Reservation Requests Research Articles

Outright fit resource allocation approach for advance reservation requests in elastic optical networks

Elastic optical networks (EONs) are a promising technology for the next-generation optical network, and advanced reservation (AR) applications have been growing expeditiously over the past few years. Thus, the routing and spectrum allocation problem for AR requests has become a significant concern. This paper proposes an approach named outright fit advanced resource reservation to improve the spectral resource allocation efficiency for AR connection requests. Our proposed approach works in two stages: The proposed resource reservation strategy first uses an outright fit resource allocation strategy to reserve the spectral resource for a connection request within the absolute best service window and leaves adequate spectral resources for subsequent requests. If a connection request cannot get resources in the first stage, the proposed optimal rescheduling technique then is applied to serve the request. Our proposed optimal rescheduling technique uses spectrum shifting and reallocation without altering the routing paths, and its optimal characteristic decreases the number of rescheduling operations, thereby decreasing the rescheduling computational complexity and cost, which improves the network’s quality of service. Moreover, this rescheduling approach increases the opportunities for successful rescheduling of the requests without inducing many spectrum fragments, significantly reducing the blocking probability. The simulation results illustrate that the proposed approach can considerably enhance the blocking performance and obtains high spectrum utilization.

Progress in regional PV power forecasting: A sensitivity analysis on the Italian case study

The increasing penetration of PV generation, driven by climate strategies and objectives, calls for accurate production forecasting to mitigate the negative effects associated with inherent variability, such as overgeneration, grid instability, supplementary reserve request. The regional PV power forecasting is crucial for Transmission and Distribution system operators for a better management of energy flows. In this work many aspects of regional PV power forecasting are investigated, by means of a comparison of six different forecasting models applied to predict the hourly production of the following days on six Italian bidding zones for one year. In particular, the work shows that the forecasting accuracy is mainly affected by the algorithm and its pre and post processing, with a range of 30% in performance accuracy, while it is less impacted by the forecasting horizon. It has been verified that the accuracy in the irradiation prediction, used in input to the power forecasting algorithm, has less impact compared to single plants. The work confirms the performance improvement which can be obtained by increasing the size of the area to which the prediction refers, through a comparison between the forecasting at bidding zone and national level. Finally, we show that the larger the controlled forecast area, the smaller the impact on the forecast accuracy due to the non-uniform spatial and capacity distribution of the PV fleet. This means that as the size of the region increases, the average irradiance progressively becomes the best PV power predictor. We refer to this phenomenon as: “input smoothing effect".

Optimal Pricing and Overbooking of Reservations

We study the optimal design of reservations for a firm with limited capacity. The firm faces a random number of customers, each of whom has a random valuation for service. The reservation policy has two components: pricing and overbooking. For the former, the firm charges a reservation fee (at the time of reservation) and a service price (at the time of service). For the latter, the firm imposes a booking limit that caps the number of reservations it sells. Given the firm's reservation policy, customers make reservations in advance and later decide whether to show up. Denying service to reservation holders is costly. We obtain the following equilibrium results. First, when demand is small relative to capacity, the firm's pricing structure relies on reservation fees prepaid in advance, but when demand is large relative to capacity, it relies on payment received upon service. Second, when demand is low and/or predictable, the firm accepts all reservation requests, but when demand is high and/or variable, the firm uses a booking limit.

Evaluating the Impacts of Optimization Horizon on the Shared Autonomous Vehicle Reservation Request System

With the development of technology, shared autonomous vehicles may become one of the main traffic modes in the future. Especially, shared autonomous vehicle reservation system, commuting, and other trips with fixed departure time mostly submit their travel requests in advance. Therefore, it is important to reasonably match shared autonomous vehicles and reservation demands. In this paper, reservation requests are divided into short-term and long-term requests by inputting requests in a more realistic way. An integer linear programming model considering operator scheduling cost and system service level is established. A detailed scheme considering rolling horizon continuity and ridesharing is used to improve the dispatching result. Based on traffic data in Delft, the Netherlands, 164 scenarios are tested in which the parking cost, fuel cost, ridesharing effect, service level, and network size are analyzed. The results show that a better relocation and ridesharing matching scheme can be obtained when the rolling horizon is small, while the overall effect is better when the rolling horizon is large. Moreover, the buffer time, distance, and travel time limit for vehicle relocation should be selected according to the request quantity and the calculation time requirement. The result can provide a suggestion for the dispatching of shared autonomous vehicle reservation system with ridesharing.

Fragmentation-Aware Routing and Spectrum Allocation Algorithm for Immediate Reservation Requests in Elastic Optical Networks

Fragmentation-Aware Routing and Spectrum Allocation Algorithm for Immediate Reservation Requests in Elastic Optical Networks

Providing QoS to High Performance Distributed Applications in Software-Defined Networks (SDNs)

Nowadays, there is an ever-increasing number of applications that have strict quality of service (QoS) requirements. The ability to define QoS requirements in traditional networks is limited due to the complex control of these environments. Modification of the existing infrastructure has high administrative costs, since the subsystem of each service component must have its resources managed by a centralized organization to guarantee users the level of QoS that each of them requires. The specification of quality of service (QoS) requirements in traditional networks is limited by the high administrative cost of these environments. Nevertheless, newer network paradigms, as Software-Defined Networks (SDNs), simplify and relaxes the management of networks. In this sense, SDN can provide a simple/effective way to develop QoS provisioning. This approach allows the specification of classes of service and also negotiates the QoS requirements between applications and the SDN network controller. The SDN controller, in turn, monitors the network and adjusts its performance through resource reservation and traffic prioritization. Have developed a QoS provision architecture for high performance distributed applications exploiting the capabilities of SDN. In this architecture, simple software components enable a process of message exchanging that includes reservation request and reservation confirmation. This procedure allows a network controller to configure QoS queues to individual packet flows. The developed a proof-of-concept of proposal and experimental results show that the additional routines present low overhead, whereas – for a given test application — observes a reduction of up to 47% in transfer times. Despite the specific scenario evaluated, results indicate our solution feasibility. Future works include the development of renegotiation and adaptation functions.

Dynamic routing, modulation, and spectrum assignment based on fuzzy logic control in elastic optical networks.

Considering the constantly changing network resources and randomly generated spectrum fragmentation problem, a dynamic routing, modulation, and spectrum assignment based on the fuzzy logic control (RMSA-FLC) algorithm is proposed in this paper. A fuzzy logic control (FLC) system based on the degree of fragmentation optimization and the degree of link selection is constructed. The path-control weight (PW) is achieved as the output of the FLC system, and the path and spectrum allocation scheme with the maximum PW is selected for the immediate reservation requests. The simulation results show that the proposed RMSA-FLC algorithm can effectively reduce the blocking probability and improve the spectrum resource utilization in a dynamic elastic optical network.

Offering strategy of a price-maker virtual power plant in energy and reserve markets

This paper deals with the offering strategy of a virtual power plant (VPP) that participates in the energy and reserve electricity markets. The VPP under consideration includes diverse electricity assets, such as a flexible demand, a conventional generating unit, a renewable generating unit, and a storage unit. The VPP behaves as a price-maker player and determines its offering decisions one day in advance. The decision-making problem is, therefore, highly influenced by different sources of uncertainties, including the renewable production levels, the up/down reserve request coefficients, and the up/down reserve energy prices, all of which are represented using a number of scenarios. The problem is formulated using a stochastic bi-level model. The objective of the upper-level problem is to maximize the expected profit of the VPP while meeting the technical limitations of the units in the VPP for the realization of each scenario. The lower-level problem represents the clearing of the energy and reserve markets and provides the market prices. The stochastic bi-level model is converted into a mathematical program with equilibrium constraints by replacing the equilibrium solutions of the market clearing problems with their equivalent first-order optimality conditions. The results of a realistic case study verify the performance of the proposed approach and show that the VPP can increase its profit by behaving as a price-maker agent in the energy and reserve markets.

Design of a Decision-Based Multicriteria Reservation System for the EV Parking Lot

In metropolitans, the problem of finding available parking slots has changed as finding available parking slots having charging stations due to increasing electric vehicle (EV) deployment. Smart management systems can be used in this manner for obtaining an optimum parking slot in EV parking lots (PLs) considering EV users’ preferences. This article proposes a smart reservation system considering the behavior of EV users, parking slot availability (PSA), state-of-charge (SoC) value of EVs, and PL usage history of EV users. In order to handle weighting the behavior of EV users according to a comprehensive criteria comparison, the analytical hierarchy process (AHP) from multicriteria decision-making (MCDM) techniques is used in the smart reservation system. Thereafter, the proposed ranking function is presented to develop the mentioned quality-of-experience (QoE)-based charging slot allocation considering the reservation requests of EV users sent via a mobile application and to accept the optimal EVs in accordance with the weights assigned by AHP. The proposed concept is tested under different cases generated by changing the individual importance degree of EV user’s criteria. The different case studies demonstrate the effectiveness of the proposed decision-based multicriteria reservation system in terms of EV users’ acceptance ratio. Simulation results show that not only the importance degree related to the EV users’ criteria has an important effect in accepting appropriate EV users but also PSA management is another vital criterion especially in peak-load hours.

The Use of Business Process Management in Hotel Direct Sales Improvement

This article deals with Business Process Modelling and Reengineering use in the hospitality industry, focusing on the improvement of direct telephone sales by application of the CRM system. After modelling the current state of the selected process using ARIS methodology, the same process was remodelled for the application of the CRM system. This application shortened the whole process (mainly the number of activities needed to prosecute) and allowed the front-office employee to be more clients oriented. The automation of labour-intensive processes can reduce the number of human-caused errors and improve the convertibility and reservation request and their overall value.

An Efficient and Secure Certificate-Based Access Control and Key Agreement Scheme for Flying Ad-Hoc Networks

The evolution of Flying Ad-hoc Networks (FANETs) marks the paradigm shift from a single large drone to multiple small drones linked together in an ad-hoc fashion. To maintain the Quality of Service (QoS) in the multi-hop networking schema, FANETs utilize the available resources efficiently. However, due to open wireless boundary and high mobility of the drones, the FANETs are vulnerable to malicious nodes that can penetrate the network and, thus, pose serious security threats, particularly at the Medium Access Control (MAC) layer. Such susceptibility compromises the network security and privacy and harms the information exchange operation within the network. The attacker can either transmit a large number of reservation requests to waste the bandwidth, listen to the control messages, conduct power-efficient jamming or falsify the information to manipulate the network control. Therefore, secure access control and a key agreement mechanism are required. The mechanism must utilize the two phases, i.e., node authentication and key agreement, to counter the aforementioned attacks. Our contribution, in this paper, is a certificate-based access control and key agreement scheme, which is based on the technique of Hyperelliptic Curve Cryptography (HECC) and employs a collision-resistant one-way cryptographic hash function. In order to assess the viability and performance of the proposed scheme, we analyze it using formal security analysis techniques, such as the Real-Or-Random (ROR) model and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The scheme is also evaluated using the informal security analysis technique, or the non-mathematical approach. The results obtained from both analyses affirm the superiority of our proposed scheme.

Around the World in 50 Restaurants

Around the World in 50 Restaurants

Temporal and Spectral 2D Fragmentation-Aware RMSA Algorithm for Advance Reservation Requests in EONs

In this paper, we explore the problem of routing, modulation and spectrum assignment (RMSA) for advance reservation (AR) requests in elastic optical networks (EONs), with the objective to further reduce the blocking probability and improve the spectrum utilization. On the one hand, we propose a minimum resource consumption routing policy (MRC) for leaving more free resources for future requests. On the other hand, we introduce a two-dimensional (2D) path resource model, in which each AR request can be transformed into a rectangle block whose length and width are related to request bandwidth and request duration respectively. Therefore, the spectrum assignment problem of AR requests is simplified to the two-dimensional rectangle packing problem. Furthermore, we design several factors to evaluate the two-dimensional fragmentation caused by a rectangle packing operation, where we consider the fragmentation situation in the rectangle block neighborhood for the first time. Based on these factors, we propose a two-dimensional fragmentation-aware spectrum assignment strategy (2D-FA). Through the combination of MRC and 2D-FA, we propose a novel RMSA algorithm named MRC-2D-FA for dynamically provisioning AR requests in EONs. Simulation results show that MRC-2D-FA can achieve lower bandwidth blocking probability and higher spectrum utilization compared with several well-performed benchmark algorithms.

Transfusion needs in patients admitted for fracture of femur

ObjectiveTo determine the variables and predictive factors associated with the administration and frequency of the allogenic blood transfusion (ABT) on patients diagnosed with fracture of femur requiring surgical intervention. The secondary objective was to describe the frequency and quantity of ABT on those patients. MethodA retrospective transversal observational study was performed on patients admitted to the Sagrat Cor hospital of Barcelona with a diagnosis of fractured femur that required surgical intervention in 2016. Several demographic variables were gathered along with the clinical data and outcome of transfused and non-transfused patients, including the type of fracture. ResultsThe overall sample was 257 patients. Of the patients studied, 52.9% required blood transfusion support. Patients who required ABT had haemoglobin values on admission of 11.01 gr/dl while those that did not require transfusion had an average value of 12.97 gr/dl.Of the patients, 42.8% were on anticoagulant and/or antiplatelet therapy before the fracture occurred. ConclusionsMore than half the patients admitted for fracture of femur received blood transfusion. The data collected showed that the hospital transfusion policy offered satisfactory results. Factors associated with the need for ABT were haemoglobin levels (Hb) on admission and the type of fracture. Age and ASA risk (classification system of the American Society of Anesthesiologists) were also risk factors for ABT. This information could be useful for blood saving protocols. Finally, we think that it is important that all patients that are hospitalised with a diagnosis of fracture of femur and require surgery have a blood reserve request made, given that a high percentage of them, at any time during their stay, will be transfused.

RoomTetris: an optimal procedure for committing rooms to reservations in hotels

RoomTetris: 酒店中极佳分房程序研究目的很多酒店, 特别是私人、家庭经营型、或者精品酒店, 在客人预定后立刻分派指定的房间给客人。这往往是因为独立房间售卖（没有特殊房型概念）或者因为客人在预定时, 工作人员手动指派房间, 亦或者是因为预订系统与渠道管理系统链接, 直接在预定后指派房间号。这种早期的分派程序是不优化的, 往往在酒店住房率高的时候, 会造成一些不必要的房间预定失败, 继而带来的利润损失。本论文旨在研究不同房间指派参数配置, 包括最优系统（RoomTetris）, 使得酒店达到更高住房率的同时产生高利润。研究设计/方法/途径本论文采用理论讨论和实验等研究方法, 并展示了提出的RoomTetris参数的最优性。本论文还将其参数放在不同的情景中做实验, 以显示其提高酒店针对随机或者次优化分派的最佳启发式策略中的住房率。研究结果研究结果表明智能型分派参数能够大大降低预定失败率（预定需求不能符合酒店房型供给）, 并且提高住房率和利润。住房时间并不是必须的参数, 极具个性化服务, 比如让客人选房间号, 可能导致利润损失（因为最优房间分派无法实现）, 房型的设计也应该参与到最优房间分派的效果中来。研究理论限制/启示预定取消和超额预定的情况也应该加入到分析中来。第二种对于拥有不止一种房型的酒店来说, 可能增加房间分派的情况在于为客人升级房型, 这样可以将客人转到其他适合房型以解决房间分派问题。此外, 更复杂系统兼容财务管理系统应该被考量, 有的时候, 房间的成本取决于客人的数量。研究实践启示由于最优算法的住房率区别在于旺季和高预定时段, 也就是高房间价格和高预定量, 本论文提出的最佳算法将提高主要财务指标, 比如RevPAR（平均客房收益）。由于房间分配系统可以完全实现自动化, 那么采用智能分派系统无疑是有效酒店管理中的优质选择。研究原创性/价值据作者所知, 此文章是首篇关于此类话题的研究优质算法（且被证实其最佳）。

A Survey of Minimum Wavelength Conversion Routing and Wavelength Assignment in WDM Networks

Generally, research on routing and wavelength task over wavelength directed WDM networks is worried about immediate reservation (IR) requests. An IR demand typically does not specify a holding time for data transmission and the start time of the data transmission are assumed to be immediate (i.e. when the connection request arrives). The idea of advance reservation (AR) has as of recently been picking up consideration for optical networks. An AR request commonly determines data about the beginning of the information transmission or a cutoff time, just as the holding time of the transmission. AR has a few significant applications for both wide-region networks and Grid networks. For instance, AR can be utilized for modifying virtual geographies to adjust to predictable peak hour traffic use. It very well may be utilized to give high- bandwidth transmission administrations, for example, video conferencing and in Grid applications requiring the booked circulation of enormous records and for co-allotment of organization and grid assets. AR can likewise be advantageous to the organization by permitting the organization administrator to more readily design asset use and accordingly increment use. Information on the holding time can prompt more ideal choices for asset distribution. This translates to better quality of service for users. In this paper we give a complete study of the past and current work on booking ahead of time for optical organizations. There have been numerous varieties of the advance reservation of time idea proposed, so we will likewise give an expansive grouping. Notwithstanding the review, we will examine what we accept are significant regions of future work and open difficulties for early booking on optical organizations. Keywords: Advance reservation, scheduled demands, WDM, survey, wavelength-routed, and RWA

Intelligent and Flexible Bandwidth Scheduling for Data Transfers in Dedicated High-Performance Networks

High-demanding transfers of extremely large amounts of data have been increasingly supported by the bandwidth reservation services in dedicated high-performance networks (HPNs). To use the bandwidth reservation service, a user needs to initialize a bandwidth reservation request (BRR) containing parameters and requirements of the bandwidth reservation or data transfer, such as the time interval. Upon receiving one BRR, existing researches and bandwidth reservation service providers return either the best-case bandwidth reservation (BR) or a reject message if not all the BRR requirements can be satisfied. In this paper, we study the intelligent and flexible bandwidth scheduling of two common types of BRRs: direct bandwidth reservation and indirect bandwidth reservation (data transfer). When not all the requirements of the first type can be satisfied, instead of a direct reject message, we identify and return two alternative BRs made within the closest time intervals before and after the user-specified time interval; for the second type, besides the above two alternative BRs, we also identify and return the alternative BR made within the closest time interval crossing the user-specified time interval. For each problem, we design a flexible bandwidth scheduling algorithm with rigorous optimality proofs to compute both the best-case and alternative BRs. For comparison, we also design two heuristic algorithms adapted from existing bandwidth scheduling algorithms. We then conduct extensive simulations to compare their overall performance, and the simulation results show that the proposed optimal algorithms have superior performance to those in comparison. To the best of our knowledge, our work in this paper is among the first to study intelligent and adaptive bandwidth scheduling with alternative BRs in HPNs.

Approximate dynamic programming for stochastic resource allocation problems

A stochastic resource allocation model, based on the principles of Markov decision processes &#x0028 MDPs &#x0029 , is proposed in this paper. In particular, a general-purpose framework is developed, which takes into account resource requests for both instant and future needs. The considered framework can handle two types of reservations &#x0028 i.e., specified and unspecified time interval reservation requests &#x0029 , and implement an overbooking business strategy to further increase business revenues. The resulting dynamic pricing problems can be regarded as sequential decision-making problems under uncertainty, which is solved by means of stochastic dynamic programming &#x0028 DP &#x0029 based algorithms. In this regard, Bellman’s backward principle of optimality is exploited in order to provide all the implementation mechanisms for the proposed reservation pricing algorithm. The curse of dimensionality, as the inevitable issue of the DP both for instant resource requests and future resource reservations, occurs. In particular, an approximate dynamic programming &#x0028 ADP &#x0029 technique based on linear function approximations is applied to solve such scalability issues. Several examples are provided to show the effectiveness of the proposed approach.

RMSA algorithm for malleable-reservation requests in elastic optical networks

Abstract Elastic optical networking is a promising technology for the next generation of optical core networks and the routing, modulation and spectrum assignment (RMSA) problem is one of its key issues. The RMSA problems for immediately reservation (IR) and advance reservation (AR) requests have been widely researched. Malleable reservation (MR) requests are another kind of important traffics in elastic optical networks (EONs). However, the RMSA problem for MR requests has not been well considered. In this paper, we investigate the RMSA problem for MR requests in EONs and propose an algorithm named Min-RRD. The algorithm assigns frequency-time blocks with the minimum sum of three indexes, namely number of used resources ( R used ), number of impacted resources ( R impacted ) and distance to corner ( D corner ), to MR requests. Simulation results show that the proposed algorithm has a lower blocking probability and a smaller delay than the existing algorithm. Hence, it is a well-performed RMSA algorithm.

Static resource allocation of advanced reservation requests in elastic optical networks.

Considering the flexibility characteristic of advanced reservation (AR) requests, the problem of static routing, modulation, spectrum, and time assignment (RMSTA) of AR requests in elastic optical networks is studied in this paper, in order to deploy the spectrum resource economically and enable more requests to be served. The multi-objective integer linear program (ILP) model, which can minimize the maximum utilized frequency and time slot indices as well as find a trade-off between them, is used to formulate the RMSTA problem. Then the proportion optimal RMSTA (PO-RMSTA) heuristic algorithm with three sorting strategies is proposed to get the sub-optimal solutions. The PO-RMSTA algorithm and sorting strategies, ascending order of elastic time (AET), descending order of data volume (DDV), and ascending order of alternative schemes (AAS), are simulated in our work and proved to obtain the approximate optimal solutions. The sorting policy AET achieved the best performance when minimizing the maximum utilized frequency slot index, whereas the sorting policy DDV worked best when minimizing the maximum utilized time slot index. As for the compromise between two indices, both AET and AAS provided satisfying results.