Rerouting Approach Research Articles

HMLPA*: a hierarchical multi-target LPA* pathfinding algorithm designed for dynamic indoor path network

The Lifelong Planning A* (LPA*) algorithm demonstrates unique advantages in dynamic pathfinding by employing incremental update techniques that reuse previously computed search results, enabling rapid path replanning in dynamic road network environments. However, when changes occur near the starting point or specific positions, such as key intersections, bottlenecks, or locations with high connectivity within the path network, even minor changes can trigger significant adjustments, which significantly increase the re-routing search space and computational costs of LPA*. To address this limitation, we propose a Hierarchical Multi-target LPA* (HMLPA*) algorithm that partitions the indoor path network into multiple subgraphs using the METIS graph partitioning algorithm and constructs an abstract trunk graph based on the key nodes of these subgraphs, thereby forming a hierarchical structure for the indoor path network. By leveraging this hierarchical structure, The HMLPA*’s subalgorithm, Multi-target LPA* (MLPA*), initiates pathfinding and confines re-routing to affected subgraphs and the abstract trunk graph. This localized re-routing approach effectively limits the search scope and significantly reduces computational overhead. Experimental results demonstrate that HMLPA* substantially outperforms LPA* in rerouting efficiency, effectively mitigating the high computational costs associated with the dynamic computational environment of the indoor path network.

Traffic predictive-based flow splitting rerouting scheme for link failures in software-defined networks

This paper presents a traffic rerouting approach to keep a satisfactory QoS (Quality of Service) in virtualized network infrastructures (VPN, Cloud, etc.), supervised by an SDN (Software-Defined Networking) controller dealing with high traffic fluctuations. Traffic fluctuations are usually caused by link failures or link congestion and result in high packet loss, long delay times, and high jitter. These metrics are critical in computer network's QoS assessing. In our strategy, we combine traffic prediction in the SDN controller with flow splitting in the data plane. Simulations reveal that this strategy provides more satisfying values of the QoS assessment metrics compared to the literature.

A column generation approach for operational flight scheduling and aircraft maintenance routing

Aircraft is one of the most expensive resources owned by an airline which should be properly planned. The aircraft maintenance routing problem (AMRP) generates aircraft routes to serve scheduled flights, while satisfying the strict maintenance requirements. However, in operations, the pre-determined aircraft routes are usually disrupted due to unplanned maintenance requirements or insufficient remaining legal flying time to maintenance stations. Thus, airlines often have to re-route aircraft in real time. This study proposes a new aircraft re-routing approach to fulfil the maintenance requirements arising in the operational stage. Specifically, maintenance stations are capacity-constrained, while airlines could allocate maintenance resources (like staff and equipment) to other airports with additional costs. Besides, flights could be re-scheduled (i.e., cancelled with a high penalty), while the model endeavors to minimize the impact of recovery actions on the original plan. To achieve this, specialized flight networks are constructed, and a column generation-based algorithm is developed to obtain high-quality solutions within short computational times. Computational experiments show that the solutions obtained by the proposed algorithm are optimal or near-optimal with an optimality gap of 0.3% on average. In addition, some managerial insights on allocating maintenance resources to other airports to fulfil aircraft maintenance demands in operations are discussed.

Concept of climate-charged airspaces: a potential policy instrument for internalizing aviation's climate impact of non-CO2 effects

ABSTRACT Approximately 50–75% of aviation's climate impact is caused by non-CO2 effects, like the production of ozone and the formation of contrail cirrus clouds, which can be effectively prevented by re-routing flights around highly climate-sensitive areas. Here, we discuss options how to incentivize re-routing approaches and apply multicriteria trajectory optimizations to demonstrate the feasibility of the concept of climate-charged airspaces (CCAs). We show that although climate-optimized re-routing results in slightly longer flight times, increased fuel consumption and higher operating costs, it is more climate-friendly compared to a cost-optimized routing. In accordance to other studies, we find that the averaged temperature response over 100 years (ATR) of a single flight can be reduced by up to 40%. However, if mitigation efforts are associated with a direct increase in costs, there is a need for climate policies. To address the lack of incentivizing airlines to internalize their climate costs, this study focuses on the CCA concept, which imposes a climate charge on airlines when operating in highly climate-sensitive areas. If CCAs are (partly) bypassed, both climate impact and operating costs of a flight can be reduced: a more climate-friendly routing becomes economically attractive. For an exemplary North-Atlantic network, CCAs create a financial incentive for climate mitigation, achieving on average more than 90% of the climate impact reduction potential of climate-optimized trajectories (theoretical maximum, benchmark). Key policy insights Existing climate policies for aviation do not address non- effects, which are very sensitive to the location and the timing of the emission. By imposing a temporary climate charge for airlines that operate in highly climate-sensitive regions, the trade-off between economic viability and environmental compatibility could be resolved: Climate impact mitigation of non- effects coincides with cutting costs. To ensure easy planning and verification, climate charges are calculated analogously to en-route and terminal charges. For climate mitigation it is therefore neither necessary to monitor emissions ( , etc.) nor to integrate complex non- effects into flight planning procedures of airlines. Its implementation is feasible and effective.

Dynamic network flow optimization for real-time evacuation reroute planning under multiple road disruptions

During the course of an evacuation, evacuees often encounter unexpected incidents interrupting their plans for evacuation. Roads may not be accessible due to flooding, wild-fire propagation, accidents, the collapse of highway structures, and various other reasons. The evolving disturbances to the evacuation plan due to road disruptions may prolong the evacuation process and lead to chaos, injuries, and loss of life unless a quick, efficient recovery plan is implemented. In this work, we aim to provide a rerouting approach for an evacuation network that undergoes road disruptions. Unlike previous studies, it is assumed that incidents can occur on multiple roads and that the time of each occurrence can differ from the time of other occurrences. Flow optimization techniques are used to represent evacuation traffic flow on the transportation network. A dynamic traffic flow rate is considered in which the evacuation flow rate can change over time during the planning horizon. The variation in the flow rates enables a better projection of the traffic dynamics and consequences caused by disturbances. Furthermore, a path-based dynamic network flow optimization formulation is proposed to make the model scalable for large evacuation networks. Two preprocessing algorithms are introduced to calculate specific parameters associated with road disruptions and topology of the evacuation network. The use of these parameters enables us to transform the original optimization model into a linear model to reduce the computational burden. Numerical experiments are made to show the performance of the proposed model. Furthermore, the effects of specific features such as disruption time, disturbance location, and the plan updating time on the evacuation process are investigated. Results indicate that when more incidents occur later or when incident information is received earlier, the magnitude of the rerouting completion time is lessened.

Better safe than sorry: a vehicular traffic re-routing based on traffic conditions and public safety issues

Vehicular traffic re-routing is the key to provide better traffic mobility. However, taking into account just traffic-related information to recommend better routes for each vehicle is far from achieving the desired requirements of proper transportation management. In this way, context-aware and multi-objective re-routing approaches will play an important role in traffic management. Yet, most procedures are deterministic and cannot support the strict requirements of traffic management applications, since many vehicles potentially will take the same route, consequently degrading overall traffic efficiency. So, we propose an efficient algorithm named as Better Safe Than Sorry (BSTS), based on Pareto-efficiency. Simulation results have shown that our proposal provides a better trade-off between mobility and safety than state-of-the-art approaches and also avoids the problem of potentially creating different congestion spots.

Safe and Sound: Driver Safety-Aware Vehicle Re-Routing Based on Spatiotemporal Information

Vehicular traffic re-routing is key to provide better vehicular mobility. However, considering just traffic-related information to recommend better routes for each vehicle is far from achieving the desired requirements of a good Traffic Management System, which intends to improve not only mobility but also driving experience and safety of drivers and passengers. Context-aware and multi-objective re-routing approaches will play an important role in traffic management. However, most of these approaches are deterministic and can not support the strict requirements of traffic management applications, since many vehicles potentially will take the same route, and, thus, degrade the overall traffic efficiency. In this work, we introduce Safe and Sound (SNS), a non-deterministic multi-objective re-routing approach for improving traffic efficiency and reduce public safety risks (based on criminal events) for drivers and passengers. SNS employs a hybrid architecture and a cooperative re-routing approach for improving system scalability and computation efforts. SNS uses a recurrent neural network to both predict future safety risks dynamics and enable a personalized re-routing in which each vehicle decides the risks it wants to avoid. Simulation results revealed that when compared to state-of-the-art approaches, SNS reduces the CPU time of the re-routing algorithm in approximately 99% and decreases the average safety risk for drivers and passengers in at least 30% while keeping efficient traffic mobility.

Conflict-free rerouting scheme through flow splitting for virtual networks using switches

The weaknesses of the Internet led to the creation of a new network paradigm – network virtualization. Virtualization is a very successful technique for sharing and reusing resources, which results in higher efficiency. Despite its advantages, including flexibility in network architecture, virtualization imposes many challenges, such as physical resource allocation to virtual devices. An efficient allocation strategy for these resources can ensure good Quality of Service (QoS) in virtual networks, whether in node or link failure events. This paper presents a conflict-free rerouting scheme with efficient additional capacity usage for link and node failure resilience in a virtual network using switches. Combining an IP Fast Rerouting approach and flow-splitting strategy, this scheme provides short reaction time, stable performance and low complexity because the rerouting calculation and configuration are performed in advance. We show that rerouting by traffic splitting based on the entering arc and destination is sufficient to address all link-failure situations in the network, assuming that the network is two-link connected. After modelling the dimensioning problem as an Integer Linear Programme, we demonstrate through practical implementation of our rerouting scheme on different networks that the scheme can substantially minimize the additional capacity draw on the substrate network. A solution using multiple virtual planes is also provided to solve several conflict problems in the case of simultaneous multiple link failures.

Fault tolerance in TCAM-limited software defined networks

In Software Defined Networks (SDNs), while a proactive fault tolerance based on the local rerouting approach enables fast failure recovery, it requires to install forwarding rules for the backup paths in the switch Ternary Content Addressable Memory (TCAM) in advance. Since the TCAM size is limited and forwarding rules are long, using large number of forwarding rules for backup paths leads to frequent eviction of flows at the switches. To guarantee the bandwidth requirement for a flow upon a link failure, bandwidth reservation is also required on the backup path. Inefficient backup bandwidth usage will cause rejection of increased number of flows. In this paper, we address the problem of proactive fault tolerance in SDNs, considering the above challenges by adopting the local rerouting approach. We develop an optimization programming formulation that determines the set of backup paths to protect a flow while minimizing the number of additional rules and bandwidth required for the backup paths. Since this problem is computationally prohibitive, we develop two heuristic algorithms, namely Forward Local Rerouting (FLR) and Backward Local Rerouting (BLR) to compute backup paths so as to improve TCAM and bandwidth usage efficiency. We propose a flexible adaptive failure recovery framework that takes the decision of using FLR or BLR based on the network state. We evaluate the proposed algorithms through simulations and compare their performance with the optimal solution. The results show that the proposed algorithms perform very close to the optimal solution and reduce the number of additional rules required to protect a flow by up to 75% compared to the approaches that do not consider the limited size of TCAM. The results also show that the proposed algorithms are effective in terms of backup bandwidth efficiency and meet the carrier-grade requirement with the recovery time below 50 ms.

Facial nerve management in jugular paraganglioma surgery: a literature review.

This literature review analysed facial nerve management strategies in jugular paraganglioma surgery and discusses the tumour resection rate and the facial nerve outcome associated with each technique. A retrospective review of PubMed and Medline articles on the surgical treatments for jugular paraganglioma was performed. Tumour resection rates and post-operative facial nerve function after non-rerouting, short anterior rerouting and long anterior rerouting approaches were evaluated for each article. A total of 15 studies involving a total of 688 patients were included. Post-operative facial nerve function was similar after non-rerouting and short anterior rerouting approaches (p = 0.169); however, both of these techniques had significantly better post-operative facial nerve outcomes compared with long anterior rerouting (p < 0.001 and p = 0.001, respectively). The total tumour removal rate was significantly higher for long anterior rerouting than with the non-rerouting approach (p = 0.016). There was no difference in total tumour removal rate between the long and short anterior rerouting approaches (p = 0.067) and between the short anterior rerouting and non-rerouting approaches (p = 0.867). No strict guidelines for facial nerve management in jugular paraganglioma resection are available. Although long anterior rerouting provides the best tumour exposure along with a low morbidity rate, case-by-case selection of the surgical approach is recommended.

Dynamic fault‐tolerant routing algorithm for networks‐on‐chip based on localised detouring paths

Downscaled complementary metal-oxide semiconductor (CMOS) technology feature sizes have enabled massive transistor integration densities. Multi-core chips with billions of transistors are now a reality. However, this rapid increase in on-chip resources has come at the expense of higher susceptibility to defects and wear-out. The inter-router communication links of networks-on-chips (NoCs) are composed of metal wires that are especially vulnerable to catastrophic physical effects such as those of electro-migration, which can even cause link disconnects. To address this hazard, fault-tolerant (FT) routing algorithms sustain on-chip communication by re-routing messages around faulty links, or regions. This work presents a new FT routing scheme that employs a localised re-routing approach. Packets are de-toured around faulty links/regions based on purely local and distributed decisions, and without any global link state knowledge. The algorithm, which is proven to be deadlock- and livelock-free, also handles dynamically occurring faults. Detailed evaluation with synthetic traffic patterns and real applications within a full-system simulation environment demonstrate the efficacy of the new scheme with up to 12% of NoC links being faulty. Synthesis results also prove the feasibility of the proposed protocol at modest hardware and power consumption overheads of only over 5 and 2.5%, respectively.

Fast Emergency Paths Schema to Overcome Transient Link Failures in OSPF Routing

A reliable network infrastructure must be able to sustain traffic flows, even when a failure occurs and changes the network topology. During the occurrence of a failure, routing protocols, like OSPF, take from hundreds of milliseconds to various seconds in order to converge. During this convergence period, packets might traverse a longer path or even a loop. An even worse transient behaviour is that packets are dropped even though destinations are reachable. In this context, this paper describes a proactive fast rerouting approach, named Fast Emergency Paths Schema (FEP-S), to overcome problems originating from transient link failures in OSPF routing. Extensive experiments were done using several network topologies with different dimensionality degrees. Results show that the recovery paths, obtained by FEPS, are shorter than those from other rerouting approaches and can improve the network reliability by reducing the packet loss rate during the routing protocols convergence caused by a failure.

Analyzing fault aware collective performance in a process fault tolerant MPI

Application developers are investigating Algorithm Based Fault Tolerance (ABFT) techniques to improve the efficiency of application recovery beyond what traditional techniques alone can provide. Applications will depend on libraries to sustain failure-free performance across process failure to continue to use High Performance Computing (HPC) systems efficiently even in the presence of process failure. Optimized Message Passing Interface (MPI) collective operations are a critical component of many scalable HPC applications. However, most of the collective algorithms are not able to handle process failure. Next generation MPI implementations must provide fault aware versions of such algorithms that can sustain performance across process failure. This paper discusses the design and implementation of fault aware collective algorithms for tree structured communication patterns. The three design approaches of rerouting, lookup avoiding and rebalancing are described, and analyzed for their performance impact relative to similar fault unaware barrier and broadcast collective algorithms. The analysis shows that the rerouting approach causes a significant performance degradation while the rebalancing approach can bring the performance within 1% of the fault unaware performance. This paper also presents the impact of the run-through stabilization prototype on point-to-point communication, and analyzes the time to rebalance the tree while accounting for process failures.

Aspect of selective rerouting in multicriteria scheduling of flexible manufacturing

In this paper, a Multi-Criteria Scheduling Algorithm (MCSA) based on swapping of dispatching rules and Selective Rerouting (SR) approach based on lateral entry of critical jobs in the queue of alternate machine is used. Further, the effect of simultaneous application of MCSA and SR has been investigated. The system performance has been evaluated using mean flow time, maximum flow time, mean tardiness and maximum tardiness as the performance measures. Simulation studies using ProModel ® simulation software were carried out at different breakdown levels for a range of part complexity and part mix, in three types of flexible job shops with Job/Machine ratio less than, equal to and greater than unity involving a total of 799 simulation runs. Each run of simulation spans for a period of 2000 completed jobs. The results establish that simultaneous application of MCSA and SR improves the system performance between 12.17 % to 28.73 % and 30.51 % to 47.67 % over that when SR and MCSA respectively are applied individually. The improvement is more at low breakdown levels and high part complexity.

Preprocessing and Partial Rerouting Techniques for Accelerating Reconfiguration of Degradable VLSI Arrays

This paper presents novel techniques to accelerate the reconfiguration of degradable very large scale integration arrays. A preprocessing step is used to derive the upper and lower size bounds of the maximum logical array (MLA) such that only those subarrays that possibly contain the MLA are reconfigured, thereby reducing the reconfiguration time and also obtaining a same-sized logical array. In addition, the partial rerouting approach is generalized so that as many as possible previous routing results can be reused in the current rerouting step. The reconfiguration time is reduced from O((1-?)·s·m ·n) to its lower bound O((1-?)·m·n) for m × n host arrays with small fault density ?, where s is the expected routing length required per logical column.

Coarse optical circuit switching by default, rerouting over circuits for adaptation

As Internet traffic continues to grow unabated at an exponential rate, it is unclear whether the existing packet-routing network architecture based on electronic routers will continue to scale at the necessary pace. On the other hand, optical fiber and switching elements have demonstrated an abundance of capacity that appears to be unmatched by electronic routers. In particular, the simplicity of circuit switching makes it well suited for optical implementations. We present what we believe to be a new approach to optical networking based on a paradigm of coarse optical circuit switching by default and adaptive rerouting over circuits with spare capacity. We consider the provisioning of long-duration quasi-static optical circuits between edge routers at the boundary of the network to carry the traffic by default. When the provisioned circuit is inadequate, excess traffic demand is rerouted through circuits with spare capacity. In particular, by adaptively load balancing across circuits with spare capacity, excess traffic is routed to its final destination without the need to create circuits on the fly. Our evaluations on two separate real, large Internet service provider point-of-presence-level topologies, Abilene and GEANT, show that only a very small amount of excess traffic needs to be rerouted even during peak traffic hours when the circuit configurations are carefully chosen and that this excess traffic could always be accommodated using our adaptive rerouting approach. We also demonstrate that our adaptive load-balancing approach is robust to sudden unexpected traffic changes by demonstrating its ability to reroute traffic under a number of hot-spot scenarios.

Rerouting schemes for dynamic traffic grooming in optical WDM networks

Traffic grooming in optical WDM mesh networks is a two-layer routing problem to effectively pack low-rate connections onto high-rate lightpaths, which, in turn, are established on wavelength links. The objective of traffic grooming is to improve resource efficiency. However, resource contention between lightpaths and connections may result in inefficient resource usage or even the blocking of some connections. In this work, we employ a rerouting approach to alleviate resource inefficiency and improve the network throughput under a dynamic traffic model. We propose two rerouting schemes, rerouting at lightpath level (RRLP) and rerouting at connection level (RRCON) and a qualitative comparison is made between the two. We also propose two heuristic rerouting algorithms, namely the critical-wavelength-avoiding one-lightpath-limited (CWA-1L) rerouting algorithm and the critical-lightpath-avoiding one-connection-limited (CLA-1C) rerouting algorithm, which are based on the two rerouting schemes. Simulation results show that rerouting reduces the blocking probability of connections significantly.

Delay Constrained Routing and Link Capacity Assignment in Virtual Circuit Networks

An essential issue in designing, operating and managing a modern network is to assure end-to-end QoS from users perspective, and in the meantime to optimize a certain average performance objective from the systems perspective. So in the first part of this paper, we address the above issue by using the rerouting approach, where the objective is to minimize the average cross-network packet delay in virtual circuit networks with the consideration of an end-to-end delay constraint (DCR) for each O-D pair. The problem is formulated as a multicommodity network flow problem with integer routing decision variables, where additional end-to-end delay constraints are considered. As the traffic demands increases over time, the rerouting approach may not be applicable, which results in the necessity of capacity augmentation. Henceforth, the second part of this paper is to jointly consider the link capacity assignment and the routing problem (JCR) at the same time where the objective is to minimize the total link installation cost with considering the average and end-to-end delay constraints. Unlike previous research tackling this problem with a two-phase approach, we propose an integrated approach to considering the routing and capacity assignment at the same time. The difficulties of OCR and JCR result from the integrality nature and particularly the nonconvexity property associated with the end-to-end delay constraints. We propose novel Lagrangean relaxation based algorithms to solve the DCR and the JCR problems. Through computational experiments, we show that the proposed algorithms calculate near-optimal solutions for the DCR problem and outperform previous two-phase approach for the JCR problem under all tested cases.