Cost Of Additional Resources Research Articles

Reconstructing jets in the Phase-2 upgrade of the CMS Level-1 Trigger with a seeded cone algorithm

The Phase-2 Upgrade of the CMS Level-1 Trigger (L1T) will reconstruct particles using the Particle Flow algorithm, connecting information from the tracker, muon, and calorimeter detectors, and enabling fine-grained reconstruction of high level physics objects like jets. We have developed a jet reconstruction algorithm using a cone centred on an energetic seed from these Particle Flow candidates. The implementation is designed to find up to 16 jets in each Xilinx Ultrascale+ FPGA, with a latency of less than 1 µs, and event throughput of 6.7 MHz to fit within the L1T system constraints. Pipelined processing enables reconstruction of jet collections with different cone sizes for little additional resource cost. The design of the algorithm also provides a platform for additional computation using the jet constituents, such as jet tagging using neural networks. We will describe the implementation, its jet reconstruction performance, computational metrics, and the developments towards jet tagging.

Traditional and fuzzy goal programming approaches for resource dependent assembly line balancing problem

In this study, two goal programming models are proposed for balancing resource dependent assembly lines with precise and fuzzy goals in order to provide flexibility for decision makers based on their decision environment and preferred priorities. Three conflicting goals, namely, total number of utilized workstations, cycle time and total cost of additional resources (equipment and assistant workers) are considered. The proposed models are validated on illustrative examples and scenario analyses are performed with different priority levels of the goals. The results show that the proposed goal programming formulations are valid and useful for balancing resource dependent assembly lines.

Neighbor self-knowledge distillation

Self-Knowledge Distillation (Self-KD), a technique that enables neural networks to learn from themselves, often relies on auxiliary modules or networks to generate supervisory signals for training. However, this approach incurs significant additional resource costs. Moreover, incorporating auxiliary classifiers within the network architecture creates a capacity mismatch when distilling knowledge from deep to shallow classifiers. This paper proposes a concise and efficient Self-KD method called Neighbor Self-Knowledge Distillation (NSKD), which introduces teacher assistants into the Self-KD by adding auxiliary classifiers to the shallow part of the network to construct distillations of multiple neighboring student-teacher assistant combinations to reduce the mismatch between the students' and teachers' abilities. During distillation, NSKD utilizes only the soft labels generated by each classifier and corresponding ground truth labels as supervisory signals, minimizing resource consumption. NSKD enables neighboring modules to learn from each other through neighboring distillation, enhancing overall network performance. Experimental results on five network models and seven popular datasets demonstrate the superiority of NSKD over other state-of-the-art Self-KD methods. Notably, NSKD achieves average accuracy improvements of 2.26%, 2.32%, and 2.4% on the CIFAR100, TinyImageNet, and fine-grained visual classification datasets.

Optimization of French Hospital Department Activities Using an Efficient Discrete Event Simulation Model

A mismatch between patient demand and emergency departments (EDs)’ capacity to deliver care often leads to poor patient flow and overcrowding, and therefore an increase in waiting. This paper presents a mid-term decision support system dealing with scheduling and allocation of resources in the ED of the Hospital Center of Troyes, France. An efficient performance evaluation tool based on discrete event simulation (DES) is developed. Through a what-if scenario strategy, 145 scenarios were simulated that allowed us to create a new benchmark that does not exist in the literature. To rank and select the best alternatives, the VIKOR multicriteria analysis method and the entropy method were used. With the objective of minimizing the waiting time and inpatient stay under an additional resource cost constraint, this work has helped to quantify and analyze the impacts related to the structural and organizational reorganization of the ED.

Methodology and immediate results of selective controlled cerebral and myocardial perfusion for aortic arch obstruction in children

Highlights. Congenital heart defects in combination with aortic arch hypoplasia or coarctation of aorta are quite common in cardiac surgeon’s practice. The protection of internal organs is an important point in the treatment of these defects. Several methods have been proposed from hypothermic arrest to selective perfusion of various vascular regions. Given the variety of techniques, the effectiveness and advantages of each one are still a topic of debates. The article reflects the experience of using cerebro-myocardial perfusion in children with surgical correction of the aortic arch pathology.Aim. To analyze the prospects of regional selective controlled cerebral and myocardial perfusion method in surgical correction of aortic arch obstruction in children.Methods. A retrospective single-center analysis of the treatment in 29 pediatric patients was carried out and immediate results of cerebral-myocardial perfusion used in children with surgical correction of aortic arch obstruction in the period from 2016 to 2020 are presented. Median age was 6 days (1 day – 15 years old). Median weight was 3.6 kg (1.8–47 kg). 15 patients were girls, 14 patients were boys. The inclusion criteria for all the patients were cerebro-myocardial perfusion for aortic arch reconstruction.Results.Cardiopulmonary bypass time median was 78 minutes (43–206 minutes). The average time of cerebro-myocardial perfusion was 22.4 + –6.4 min (12–35 min). The median duration of the surgery was 3.1 hours (2.25–5.5 hours). The median time for mechanical ventilation was 101 hours (6–744 hours), in the ICU – 8.5 days (1–31 days). The average time of hospital stay was 18.2 days + –6.7 days (7–31 days). Early postoperative mortality was 3.4%. Renal replacement therapy was required for 2 newborns (7%). Operational risks, according to the Aristotle Score, were significantly higher in newborns (χ2 = 3.9277, df = 1, p-value = 0.0475). There were no cardiac events associated with myocardial perfusion. The type of cardioplegia (blood or “Kustadiol”) did not significantly affect the pumping function of the heart, assessed by transthoracic echocardiography on day 1 after the surgery (χ2 = 0.27273, df = 1, p-value = 0.6015). Acute ischemic cerebrovascular accident occurred in 1 patient (3.5%).Conclusion. The technique of controlled selective cerebro-myocardial perfusion is reproducible without any additional resource costs. We can confidently say that the time of surgery and cardiopulmonary bypass is much shorter than in case of using deep hypothermic arrest or isolated selective cerebral perfusion, as soon as there is less time needed for cooling and re-warming the body. Also, the time of cardiac arrest was reduced or completely eliminated (with isolated reconstruction of the aortic arch). The technique is effective and safely reproducible in both newborns and older children. The results for mortality and complications are encouraging but must be further evaluated and compared.

Study of social tension based on electronic social networks big data

The article presents a methodology for assessing the level of social tension according to the data of electronic social networks. The calculation of the level of social tension according to the specified method is carried out automatically using software tools and requires the participation of the researcher only at the level of an analytical conclusion. An approach to identifying the dissatisfaction of the population at the level of the simplest actions of social network accounts has been described in detail. The necessity of identifying certain spheres of public life for the identification of population discontent has been substantiated, the indicated spheres have been highlighted and described. An indicator has been developed that makes it possible to calculate the level of social tension within each of the identified spheres of public life, taking into account the level of negative messages (posts and comments) and the discussion of each topic. A generalising indicator of the level of social tension has been developed, combining individual indicators of tension by topic. The calculation of the generalising indicator makes it possible to identify the level of social tension in a region or other territorial entity and track its dynamics in any perspective, including retrospectively.The proposed methodology for assessing social tension based on data from electronic social networks differs significantly from existing sociological and statistical approaches. Its main advantage lies in the minimal time lag between the dynamics of social tension, reflected in the social network, and its identification, which expands the possibilities of a prompt response to the growth of negative moods in society. Another difference of the proposed approach is the possibility of multiple repetitions of calculations with minimal, in contrast to the sociological method, the cost of additional resources for each subsequent iteration of the calculation of the indicator value.

'Dalarinji': A flexible clinic, belonging to and for the Aboriginal people, in an Australian emergency department.

Equity and access to high-quality healthcare for Aboriginal and Torres Strait Islander (Aboriginal) people has remained refractory for complex and multifactorial reasons, and there are sound ethical arguments for addressing this urgently. In EDs all patients who 'leave at own risk' (LAOR) or 'do not wait to be seen' (DNW) are at increased risk of readmission, morbidity or death. This also incurs additional resource costs to the health system. Aboriginal patients have high rates of DNW and LAOR. The Flexiclinic model of care was co-designed to better support the needs of Aboriginal patients in the ED and to reduce the rates of DNW and LAOR. 'Dalarinji', or Flexiclinic, is a flexible model of care within the ED collaboratively devised with the Aboriginal Health Unit to address the major factors that influence this vulnerable cohort leaving the St Vincent's Hospital ED (SVHED) prior to being assessed or before completion of treatment. In the 3 months since its introduction, the Flexiclinic approach has significantly improved the quality and equity of access to medical care at SVHED for Aboriginal patients with the average summed rate of DNW and LAOR falling to 5.2% of presentations, representing a fivefold decrease in the probability of Aboriginal patients receiving incomplete care. The Flexiclinic approach has significantly improved medical care at SVHED for Aboriginal patients. It has been well received by both staff and patients and has had no adverse effects on delivery of services to other patient groups.

INVESTIGATION OF THE PROBLEM OF OPTIMIZATION OF THE HIERARCHICAL STRUCTURE OF A SPARSE AND DENSE COMMUNICATION NETWORK

The article is devoted to the study of the optimization problem for the hierarchical structure of a multicommodity communication network with discrete flows and parameters when its density changes (the ratio of the number of network arcs to the maximum possible number of arcs for a given number of nodes in the network). The network has three levels of hierarchy — a backbone, a zonal and a internal and four types of nodes — backbone nodes of the first, second and third types, forming the backbone and zonal levels of the network, and nodes of the fourth type, which subordinate to each backbone node and form the internal levels of the network. The types of nodes different from one another in functionality. The main task of the study is to establish how the structure of the backbone network changes (the number and location of backbone nodes of the first, second and third types), the scheme of processing and distribution of flows and technical and economic indicators of the network's functioning for various degrees of its density. The principles of organizing the sorting and distribution of flows in a three-level network and its mathematical model are given. A mathematical model of the problem of optimizing the structure of the backbone network and the schemes of sorting and distribution of flows is formulated. The algorithms for solving the problem are based on the discrete analogue of the local descent method proposed earlier by the authors, when the neighborhoods of the metric space of possible solutions are chosen from heuristic considerations, taking into account the peculiarities of the problem being solved. Computer modeling of the problem on a homogeneous network containing 100 nodes with a change in the degree of nodes from 2 to 99 is carried out. The modeling was carried out on the example of a road transport network for the transportation of cargo using a computer program, which is part of the instrumental software of the Information and Analytical Decision Support System (IA DSS), which is being developed at the Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine. An experimental study of the solution to the problem showed that the best technical, economic and operational indicators of its functioning are achieved with a degree nodes from 9 to 14, when high network connectivity is ensured, and is significantly reduced the average and maximum time of delivery of cargos to recipients. The proposed computer technology for solving problem with changing network density allows you to interactively modeling various options of a network , changing the topology, hierarchical structure, flows, parameters and constraints of the model and from the family of the resived results choose the best option, taking into account the selected a goal function and the accepted constraints; calculate preliminary technical and economic indicators of the network's functioning, estimate the cost of additional resources and plan the amount of investment required for the modernization and construction of its structural elements, which ultimately makes it possible to increase the efficiency functioning of the network by optimizing use of its resources and reducing the operating costs for the processing and transportation of flows.

An Uncertain Resource Constrained Scheduling Model Based on Uncertainty Theory

Resource constrained project scheduling problem is to make a schedule for minimizing of the completion time or total cost subject to precedence rules and resource constraints. Traditional resource constrained project scheduling problem research takes into account achieve management goal in certain environment. However, there are many uncertainties in practical projects due to the uncertain factors, which leads to the change of resource availability. In this paper, for better described the uncertain resource constrained project scheduling problem, we firstly consider the uncertain resource availability project scheduling problem based on uncertainty theory. To meet the manger goals, it is assumed that the increased quantities of resource are uncertain variables and the finish time of each activity is a decision variable. Then, an uncertain resource constrained model is built. The goals of the model are to minimize the completion time and the total cost which composed by the activity cost and the additional resource cost. One of the constraints is the finish-start precedence relationship among the project activities. The other constraint is the resource constraint in which the demand of resource shall not exceed the total supply of resource for each resource type at any time. Furthermore, the equivalent form of the above model is given and its equivalence is proved. Finally, a genetic algorithm is applied to search for quasi-optimal scheduling, and a project example is given to illustrate the effectiveness of the model.

Shorter gate sequences for quantum computing by mixing unitaries

Fault-tolerant quantum computers compose elements of a discrete gate set in order to approximate a target unitary. The problem of minimising the number of gates is known as gate-synthesis. The approximation error is a form of coherent noise, which can be significantly more damaging than comparable incoherent noise. We show how mixing over different gate sequences can convert this coherent noise into an incoherent form. As measured by diamond distance, the post-mixing noise is quadratically smaller than before mixing, with no additional resource cost. Equivalently, we can use a shorter gate sequence to achieve the same precision as unitary gate-synthesis, with a factor 1/2 reduction for a broad class of problems.

A proactive scheduling approach to steel rolling process with stochastic machine breakdown

We address a proactive scheduling problem with stochastic machine breakdown, controllable processing time and deterioration effect considerations arising from steel production. The problem is to determine the pre-compression amount of each job’s processing time and the job sequence for the rolling process so as to achieve a robust predictive schedule in response to machine breakdown. Both robustness and stability of the predictive schedule are considered, in correspondence with the mean and variance of rescheduling cost that consists of match-up time cost and additional resource cost. Since the scenario-based approach to robustness evaluation of a predictive schedule is cursed with high computational burden, a surrogate-assisted multi-objective evolutionary algorithm based on Elitist non-dominated sorting genetic algorithm is proposed to solve the proactive scheduling problem under consideration. Support vector regression model is introduced to approximate the robustness of the each alternative schedule which surrogates the time-consuming simulation-based fitness evaluation process and saves more time for solution space search. In addition, a probabilistic sequencing strategy which takes advantage of each job’s ability to absorb disruption at low cost is introduced to guide the evolutionary search. Computational experiments of numerical and practical data indicate that the proposed proactive scheduling approach performs well in response to stochastic machine breakdown. The support vector regression model and the probabilistic sequencing strategy improve the performance of the proposed algorithm with respect to the convergence and diversity of the obtained Pareto front.

A Highly Compatible Circular-Shifting Network for Partially Parallel QC-LDPC Decoder

The conventional methodology for designing QC-LDPC decoders is applied for fixed configurations used in wireless communication standards, and the supported largest expansion factor Z (the parallelism of the layered decoding) is a fixed number. In this paper, we study the circular-shifting network for decoding LDPC codes with arbitrary Z factor, especially for decoding large Z (Z P) codes, where P is the decoder parallelism. By buffering the P-length slices from the memory, and assembling the shifted slices in a fixed routine, the P-parallelism shift network can process Z-parallelism circular-shifting tasks. The implementation results show that the proposed network for arbitrary sized data shifting consumes only one times of additional resource cost compared to the traditional solution for only maximum P sized data shifting, and achieves significant saving on area and routing complexity.

Reduced Emergency Room Utilization for Initiation of Anticoagulation with Rivaroxaban Treatment of Cancer-Associated Thrombosis

▪Venous thromboembolism (VTE) is a leading cause of mortality and morbidity in cancer patients, and management represents a major cost to the healthcare system. We have previously presented in a cohort of 200 patients with cancer-associated thrombosis, rivaroxaban provides an alternative to low molecular weight heparin (LMWH), with 4.4% recurrent VTE and 2.2% major bleeding at 6 months (Mantha et al, ASH Abstract, 2015). Other recent publications have provided similar support for use of rivaroxaban in treatment of cancer-associated thrombosis (Bott-Kitslaar et al, Am J Med. 2016, Prins et al, Lancet Haem, 2014). In our early experience with rivaroxaban, fewer patients were sent to the Emergency Room (ER) for initiation of rivaroxaban than LMWH. We now characterize the site and cost of initiation of anticoagulation for the full 200 rivaroxaban patient cohort and a similar cohort of patients treated with LMWH demonstrating significant changes in practice and cost savings.In an IRB approved initiative we track all patients with cancer-associated thrombosis at MSKCC. We characterized the site of initiation of anticoagulation of the first 200 cancer patients with a pulmonary embolism (PE) or lower extremity deep vein thrombosis DVT since January 2014, treated with rivaroxaban. A similar cohort from June through December 2013 was treated with enoxaparin. We excluded patients whose VTE developed as an inpatient. Anticoagulation starts were classified as an emergency room (ER) visit or a second return outpatient visit on the same day for patient education and insurance authorization, a single outpatient visit, or telephone communication. Respective billing codes were then used as part of an economic evaluation to estimate the cost of the additional healthcare resources utilized, and therefore the costs saved by reduction in ER visits or second medical office visits.In the first 6 months of rivaroxaban availability, there was no decrease in ER utilization, compared with LMWH use. After 6 months of rivaroxaban availability, there was a significant decrease in ER visits for VTE management (p=0.008), which resulted in a decrease from baseline of 71% to 34% after one year (p=0.0001). Also of note, after one year of rivaroxaban availability, 18% of newly diagnosed VTE were managed by a simple telephone call to the patient or family member, typically after a recent outpatient visit. Only 2 patients who were started on rivaroxaban had required an additional outpatient visit to our Hematology clinic for evaluation.Based on 2016 Medicare billing codes, we calculated the cost for the additional resources utilized, beyond a single outpatient visit. During the first 6 months of rivaroxaban use, the cost of additional resources per 100 outpatient VTE patients ($47,067) was not significantly different than during the LMWH era ($43,144). However, as practice patterns evolved, ER utilization declined and more patients were managed without additional healthcare resources, resulting in an approximately 50% reduction in costs, for a savings of approximately $20,000 per 100 anticoagulation initiations.Management of cancer-associated thrombosis with LMWH is painful to the patient and expensive to the healthcare system. Patient quality of life is improved by treatment with rivaroxaban versus LMWH, with no evidence of loss of safety or efficacy. In this analysis, we expand on our prior observation that demonstrated a marked reduction in ER visits or hematology consults for the purpose of anticoagulation initiation and also show a substantial cost savings, of approximately $20,000 per 100 VTE patients. These changes in practice developed over an 18-month period, presumably reflecting a learning curve as healthcare providers became more familiar and comfortable with rivaroxaban. Of course, some patients with a new cancer-associated thrombosis should be sent to an ER for evaluation, based on their hemodynamic state or co-morbidities. However, our findings suggest that a majority of patients with cancer-associated thrombosis do not require ER visits, improving patient quality of life and sparing healthcare resources. [Display omitted] DisclosuresSoff:Janssen Pharmaceuticals: Other: Summer Student Internship. Mantha:Janssen Scientific Affairs, LLC: Research Funding. Soff:Janssen Scientific Affairs, LLC: Consultancy, Research Funding.

Modeling a Generalized Resource Constrained Multi Project Scheduling Problem Integrated with a Forward-Backward Supply Chain Planning

Generalized Resource Constrained Multi Project Scheduling Problem, GRCMPSP, is issue of determining a scheduling plan for executing projects’ activities under satisfaction of precedence relationship between activities and availability of resources. This paper focuses on the resources’ availability. To deal with feeding nonrenewable recourses over periods they are demanded and to define a production-transportation plan for them, our proposed mixed integer programming model integrates GRCMPSP with Supply Chain Planning model. Also, to establish a plan for assigning required amounts of renewable resources, it supposes possibility of renting supplementary quantities. This assumption leads the model to define an optimum assignment under considering rent cost of additional resources and penalty cost may originate from lateness of the activities. The results are shown from applying the model on a project called CRIB A, which is defined to reduce energy consumption level of buildings in France.

Obesity in pregnancy: infant health service utilisation and costs on the NHS

ObjectiveTo estimate the direct healthcare cost of infants born to overweight or obese mothers to the National Health Service in the UK.DesignRetrospective prevalence-based study.SettingCombined linked anonymised electronic data sets on...

A knowledge-based evolutionary proactive scheduling approach in the presence of machine breakdown and deterioration effect

This paper considers proactive scheduling in response to stochastic machine breakdown under deteriorating production environments, where the actual processing time of a job gets longer along with machine's usage and age. It is assumed that a job's processing time is controllable by allocating extra resources and the machine breakdown can be described using a given probability distribution. If a machine breaks down, it needs to be repaired and is no longer available during the repair. To absorb the repair duration, the subsequent unfinished jobs are compressed as much as possible to match up the baseline schedule. This work aims to find the optimal baseline sequence and the resource allocation strategy to minimize the operational cost consisting of the total completion time cost and the resource consumption cost of the baseline schedule, and the rescheduling cost consisting of the match-up time cost and additional resource cost. To this end, an efficient multi-objective evolutionary algorithm based on elitist non-dominated sorting is proposed, in which a support vector regression (SVR) surrogate model is built to replace the time-consuming simulations in evaluating the rescheduling cost, which represents the solution robustness of the baseline schedule. In addition, a priori domain knowledge is embedded in population initialization and offspring generation to further enhance the performance of the algorithm. Comparative results and statistical analysis show that the proposed algorithm is effective in finding non-dominated tradeoff solutions between operational cost and robustness in the presence of machine breakdown and deterioration effect.

A Hardware Scheduler Based on Task Queues for FPGA-Based Embedded Real-Time Systems

A hardware scheduler is developed to improve real-time performance of soft-core processor based computing systems. A hardware scheduler typically accelerates system performance at the cost of increased hardware resources, inflexibility and integration difficulty. However, the reprogrammability of FPGA-based systems removes the problems of inflexibility and integration difficulty. This paper introduces a new task-queue architecture to better support practical task controls and maintain good resource scaling. The scheduler can be configured to support various algorithms such as time sliced priority scheduling, Earliest Deadline First and Least Slack Time. The hardware scheduler reduces scheduling overhead by more than 1,000 clock cycles and raises the system utilization bound by a maximum 19.2 percent. Scheduling jitter is reduced from hundreds of clock cycles in software to just two or three cycles for most operations. The additional resource cost is no more than 17 percent of a typical softcore system for a small scale embedded application.

Cooperative relaying in OFDMA networks based on the joint use of hierarchical modulation and link adaptation

In cooperative relaying, the base station broadcasts a signal to the destination, the relay overhears it and forwards it in a next time slot to the destination. The latter combines the two received copies of the signal in order to reconstruct the original one. In this study, we consider a relay-based OFDMA network, as is the case of long term evolution advanced systems. We, first, make use of hierarchical modulation to send additional information to the relay so as to enable it to reconstruct a more robust copy of the original signal, and, second, adapt the transmission from the relay to the destination by taking advantage of the typically good radio conditions between them so as to reduce the cost of additional resources needed by relaying and hence improve the overall system capacity. We model such a system at the user level, considering a realistic arrival and departure setting and quantify the gains thus achieved in a cross-layer manner, in terms of throughput and blocking probability. We, eventually, propose an enhancement to the afore-mentioned scheme that takes advantage of the good radio conditions of users who are close to the base station to send them an additional stream using hierarchical modulation.

A retrospective benefit-cost analysis of the 1997 stair-fall requirements for baby walkers

Based on estimates from the U.S. Consumer Product Safety Commission (CPSC), there were about 25,000 baby walker-related injuries treated annually in U.S. hospital emergency departments during the early 1990s. This amounted to about 8 injuries for every 1000 baby walkers in use. Most injuries resulted from falls down stairs. After CPSC initiated a regulatory proceeding in 1994, the CPSC staff worked with industry to address the stair-fall hazard. This cooperative effort resulted in requirements designed to prevent stair-fall injuries that became effective in 1997 as part of a revised voluntary safety standard. This study presents a retrospective benefit-cost analysis of the 1997 stair-fall requirements. The benefits were defined as the reduction in the costs of injuries resulting from the use of the safer walkers. The costs were defined as the additional resource costs associated with making baby walkers safer. The study found that the stair-fall requirements were highly effective in reducing the risk of stair-fall injury, and that the benefits of the requirements substantially exceeded the costs. The expected net benefits (i.e., benefits minus costs) amounted to an average of about $169 per walker, over the walker's expected product life. Given current U.S. sales of about 600,000 baby walkers annually, the present value of the expected net benefits associated with 1 year's production amounts to over $100 million annually. A sensitivity analysis showed that the major findings were robust with respect to variations in underlying assumptions.

Efficient Online Algorithms for Dynamic Shared Path Protection in WDM Optical Networks

In this work, we have proposed and studied efficient online algorithms for shared path protection under dynamic traffic conditions in survivable WDM optical mesh networks. Given a connection request, routing and wavelength assignment of a working path and a protection path for the request is formulated as two integer linear programs based on shared and dedicated path protection, respectively. The objective is to minimize the total cost of additional resources used by the working path as well as the protection path to accommodate a new connection request. We then devise two resource efficient online algorithms using pre-computed candidate routes. The first algorithm uses one candidate working path and one candidate protection path for each newly arrived connection request while the second algorithm may use multiple candidate working paths and/or multiple candidate protection paths. The selection of a pair of paths from candidate routes as well as the assignment of appropriate wavelengths to accommodate a connection request is then jointly considered to minimize the total cost of additional resources. The solutions to the ILP formulations serve as the baseline for evaluating the performance of the proposed algorithms. We have evaluated the effectiveness of the proposed online algorithms via extensive simulations in terms of the connection blocking probability and the revenue earnings improved over the dedicated path protection approach. Our simulations indicate that our proposed computationally efficient online algorithms are able to provide 100% restorability against single failures with a resource efficiency comparable to that of the optimal shared path protection. The results also show that a small increase in the number of candidate working paths or protection paths (from 1 to 3) provides better performance, but a further increase does not improve the performance significantly. Therefore, a proper balance can be struck to achieve both satisfactory performance and efficient computation.