimum task assignment that minimizes the cycle time under the assumption that station quantities are constant which are described as Type-2 assembly lines. Stochastic assembly lines are considered in which task times are distributed according to a statistical distribution. A new algorithm which gives optimum solution using Constraint Programming and Queuing Network is proposed. In this algorithm, the possible combinations are determined by Constraint Programming, and then, the performance measures are evaluated by Queuing Network. The method is tested with several numerical experiments from literature and the applicability is confirmed. [ABSTRACT FROM AUTHOR]

In this paper we consider the variational problem in the non-negative orthant of ℝ. The solution of this problem gives the large deviation rate function for the stationary distribution of an SRBM (Semimartingal Reflecting Brownian Motion). Avram, Dai and Hasenbein (Queueing Syst. 37, 259-289, ) provided an explicit solution of this problem in the non-negative quadrant. Building on this work, we characterize reflective faces of the non-negative orthant of ℝ, we construct boundary influence cones and we provide an explicit solution of several constrained variational problems in ℝ. Moreover, we give conditions under which certain spiraling paths to a point on an axis have a cost which is strictly less than the cost of every direct path and path with two pieces. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical solution for reducing the mean number of the tasks waiting to be processed in a grid environment is proposed. The approach uses queuing theory and models the grid environment in the form of an open queuing network (QN). Applying the steady state analysis to the proposed QN and minimizing the mean number of waiting tasks within the grid environment, an equality and inequality system is obtained. Solving the equality and inequality system, subtasks arrival rates at each of the resources within the grid environment can be estimated. Applying the obtained subtasks arrival rates at each of the grid resources, the mean number of the waiting tasks in the grid environment could be minimized. To evaluate the results obtained from the proposed QN and provide a graphical representation of the grid environment a formal description of the environment in terms of generalized stochastic Petri nets (GSPNs) is presented. Steady state analyzing of the GSPN model and finding the subtask dispatching weights at each of the grid resources, subtask arrival rates can be estimated. Comparing the results obtained from two proposed approaches shows that the subtasks arrival rates achieved from QNs and GSPNs are the same. [ABSTRACT FROM AUTHOR]

Queuing networks present as beneficial models for a category of problems emerging in modern manufacturing systems. As the optimal control problem for queuing networks in familiar to be difficult, an important topic of research during the last two decades has been the growth of difficult estimations, and the use of these estimations to control optimal controls. Flexible moderations are an important class of such estimations that have received much consideration in recent years. The central objective of this paper is to determine the utilization of flexible moderations in solving a diversity of scheduling problems. In this paper, we investigate the role of flexible moderations in solving classic job shop problems. For the job shop problem with the objective of minimizing makespan, we build a schedule that is guaranteed to be within a consistent of the optimal. In other words, we examine the job shop scheduling problem with the aim of minimizing holding costs. Recent results show that for this objective, the job shop problem does not have a polynomial time estimation plan; consequently, in terms of approximability, this is a harder objective than the makespan. Our main result is an algorithm, based on regular relaxation that presents lateral optimal schedules. [ABSTRACT FROM AUTHOR]

This paper deals with decision making in a remanufacturing facility where returned products arrive according to a Poisson process. Arrivals have different routings among the facility stations since they have different defects and need different operations. A returned product is either accepted for remanufacturing or sold at a salvage value without working on it in order to reduce congestion. The authors provide an analytical model using a queuing network theory to obtain the best policy for accepting returned products. Furthermore, a continuous genetic algorithm is implemented to solve the model, which happens to be a mixed integer nonlinear programming problem. Several examples are solved by the implemented genetic algorithm and the results are evaluated. [ABSTRACT FROM AUTHOR]

Abstract: We present theoretical and numerical results for the performance of a multiprocessor network modeled as a ring and as a toroidal square lattice of nodes with local processors that generate messages for output ports/buffers. The output buffers are assumed to have infinite capacity, and the service time is deterministic. Two models are considered. One assumes that every processor generates messages with rate per time slot and per output port/buffer. The other model considers that the generation rate of a node depends on the intensity of the flow of arriving messages. Explicit expressions for the distribution of queue lengths, the average number of messages in the buffers, the average latency, and the critical network load depending on the distance between the source and the destination are obtained. Simulation results show excellent agreement with theoretical predictions based on the assumption of independent queues. [ABSTRACT FROM AUTHOR]

This note describes an importance sampling (IS) algorithm to estimate buffer overflows of stable Jackson networks with a tree topology. Three new measures of service capacity and traffic in Jackson networks are introduced and the algorithm is defined in their terms. These measures are effective service rate, effective utilization and effective service-to-arrival ratio of a node. They depend on the nonempty/empty states of the queues of the network. For a node with a nonempty queue, the effective service rate equals the node’s nominal service rate. For a node i with an empty queue, it is either a weighted sum of the effective service rates of the nodes receiving traffic directly from node i, or the nominal service rate, whichever smaller. The effective utilization is the ratio of arrival rate to the effective service rate and the effective service-to-arrival ratio is its reciprocal. The rare overflow event of interest is the following: given that initially the network is empty, the system experiences a buffer overflow before returning to the empty state. Two types of buffer structures are considered: (1) a single system-wide buffer shared by all nodes, and (2) each node has its own fixed size buffer. The constructed IS algorithm is asymptotically optimal, i.e., the variance of the associated estimator decays exponentially in the buffer size at the maximum possible rate. This is proved using methods from (Dupuis et al. in Ann. Appl. Probab. 17(4):1306–1346, ), which are based on a limit Hamilton–Jacobi–Bellman equation and its boundary conditions and their smooth subsolutions. Numerical examples involving networks with as many as eight nodes are provided. [ABSTRACT FROM AUTHOR]

Introduce the Class-oriented Method of Moments (CoMoM), a new exact algorithm to compute performance indexes in closed multiclass queuing networks. Closed models are important for performance evaluation of multitier applications, but when the number of service classes is large, they become too expensive to solve with exact methods such as Mean Value Analysis (MVA). CoMoM addresses this limitation by a new recursion that scales efficiently with the number of classes. Compared to the MVA algorithm, which recursively computes mean queue lengths, CoMoM also carries on in the recursion information on higher-order moments of queue lengths. We show that this additional information greatly reduces the number of operations needed to solve the model and makes CoMoM the best-available algorithm for networks with several classes. We conclude the paper by generalizing CoMoM to the efficient computation of marginal queue-length probabilities, which finds application in the evaluation of state-dependent attributes such as quality-of-service metrics. [ABSTRACT FROM AUTHOR]

Abstract: Importance sampling (IS) is a variance reduction method for simulating rare events. A recent paper by Dupuis, Wang and Sezer [Paul Dupuis, Ali Devin Sezer, Hui Wang, Dynamic importance sampling for queueing networks, Annals of Applied Probability 17 (4) (2007) 1306–1346] exploits connections between IS and stochastic games and optimal control problems to show how to design and analyze simple and efficient IS algorithms for various overflow events of tandem Jackson Networks. The present paper carries out a program parallel to the paper by Dupuis et al. for a two node tandem network whose arrival and service rates are modulated by an exogenous finite state Markov process. The overflow event we study is the following: the number of customers in the system reaches without the system ever becoming empty, given that initially the system is empty. [Copyright &y& Elsevier]

Abstract: In a supply chain organized as a network of autonomous enterprises, the main objective of each partner is to optimize his production and supply policy with respect to his own economic criterion. Conflicts of interests and the distributed nature of the decision structure may induce a global loss of efficiency. Contracts can then be used to improve global performance and decrease risks. The purpose of the paper is to evaluate the efficiency of different types of contracts between the industrial partners of a supply chain. Such an evaluation is made on the basis of the relationship between a producer facing a random demand and a supplier with a random lead-time. The model combines queuing theory for evaluation aspects and game theory for decisional purposes. [Copyright &y& Elsevier]

Abstract: Queuing network contains a series of service facilities (in our case, culture tanks or ponds), at some or all of which, a customer (fish) must receive service; it is, therefore, necessary to study the entire network. A culture tank or pond can be seen as a queuing system in which neither a queue (“over-holding” of fish in tank A before being moved to tank B), nor an idle pond is allowed, and arrival and departure rates are equal. The entire farm can be seen as a queuing network. A queuing model for optimizing the management parameters of a recirculating aquaculture system was developed. The model validity was statistically tested and was not rejected within the 95% confidence level, therefore, the model can be useful for both research and practical applications. The model aims to optimize: (1) the system layout, (2) the fish batch arrival frequency, (3) the number of fingerlings in a batch, (4) the number of days in each culture tank, and (5) grading criteria along the production lines. Under our local farm conditions we found that: the “2, 4, 8 layout” was a superior layout; the optimal operating parameters were: arrival of a batch every 36 days; 72 days at the nursery stage (up to 25 g); followed by 144 days (up to 200 g) at each successive growth phase. The optimal values maintain biomass density criterion of 80 kg m−3 and tank utilization criterion of never below 99%. [Copyright &y& Elsevier]

Circulant matrices possess unusual and interesting properties. These properties have been exploited to obtain the transient solution in closed form for a circulant queuing network that models a distributed query processing system. The sojourn time of a customer in the circulant queuing network is determined. A semi-Markov generalisation of this network is also studied. [Copyright &y& Elsevier]

According to the static locking concurrency control policy, transactions which have predeclared their locks can only be activated when they have acquired all requested locks. Lock contention results in transaction blocking, such that only a subset of V transactions available for processing can be active. We develop an analytic solution method based on recursion to compute performance measures of interest for static locking systems. The probability of lock conflict is computed approximately by noting that the mean number of active transactions encountered by a blocked transaction is that of a system with V - 1 transactions. Transactions delay before activation is determined by the mean number of times it is checked unsuccessfully for activation (e( V )) and the mean elapsed time between these instants. It is shown that the mean number of active transactions is V/(1 + η(V)), where η is the ratio of the mean residual residence time of a transaction in the system and its mean residence time. It follows that the variability in transaction residence time, in addition to lock contention, has an adverse effect on performance. Based on the locking requirements of transactions, five database access models are considered: 1) a fixed number of exclusive locks, 2) a variable number of exclusive locks, 3) shared in addition to exclusive lock requests, 4) query and update transactions, 5) nonuniform database accesses in which transactions access objects in different database domains. Numerical results obtained by the analytical solution are validated against simulation results and shown to be quite accurate. They are also used to gain insight into the behavior of static locking systems. These insights are summarized at the end of the paper. [ABSTRACT FROM AUTHOR]

Multiclass queuing network models of multiprogramming computer systems are frequently used to predict the performance of computing systems as a function of user workload and hardware con- figuration. This paper examines three different methods for incorporating operating system overhead in multiclass queuing network models. The goal of the resultant model is to provide an accurate account of the processing performance and the system CPU overhead of each of the several different types of jobs (batch, timesharing, transaction processing, etc.) that together make up the multiprogramming workload. The first method introduces an operating system workload consisting of a fixed number of jobs to represent system CPU overhead processing. The second method extends the jobs' CPU service requests to include explicitly the CPU overhead necessary for system processing. The third method employs a communicating set of user and system job classes so that the CPU overhead can be modeled by switching jobs from user to system class whenever they require system CPU service. The capabilities and accuracy of the three methods are assessed and compared against performance and overhead data measured on a Univac 1110 computer. Two prediction studies reveal that the method of class changing presents the most reliable model for predicting the performance of user and system workload processing. [ABSTRACT FROM AUTHOR]

A periodic network is a queuing network whose steady-state behavior is not constant in time, but repeats itself in a cycle. This behavior may be caused by the introduction of periodic servers, e.g., paging drums. The model presented is a generalization of some other models of queuing networks, and provides a more general definition of steady-state behavior. A theoretical solution is presented. Examples of theoretical and approximate solutions are presented for a well-known queuing network model of a computer system. [ABSTRACT FROM AUTHOR]

This paper considers a computer configuration design problem. The computer system is modeled by a closed queuing network. The system throughput is the objective function to be maximized and the speed of the devices axe the decision variables, A rich class of non-linear cost functions is considered. It is shown that any local optimum of the optimization problem is also a global optimum. it is also shown that the cost constraint is active and that the method of Lagrange multipliers van be used to solve the problem efficiently. [ABSTRACT FROM AUTHOR]