Showing papers on "Static routing published in 2018"

Segment Routing Architecture

Abstract: Segment Routing (SR) leverages the source routing paradigm. A node steers a packet through an ordered list of instructions, called segments. A segment can represent any instruction, topological or service-based. A segment can have a semantic local to an SR node or global within an SR domain. SR allows to enforce a flow through any topological path while maintaining per-flow state only at the ingress nodes to the SR domain. Segment Routing can be directly applied to the MPLS architecture with no change on the forwarding plane. A segment is encoded as an MPLS label. An ordered list of segments is encoded as a stack of labels. The segment to process is on the top of the stack. Upon completion of a segment, the related label is popped from the stack. Segment Routing can be applied to the IPv6 architecture, with a new type of routing header. A segment is encoded as an IPv6 address. An ordered list of segments is encoded as an ordered list of IPv6 addresses in the routing header. The active segment is indicated by the Destination Address of the packet. The next active segment is indicated by a pointer in the new routing header.

On Removing Routing Protocol from Future Wireless Networks: A Real-time Deep Learning Approach for Intelligent Traffic Control

Abstract: Recently, deep learning has appeared as a breakthrough machine learning technique for various areas in computer science as well as other disciplines. However, the application of deep learning for network traffic control in wireless/heterogeneous networks is a relatively new area. With the evolution of wireless networks, efficient network traffic control such as routing methodology in the wireless backbone network appears as a key challenge. This is because the conventional routing protocols do not learn from their previous experiences regarding network abnormalities such as congestion and so forth. Therefore, an intelligent network traffic control method is essential to avoid this problem. In this article, we address this issue and propose a new, real-time deep learning based intelligent network traffic control method, exploiting deep Convolutional Neural Networks (deep CNNs) with uniquely characterized inputs and outputs to represent the considered Wireless Mesh Network (WMN) backbone. Simulation results demonstrate that our proposal achieves significantly lower average delay and packet loss rate compared to those observed with the existing routing methods. We particularly focus on our proposed method's independence from existing routing protocols, which makes it a potential candidate to remove routing protocol(s) from future wired/ wireless networks.

Unicast QoS Routing Algorithms for SDN: A Comprehensive Survey and Performance Evaluation

Abstract: A variety of communication networks, such as industrial communication systems, have to provide strict delay guarantees to the carried flows. Fast and close to optimal quality of service (QoS) routing algorithms, e.g., delay-constrained least-cost (DCLC) routing algorithms, are required for routing flows in such networks with strict delay requirements. The emerging software-defined networking (SDN) paradigm centralizes the network control in SDN controllers that can centrally execute QoS routing algorithms. A wide range of QoS routing algorithms have been proposed in the literature and examined in individual studies. However, a comprehensive evaluation framework and quantitative comparison of QoS routing algorithms that can serve as a basis for selecting and further advancing QoS routing in SDN networks is missing in the literature. This makes it difficult to select the most appropriate QoS routing algorithm for a particular use case, e.g., for SDN controlled industrial communications. We close this gap in the literature by conducting a comprehensive up-to-date survey of centralized QoS routing algorithms. We introduce a novel four-dimensional (4D) evaluation framework for QoS routing algorithms, whereby the 4D correspond to the type of topology, two forms of scalability of a topology, and the tightness of the delay constraint. We implemented 26 selected DCLC algorithms and compared their runtime and cost inefficiency within the 4D evaluation framework. While the main conclusion of this evaluation is that the best algorithm depends on the specific sub-space of the 4D space that is targeted, we identify two algorithms, namely Lagrange relaxation-based aggregated cost (LARAC) and search space reduction delay-cost-constrained routing (SSR+DCCR), that perform very well in most of the 4D evaluation space.

A Machine Learning-Based Protocol for Efficient Routing in Opportunistic Networks

Abstract: This paper proposes a novel routing protocol for OppNets called MLProph, which uses machine learning (ML) algorithms, namely decision tree and neural networks, to determine the probability of successful deliveries. The ML model is trained by using various factors such as the predictability value inherited from the PROPHET routing scheme, node popularity, node's power consumption, speed, and location. Simulation results show that MLProph outperforms PROPHET+, a probabilistic-based routing protocol for OppNets, in terms of number of successful deliveries, dropped messages, overhead, and hop count, at the cost of small increases in buffer time and buffer occupancy values.

Routing, spectrum, and core assignment in SDM-EONS with MCF: node-arc ILP/MILP methods and an efficient XT-aware heuristic algorithm

Abstract: In this paper, we focus on the static routing, spectrum, and core assignment (RSCA) problem in spacedivision multiplexing (SDM)-based elastic optical networks (EONs) with multi-core fiber (MCF). In RSCA problems, it is a challenging task to control the inter-core interference, called inter-core crosstalk (XT), within an acceptable level and simultaneously maximize the spectrum utilization. We first consider XT in a worst interference scenario (i.e., XTunaware), which can simplify the RSCA problem. In this scenario, we formulate the RSCA problem using a nodearc- based integer linear programming (ILP) method in which the numbers of both variables and constraints are greatly reduced compared with previous ILP methods, thereby leading to a significant improvement in convergence efficiency. Then, we consider the XT strictly (i.e., XT-aware) and formulate the problem using a mixed integer linear programming (MILP) method, which is an extension of the above node-arc-based ILP method. It is more suitable for different XT thresholds and/or geographically large networks, in that it has a higher degree of generalizability. Finally, we propose an XT-aware-based heuristic algorithm. The simulation results demonstrate that our heuristic algorithm achieves higher spectrum efficiency, higher degree of generalizability, and higher computational efficiency than the existing heuristic algorithm(s).

Energy-Aware Dual-Path Geographic Routing to Bypass Routing Holes in Wireless Sensor Networks

Abstract: Geographic routing has been considered as an attractive approach for resource-constrained wireless sensor networks (WSNs) since it exploits local location information instead of global topology information to route data. However, this routing approach often suffers from the routing hole (i.e., an area free of nodes in the direction closer to destination) in various environments such as buildings and obstacles during data delivery, resulting in route failure. Currently, existing geographic routing protocols tend to walk along only one side of the routing holes to recover the route, thus achieving suboptimal network performance such as longer delivery delay and lower delivery ratio. Furthermore, these protocols cannot guarantee that all packets are delivered in an energy-efficient manner once encountering routing holes. In this paper, we focus on addressing these issues and propose an energy-aware dual-path geographic routing (EDGR) protocol for better route recovery from routing holes. EDGR adaptively utilizes the location information, residual energy, and the characteristics of energy consumption to make routing decisions, and dynamically exploits two node-disjoint anchor lists, passing through two sides of the routing holes, to shift routing path for load balance. Moreover, we extend EDGR into three-dimensional (3D) sensor networks to provide energy-aware routing for routing hole detour. Simulation results demonstrate that EDGR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared to other geographic routing protocols in WSNs over a variety of communication scenarios passing through routing holes. The proposed EDGR is much applicable to resource-constrained WSNs with routing holes.

The multi-depot electric vehicle location routing problem with time windows

Abstract: Article history: Received October 27 2016 Received in Revised Format December 22 2016 Accepted February 27 2017 Available online March 1 2017 In this paper, the Multi-Depot Electric Vehicle Location Routing Problem with Time Windows (MDVLRP) is addressed. This problem is an extension of the MDVLRP, where electric vehicles are used instead of internal combustion engine vehicles. The recent development of this model is explained by the advantages of this technology, such as the diminution of carbon dioxide emissions, and the support that they can provide to the design of the logistic and energy-support structure of electric vehicle fleets. There are many models that extend the classical VRP model to take electric vehicles into consideration, but the multi-depot case for location-routing models has not been worked out yet. Moreover, we consider the availability of two energy supply technologies: the “Plug-in” Conventional Charge technology, and Battery Swapping Stations; options in which the recharging time is a function of the amount of energy to charge and a fixed time, respectively. Three models are proposed: one for each of the technologies mentioned above, and another in which both options are taken in consideration. The models were solved for small scale instances using C++ and Cplex 12.5. The results show that the models can be used to design logistic and energy-support structures, and compare the performance of the different options of energy supply, as well as measure the impact of these decisions on the overall distance traveled or other optimization objectives that could be worked on in the future. © 2018 Growing Science Ltd. All rights reserved

Energy Efficient Link-Delay Aware Routing in Wireless Sensor Networks

Abstract: This paper investigates the problem of energy consumption in wireless sensor networks. Wireless sensor nodes deployed in harsh environment where the conditions change drastically suffer from sudden changes in link quality and node status. The end-to-end delay of each sensor node varies due to the variation of link quality and node status. On the other hand, the sensor nodes are supplied with limited energy and it is a great concern to extend the network lifetime. To cope with those problems, this paper proposes a novel and simple routing metric, predicted remaining deliveries (PRD), combining parameters, including the residual energy, link quality, end-to-end delay, and distance together to achieve better network performance. PRD assigns weights to individual links as well as end-to-end delay, so as to reflect the node status in the long run of the network. Large-scale simulation results demonstrate that PRD performs better than the widely used ETX metric as well as other two metrics devised recently in terms of energy consumption and end-to-end delay, while guaranteeing packet delivery ratio.

BERA: a biogeography-based energy saving routing architecture for wireless sensor networks

Abstract: Biogeography-based optimization (BBO) is a relatively new paradigm for optimization which is yet to be explored to solve complex optimization problems to prove its full potential. In wireless sensor networks (WSNs), optimal cluster head selection and routing are two well-known optimization problems. Researchers often use hierarchal cluster-based routing, in which power consumption of cluster heads (CHs) is very high due to its extra functionalities such as receiving and aggregating the data from its member sensor nodes and transmitting the aggregated data to the base station (BS). Therefore, proper care should be taken while selecting the CHs to enhance the life of the network. After formation of the clusters, data to be routed to the BS in inter-cluster fashion for further enhancing the life of WSNs. In this paper, a biogeography-based energy saving routing architecture (BERA) is proposed for CH selection and routing. The biogeography-based CH selection algorithm is proposed with an efficient encoding scheme of a habitat and by formulating a novel fitness function that uses residual energy and distance as its metrics. The BBO-based routing algorithm is also proposed. The efficient encoding scheme of a habitat is developed, and its fitness function considers the node degree in addition to residual energy and distance. To exhibit the performance of BERA, it is extensively tested with some existing routing algorithms such as DHCR, Hybrid routing, EADC and some bio-inspired algorithms, namely GA and PSO. Simulation results confirm the superiority/competitiveness of the proposed algorithm over existing techniques.

A Microbial Inspired Routing Protocol for VANETs

Abstract: We present a bio-inspired unicast routing protocol for vehicular ad hoc networks which uses the cellular attractor selection mechanism to select next hops. The proposed unicast routing protocol based on attractor selecting (URAS) is an opportunistic routing protocol, which is able to change itself adaptively to the complex and dynamic environment by routing feedback packets. We further employ a multiattribute decision-making strategy, the technique for order preference by similarity to an ideal solution, to reduce the number of redundant candidates for next-hop selection, so as to enhance the performance of attractor selection mechanism. Once the routing path is found, URAS maintains the current path or finds another better path adaptively based on the performance of current path, that is, it can self-evolution until the best routing path is found. Our simulation study compares the proposed solution with the state-of-the-art schemes, and shows the robustness and effectiveness of the proposed routing protocol and the significant performance improvement, in terms of packet delivery, end-to-end delay, and congestion, over the conventional method.

A survey of recent advances in vehicle routing problems

Abstract: A vehicle routing problem involves finding a set of optimal route for a fleet of capacitated vehicles which are available at a location to service the demands of a set of customers. In its simplest form, a customer is required to be visited once and the capacity of a vehicle must not be exceeded. In this paper, a review of four common and applicable variants of the vehicle routing problem, namely, capacitated vehicle routing problem, vehicle routing problem with time windows, periodic vehicle routing problem and the dynamic vehicle routing problem, are considered based on formulation techniques, methods of solution and areas of application. A summary table is presented for each variant to emphasis some key features that represent direction of current research.

AODVCS, a new bio-inspired routing protocol based on cuckoo search algorithm for mobile ad hoc networks

Abstract: Mobile ad hoc networks (MANETs) are becoming an emerging technology that offer several advantages to users in terms of cost and ease of use. A MANET is a collection of mobile nodes connected by wireless links that form a temporary network topology that operates without a base station and centralized administration. Routing is a method through which information is forwarded from a transmitter to a specific recipient. Routing is a strategy that guarantees, at any time, the connection between any two nodes in a network. In this work, we propose a novel routing protocol inspired by the cuckoo search method. Our routing protocol is implemented using Network simulator 2. We chose Random WayPoint model as our mobility model. To validate our work, we opted for the comparison with the routing protocol ad hoc on-demand distance vector, destination sequence distance vector and the bio-inspired routing protocol AntHocNet in terms of the quality of service parameters: packet delivery ratio and end-to-end delay (E2ED).

On Caching and Routing in Information-Centric Networks

Abstract: With the exponential growth of content in recent years, users are primarily interested in obtaining particular content and are not concerned with the host housing the content. By treating content as a first class citizen, information- centric networks (ICN) seek to transform the Internet from a host-to-host communication model to a content-centric model. A key component of ICN is to cache content at storage-enabled routers. By caching content at in-network routers, network performance can be improved by delivering content from routers closer to the user and not from the origin servers (content custodians). In this article, we provide an overview of the state-of-the-art cache management and routing policies in ICN. We present a small comparison study of some state-of-the-art algorithms on a real Internet topology to help the reader appreciate how the different strategies compare against one another. Our simulation results demonstrate that it is hard to pick a winner among existing policies. We conclude the article with a discussion of open research questions.

Fuzzy Logic Based Reliable and Real-Time Routing Protocol for Mobile Ad hoc Networks

Abstract: MANET (mobile ad-hoc network) includes a set of wireless mobile nodes which communicate with one another without any central controls or infrastructures and they can be quickly implemented in the operational environment. One of the most significant issues in MANETs is concerned with finding a secure, safe and short route so that data can be transmitted through it. Although several routing protocols have been introduced for the network, the majority of them just consider the shortest path with the fewest number of hops. Hop criterion is considered for simple implementation and it is reliable in dynamic environments; however, queuing delay and connection delay in the intermediate nodes are not taken into consideration for selecting route in this criterion. In this paper, a fuzzy logic-based reliable routing protocol (FRRP) is proposed for MANETs which selects stable routes using fuzzy logic. It is able to optimize system efficiency. The score allocated to routes are based on four criteria: accessible bandwidth, the amount of energy of battery, the number of hops and the degree of dynamicity of nodes. The simulation results obtained from OPNET simulator version 10.5 indicate that the proposed protocol, in comparison with ad hoc on-demand distance vector (AODV) and fuzzy-based on-demand routing protocol (FBORP), was able to better improve packet delivery rate, average end-to-end delay and throughput.

An efficient routing protocol for the QoS support of large-scale MANETs

Abstract: Summary The hierarchical routing algorithm is categorized as a kind of routing method using node clustering to create a hierarchical structure in large-scale mobile ad hoc network (LMANET). In this paper, we proposed a new hierarchical clustering algorithm (HCAL) and a corresponded protocol for hierarchical routing in LMANET. The HCAL is designed based on a cost metric in the form of the link expiration time and node's relative degree. Correspondingly, the routing protocol for HCAL adopts a reactive protocol to control the existing cluster head (CH) nodes and handle proactive nodes to be considered as a cluster in LMANET. Hierarchical clustering algorithm jointly utilizes table-driven and on-demand routing by using a combined weight metric to search dominant set of nodes. This set is composed by link expiration time and node's relative degree to establish the intra/intercommunication paths in LMANET. The performance of the proposed algorithm and protocol is numerically evaluated in average end-to-end delay, number of CH per round, iteration count between the CHs, average CH keeping time, normalized routing overhead, and packet delivery ratio over a number of randomly generated benchmark scenarios. Furthermore, to corroborate the actual effectiveness of the HCAL algorithm, extensive performance comparisons are carried out with some state-of-the-art routing algorithms, namely, Dynamic Doppler Velocity Clustering, Signal Characteristic-Based Clustering, Dynamic Link Duration Clustering, and mobility-based clustering algorithms.

Balanced and energy-efficient multi-hop techniques for routing in wireless sensor networks

Abstract: In Wireless Sensor Networks, the power resources of the nodes are significantly restricted. Hence, a special treatment for their available energy is deeply required. In long distance transmission, Multi-Hop (MH) techniques are preferred. Although MH minimizes the amount of energy cost consumed by each node along the path but finding the optimal routing path between nodes is still very interesting issues. This paper proposes a Balanced and Energy Efficient MH (BEEMH) algorithm that is developed based on Dijkstra algorithm. It gives great interest to the residual energy of nodes; hence higher energy nodes are exclusively elected to work as relays. Moreover, the total energy consumption at both TX and RX has been merged to model the weight of links between nodes. Finally, Dijkstra algorithm is employed to efficiently search for the minimum cost path. Furthermore, two proposed MH protocols are introduced. Both are mainly based on the BEEMH algorithm. MATLAB simulator has been used to evaluate BEEMH in comparison with other conventional algorithms such as; minimum transmission energy (MTE), energy saving oriented least-hop routing algorithm (ESLHA), and energy saving-oriented routing algorithm based on Dijkstra (ESRAD) under various scenarios of network models. Then the performance of our proposed protocols is compared with the related MH protocols.

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

Abstract: Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.

Characterizing Data Deliverability of Greedy Routing in Wireless Sensor Networks

Abstract: As a popular routing protocol in wireless sensor networks (WSNs), greedy routing has received great attention. The previous works characterize its data deliverability in WSNs by the probability of all nodes successfully sending their data to the base station. Their analysis, however, neither provides the information of the quantitative relation between successful data delivery ratio and transmission power of sensor nodes nor considers the impact of the network congestion or link collision on the data deliverability. To address these problems, in this paper, we characterize the data deliverability of greedy routing by the ratio of successful data transmissions from sensors to the base station. We introduce $\eta$ -guaranteed delivery which means that the ratio of successful data deliveries is not less than $\eta$ , and study the relationship between the transmission power of sensors and the probability of achieving $\eta$ -guaranteed delivery. Furthermore, with considering the effect of network congestion, link collision, and holes (e.g., those caused by physical obstacles such as a lake), we provide a more precise and full characterization for the deliverability of greedy routing. Extensive simulation and real-world experimental results show the correctness and tightness of the upper bound of the smallest transmission power for achieving $\eta$ -guaranteed delivery.

Optimal Routing of Energy-Aware Vehicles in Transportation Networks With Inhomogeneous Charging Nodes

Abstract: We study the problem of routing for energy-aware battery-powered vehicles (BPVs) in networks with charging nodes. The objective is to minimize the total elapsed time, including travel and recharging time at charging stations, so that the vehicle reaches its destination without running out of energy. Relaxing the homogeneity of charging stations, and here, we investigate the routing problem for BPVs through a network of “inhomogeneous” charging nodes. We study two versions of the problem: the single-vehicle (user-centric) routing problem and the multiple-vehicle (system-centric) routing problem. For the former, we formulate a mixed-integer nonlinear programming (NLP)problem for obtaining an optimal path and charging policy simultaneously. We then reduce its computational complexity by decomposing it into two linear programming problems. For the latter, we use a similar approach by grouping vehicles into “subflows” and formulating the problem at a subflow-level with the inclusion of traffic congestion effects. We also propose an alternative NLP formulation obtaining near-optimal solutions with orders of magnitude reduction in the computation time. We have applied our optimal routing approach to a subnetwork of the eastern Massachusetts transportation network using actual traffic data provided by the Boston Region Metropolitan Planning Organization. Using these data, we estimate cost (congestion) functions and investigate the optimal solutions obtained under different charging station and energy-aware vehicle loads.

Load Balance in Data Center SDN Networks

Abstract: In the last two decades, networks had been changed according to the rapid changing in its requirements. The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations. The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs. Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs

Packet Routing in 3D Nanonetworks: A Lightweight, Linear-path Scheme

Abstract: Packet routing in nanonetworks requires novel approaches, which can cope with the extreme limitations posed by the nano-scale. Highly lossy wireless channels, extremely limited hardware capabilities and non-unique node identifiers are among the restrictions. The present work offers an addressing and routing solution for static 3D nanonetworks that find applications in material monitoring and programmatic property tuning. The addressing process relies on virtual coordinates from multiple, alternative anchor point sets that act as \emph{viewports}. Each viewport offers different address granularity within the network space, and its selection is optimized by a packet sending node using a novel heuristic. Regarding routing, each node can deduce whether it is located on the linear segment connecting the sender to the recipient node. This deduction is made using integer calculations, node-local information and in a stateless manner, minimizing the computational and storage overhead of the proposed scheme. Most importantly, the nodes can regulate the width of the linear path, thus trading energy efficiency (redundant transmissions) for increased path diversity. This trait can enable future adaptive routing schemes. Extensive evaluation via simulations highlights the advantages of the novel scheme over related approaches.

Global Routing With Timing Constraints

Abstract: We show how to incorporate global static timing constraints into global routing. Our approach is based on the min–max resource sharing model that proved successful for global routing in theory and practice. Static timing constraints are modeled by a linear number of additional resources and customers. The algorithm dynamically adjusts delay budgets and can, thus, tradeoff wiring congestion for delay. As a subroutine, the algorithm routes a single net. If this subroutine is near-optimal, we will find near-optimal solutions for the overall problem very efficiently. The approach works for many delay models; here we discuss a linear delay model (before buffering) and the Elmore delay model (after buffering). We demonstrate the benefit of our timing-constrained global routing algorithm by experimental results on industrial chips.

Integration of order picking and vehicle routing in a B2C e-commerce context

Abstract: E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company’s logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows.