Total Resource Consumption Research Articles

Using Proactive Fault-Tolerance Approach to Enhance Cloud Service Reliability

The large-scale utilization of cloud computing services for hosting industrial/enterprise applications has led to the emergence of cloud service reliability as an important issue for both cloud service providers and users. To enhance cloud service reliability, two types of fault tolerance schemes, reactive and proactive, have been proposed. Existing schemes rarely consider the problem of coordination among multiple virtual machines (VMs) that jointly complete a parallel application. Without VM coordination, the parallel application execution results will be incorrect. To overcome this problem, we first propose an initial virtual cluster allocation algorithm according to the VM characteristics to reduce the total network resource consumption and total energy consumption in the data center. Then, we model CPU temperature to anticipate a deteriorating physical machine (PM). We migrate VMs from a detected deteriorating PM to some optimal PMs. Finally, the selection of the optimal target PMs is modeled as an optimization problem that is solved using an improved particle swarm optimization algorithm. We evaluate our approach against five related approaches in terms of the overall transmission overhead, overall network resource consumption, and total execution time while executing a set of parallel applications. Experimental results demonstrate the efficiency and effectiveness of our approach.

Extra cost of brain metastases (BM) in patients with non-squamous non-small cell lung cancer (NSCLC): a French national hospital database analysis

PurposeTo assess the incremental cost associated with the management of patients with primary non-squamous non-small cell lung cancer (NSCLC) with brain metastases at the time of diagnosis.MethodsData were extracted from the French Hospital medical information database (Programme de Médicalisation des Systèmes d’Information (PMSI)). Patients with non-squamous NSCLC were identified through a diagnosis of lung cancer and a prescription of bevacizumab or pemetrexed. All such patients hospitalised with lung cancer for the first time in 2013 and with metastases identified at the first hospitalisation were eligible. Two cohorts were identified, one with brain metastases (group B: n=971) and one with metastases at other sites (group A: n=1529). For each patient, total in-hospital medical resource consumption associated with the initial hospitalisation in 2013 and with any follow-up stays in the following 24 months was documented. Costs were attributed from official French national tariffs and expressed in 2017 euros.ResultsThe mean number of hospitalisations per patient in the 24-moth follow-up period was 17 in group A and 21 in group B. >99% of patients in both groups received chemotherapy. 58% of patients in group B and 13% in group A were managed by radiotherapy. 37% in group B and 24% in group A received palliative care. The associated cost was €2979 per patient-month for patients in group B and €2426 for patients in group A, representing a differential cost of €553 per month. Radiotherapy (+€164/month) and palliative care (+€130/month) were the principal drivers of the incremental cost.ConclusionsThe presence of brain metastases at the time of diagnosis of non-squamous NSCLC carries a significant burden, and ways of lowering this burden are needed.

The impact of a remote monitoring system of healthcare resource consumption in patients on automated peritoneal dialysis (APD): Asimulation study .

Aims: Remote monitoring (RM) can improve management of chronic diseases. We evaluated the impact of RM in automated peritoneal dialysis (APD) in a simulation study. Materials and methods: We simulated 12 patient scenarios with common clinical problems and estimated the likely healthcare resource consumption with and without the availability of RM (RM+ and RM– groups, respectively). Scenarios were evaluated 4 times by randomly allocated nephrologist-nurse teams or nephrologist-alone assessors. Results: The RM+ group was assessed as having significantly lower total healthcare resource consumption compared with the RM– group (36.8 vs. 107.5 total episodes of resource consumption, p = 0.002). The RM+ group showed significantly lower “unplanned hospital visits” (2.3 vs. 11.3, p = 0.005), “emergency room visits” (0.5 vs. 5.3, p = 0.003), “home visits” (0.5 vs. 5.8, p = 0.016), “exchanges over the telephone” (18.5 vs. 57.8, p = 0.002), and “change to hemodialysis” (0.5 vs. 2.5, p = 0.003). Evaluations did not differ between nephrologist-nurse teams vs. nephrologist-alone assessors. Conclusion: RM can be expected to reduce healthcare resource consumption in APD patients.

Optimal Resource Allocation for Uplink Data Collection in Nonorthogonal Multiple Access Networks.

Accommodating massive connectivity for Internet of Things (IoT) applications is considered an important goal of future 5G cellular systems. Nonorthogonal multiple access (NOMA), which enables a group of mobile users to simultaneously share the same spectrum channel for transmission, provides an efficient approach to achieve the goals of spectrum-efficient data delivery. In this paper, we consider an uplink transmission in a sensor network in which a group of smart terminals (e.g., sensors) use NOMA to send their collected data to an access point. We aim to minimize the total radio resource consumption cost, including the cost for the channel usage and the cost for all senors’ energy consumption to allow the sensors to complete their data delivery requirements. Specifically, we formulate a joint optimization of the decoding-order, transmit-power and time allocations to study this problem and propose an efficient algorithm to find the optimal solution. Numerical results are provided to validate our proposed algorithm and the performance advantage of our proposed joint optimization for the uplink data collection via NOMA transmission.

A note on resource allocation scheduling with position-dependent workloads

ABSTRACTIn this note, single machine scheduling with concurrent resource allocation and position-dependent workloads is studied. The aim is to find jointly the optimal sequence and the optimal resource allocation. A bicriteria analysis of the problem is provided where the first criterion is to minimize the scheduling cost (i.e. makespan, total completion time, total absolute differences in completion times, total absolute differences in waiting times) and the second criterion is to minimize the total resource consumption cost. It is proved that four bicriteria problems can be solved efficiently.

Towards Bandwidth Guaranteed Virtual Cluster Reallocation in the Cloud

Cloud data center traffic is experiencing a rapid growth as more and more data-intensive applications are required to process big data in a cloud data center. Although fat-tree networks own rich path multiplicity, and have been widely adopted as network topologies in cloud data center networks to transmit vast bisection bandwidth, they lead to bandwidth-related bottlenecks. To address this issue, in this paper, we propose a traffic-aware virtual cluster reallocation approach via biogeography-based optimization to allocate some reallocated virtual machines (VMs) as compact as possible with those VMs in the same virtual clusters. In order to validate our approach, we build a system model to perform a thorough evaluation of its performance. Experimental results show that our proposed approach outperforms six existed approaches in term of total transmission cost, total processing time, and total network resource consumption.

Single machine scheduling to minimise resource consumption cost with a bound on scheduling plus due date assignment penalties

We study a single-machine scheduling problem in a flexible framework, where both job processing times and due dates are decision variables to be determined by the scheduler. We consider the case where each of the job processing times is a convex decreasing function of the amount of non-renewable resource that is allocated to the corresponding processing operation. Moreover, we consider two of the more common due-date assignment methods. For each of the methods, our objective is to find a solution minimising the total resource consumption cost, given an upper bound on the value of the weighted number of tardy jobs plus due date assignment costs. Since the problem is known to be -hard, we focus on designing approximation algorithms.

Differential evolution algorithm for multi-project resource leveling problem

In this paper, the model of RLP which in the multi-project environment is expanded to the RLPMP using the minimum of the variance of total resource consumption within unit time for all projects as the optimization objective. In order to ensure the optimal individual will not be destroyed by operations such as crossover or variation and still maintain convergence of differential evolution algorithm, we try to introduce the elitist reservation to the differential evolution algorithm. Case analysis showed that the improved differential evolution algorithm can solve the model of RLPMP and then improve the balance of multi-project resources effectively.

Single-machine scheduling with learning effect and resource-dependent processing times in the serial-batching production

• Under the given resource allocation, the structural properties on job batching policies and batching sequencing are proposed. • An optimal batching policy is derived for the special case. • An effective hybrid GSA–TS algorithm is developed to solve the studied problem. In this paper, we study a single machine scheduling problem by simultaneously considering the processing method of serial-batching, learning effect, resource-dependent processing times, and setup operations. We consider minimizing the makespan as the objective of the studied problem under the constraint that the total resource consumption does not exceed a given limit. For the special case where the resource allocation is given, we first propose the structural properties for job batching policies and batching sequencing, and an optimal batching policy is derived based on these properties. Then, we develop a novel hybrid GSA–TS algorithm which combines the Gravitational Search Algorithm (GSA) and the Tabu Search (TS) algorithm to solve the general case. Computational experiments with different scales show the effectiveness and efficiency of the proposed algorithm.

A note on flow-based formulations for solving resource constrained scheduling problems

The resource constrained scheduling problem involves the scheduling of a number of activities over time, where each activity consumes one or more resources per time period. For a feasible solution to exist, the total resource consumption per time period must not exceed the available resources. In addition, the order in which activities may be scheduled is determined by a precedence graph. In this paper, valid inequalities proposed for the resource flow-based formulation in previous studies are investigated to determine what effect they may have on computing times. It is shown empirically that improved computing times may be obtained if these valid inequalities are, in fact, omitted from the resource ow-based formulation. In addition, a heuristic is proposed for the generation of initial starting solutions and for estimating the extent of the scheduling horizon which, in turn, is required to calculate the latest starting times of activities. The computational results are based on well-known problem test instances as well as new randomly generated problem instances. Keywords: Scheduling, mixed integer linear programming, valid inequalities

Minimizing total resource consumption and total tardiness penalty in a resource allocation supply chain scheduling and vehicle routing problem

The increase in the consumption of resources in the past decade has caused an increase in the interest of the international academic community in the challenges to reduce such rapid consumption of resources. Every year, many researchers propose different methods by which resource consumption can be reduced. Material, equipment, and process refinement are vivid examples of such efforts. While these innovations can be very helpful, in several cases, however, they can be very costly and greatly time-consuming. In addition, decision-makers tend to tackle the problem of resource consumption, while maintaining the proper level of service. Thus, in this paper, we propose a new bi-objective mathematical model by which we can reduce the consumption of resources and energy, as well as decrease the tardiness penalty in a supply chain scheduling and vehicle routing problem. The model demonstrates that finding the proper production (assembly) sequence, assignment of orders to vehicles and vehicle routing, will enable us to reduce resource consumption. A new Non-dominated Sorting Genetic Algorithm based on shaking and local search strategies of Variable Neighborhood Search algorithm is also developed to solve the proposed problem. Several criteria are introduced and defined to assess the performance of the proposed algorithm. Results demonstrate the out-performance of the proposed algorithm compared with the classic non-dominated sorting genetic algorithm II. We also propose a method that allows decision makers to make an informed decision to choose a proper sequence of jobs and routes that create a trade-off between resource consumption and the tardiness penalty.

Identifying High Resource Consumption Areas of Assembly-Centric Manufacturing in the United States.

This paper examines supply chain value added in the US for producing assembly-centric products, which includes machinery, computers, electronics, and transportation equipment, and determines whether costs are disproportionally distributed. The implication being that reductions in resource consumption in some cost areas can disproportionally reduce total resource consumption. Efforts to develop and disseminate innovative solutions to improve efficiency can, therefore, be targeted to these high cost areas, resulting in larger efficiency improvements than might otherwise be achieved. An input-output model is used for this examination and is combined with labor data and data on assets. The top 20 industries, occupations, and industry occupation combinations contributing to production are identified. A sensitivity analysis is conducted on the model using Monte Carlo simulation. The results confirm that costs are disproportionally distributed, having a Gini coefficient of 0.75 for value added and for compensation it is 0.86. Wholesale trade, aircraft manufacturing, and the management of companies and enterprises were the industries with the largest contribution to assembly-centric manufacturing, even when including imports. Energy in the form of electricity and natural gas were discussed separately, but would rank 8th if compared to the industry rankings. In terms of occupation activities, team assemblers, general and operations managers, and sales representatives were the largest occupations. Public entities might use this model and results to identify efficiency improvement efforts that will have the largest impact on industry per dollar of expenditure.

Linking energy-sanitation-agriculture: Intersectional resource management in smallholder households in Tanzania

In order to create sustainable systems for resource management, residues from cooking and ecological sanitation (EcoSan) can be employed in recycling-driven soil fertility management. However, the link between energy, sanitation, and agricultural productivity is often neglected. Hence, the potential self-sufficient nature of many smallholdings in sub-Saharan Africa is underexploited. ObjectiveTo compare those cooking and sanitation technologies most commonly used in north-western Tanzania with locally developed alternatives, with respect to (i) resource consumption, (ii) potential to recover resources, and (iii) environmental emissions. This study examines technologies at the household level, and was carried out using material flow analysis (MFA). The specific bioenergy technologies analysed include: three-stone fires; charcoal burners; improved cooking stoves (ICS), such as rocket and microgasifier stoves; and biogas systems. The specific sanitation alternatives studied comprise: pit latrines; two approaches to EcoSan; and septic systems. ResultsThe use of ICS reduces total resource consumption; using charcoal or biogas does not. The residues from microgasifiers were analysed as having a substantial recovery potential for carbon (C) and phosphorus (P). The fact that input substrates for biogas digesters are post-agricultural in nature means that biogas slurry is not considered an ‘untapped resource’ despite its ample nutrient content.Exchanging pit latrines for water-based sanitation systems places heavy pressure on already scarce water resources for local smallholders. In contrast, the implementation of waterless EcoSan facilities significantly promotes nutrient recovery and reduces environmental emissions, particularly through greenhouse gas emission and nutrient leaching. ConclusionsRecycled outputs from the triple energy-sanitation-agriculture nexus display complementary benefits: residues from cooking can be used to restore organic matter in soils, while sanitation residues contribute to fertilisation. The combination of microgasifiers and EcoSan-facilities is the most appropriate in order to simultaneously optimise resource consumption, reduce environmental impacts, and maximise recycling-based soil management in smallholder farming systems.

Single machine due window assignment resource allocation scheduling with job-dependent learning effect

This paper deals with a single machine common due window assignment resource allocation scheduling problem with job-dependent learning effect. The objective is to find the due window starting time, a due window size, resource allocation and a job schedule such that total resource consumption cost is minimized subject to a cost function associated with the window location, window size, earliness, tardiness and makespan is less than or equal to a fixed constant number. We show that the problem can be solved in polynomial time. Some extensions of the problem are also given.

Uniform Parallel-Machine Scheduling for Minimizing Total Resource Consumption With a Bounded Makespan

This paper examines the uniform parallel-machine scheduling problem in which the objective aims to minimize the total resource consumption (TRC) with a bounded makespan. A matheuristic is proposed to deal with this strongly NP-hard problem. The performance of the proposed matheuristic is compared with that of the state-of-the-art particle swarm optimization (PSO) meta-heuristic and the lower bound (LB) of TRC on a set of benchmark instances. Computational results show that the proposed matheuristic significantly outperforms the PSO meta-heuristic and its solution is very close to the tight LB. Given the critical need for environmental protection, this paper provides an effective and efficient algorithm for diminishing the gap between the theoretical progress of scheduling and the practical need for environmental protection.

An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times

The scheduling problems with controllable processing times (CPT) are commonly encountered in some manufacturing industries. CPT means the processing times of operations can be controlled by allocating additional resources. However the flexible job-shop scheduling problem (FJSP) with CPT is seldom explored due to its essential complexity. In addition, FJSP usually involves several conflicting objectives in the practical production. Therefore, the multi-objective FJSP with CPT (MOFJSP-CPT) is highly important in terms of theoretical research and practical application. Thus, this paper focuses on the MOFJSP-CPT. Firstly, this study formulates a mathematical model with the objectives of minimizing both the makespan and the total additional resource consumption. Then, to solve this problem, we propose a new multi-objective discrete virus optimization algorithm (MODVOA) with a three-part representation for each virus, an improved method for yielding the initial population, and an ensemble of operators for updating each virus. To further improve the exploitation, a problem-specific exploitation mechanism is implemented in the later stage of the search process. Finally, to evaluate the effectiveness of the MODVOA, the MODVOA is compared with other well-known multi-objective evolutionary algorithms including NSGA-II and SPEA2. Experimental results on randomly generated instances and a real-world case demonstrate that the proposed MODVOA can achieve a better performance than other algorithms for solving the MOFJSP-CPT.

Comparative life cycle assessment and economic analysis of typical flue-gas cleaning processes of coal-fired power plants in China

The life cycle environmental impacts of widely used flue-gas cleaning processes, including limestone-gypsum wet flue-gas desulfurization (FGD), selective catalytic reduction denitration (SCR) and electrostatic precipitators (ESP), are compared. The abbreviations FGD, SCR and ESP in this article refer in particular to the above listed processes. Energy consumption, resource consumption and emission inventories of each life cycle phase are established. The potentials of five environmental impact categories, namely, global warming, acidification, nutrient enrichment, photochemical ozone formation, soot and ashes are finally obtained. The current paper reveals that the total energy consumption and resource consumption are dominated by the process operation. The three processes are compared and it is found that to achieve equal environmental burden reductions, the SCR process consumes more energy and approximately the same amount of air and inert rock as the FGD. But the water consumption of the FGD is much higher than the SCR. The ESP process consumes both the least energy and the least resource in general. The economic assessment indicates that the performance of the ESP process tends to be the best and the FGD follows when equally invested.

Scheduling jobs with deterioration effect and controllable processing time

This article considered the single machine scheduling with controllable processing time (resource allocation) and deterioration effect concurrently. It discussed the minimization of three objectives, which involve the weighted sum of the makespan and the total resource consumption cost, the total resource consumption cost under the condition that the makespan (total flow time) is restricted to a fixed constant and the optimal resource allocation and the optimal job sequence is what we need to make decision. Considering the makespan constraint, it proved that these problems can be solved in polynomial time. A special case of the last problem can be solved in polynomial time with respect to the total flow time constraint.

Single-machine past-sequence-dependent setup times scheduling with resource allocation and learning effect

This paper addresses single-machine scheduling problem with resource allocation and learning effect in the background of past-sequence-dependent (p-s-d) setup times. In the proposed model of this paper, the actual job processing times are dependent on learning effect and the amount of resource allocated, and the setup times are proportional to the length of the already processed jobs. The resource function used here is a general convex one. The optimal job sequence and the optimal amount of resource allocated to each job are determined jointly for the objective function yielded by a combination of the total completion time, total absolute differences in completion times, and the total resource consumption. Besides, we also discuss some extension and special cases of this problem. It is shown that all the problems under study are polynomially solvable while the complexity results are different.

Exergo-ecological and economic evaluation of a nuclear power plant within the whole life cycle

The multi-criteria analysis of different power technologies takes into account TEC (thermo-ecological cost); direct and cumulative emissions; and economic evaluation. The environmental and ecological comparison of the planned nuclear power plant with the existing conventional ones (coal and gas plants) requires the evaluation of the whole life cycle of electricity generation. The main cause of the imperfection of nuclear fuel cycle appears in the stage of conversion, enrichment and nuclear fuel fabrication. TEC analysis takes into account all connected process starting from natural resources extracting, through all related processes influencing product generation, up to disposal or recycling. For this reason, TEC and exergy efficiency evaluate the nuclear fuel life cycle. TEC expresses the total (cumulative) exergy consumption of non-renewable resources burdening the analysed product, which means exergy assembly of the whole cycle of this product. TEC also takes into account the additional non-renewable exergy consumption required for environmental losses mitigation caused by the harmful emissions. A significant amount of GHG (greenhouse gasses) emissions is not covered by the direct analysis since the CO2 emissions also occur in the stages of mining and transportation of fuel production. The nuclear power units are characterized by lower GHG emissions than the coal and gas technologies, for which the GHG emissions is on a comparable level. Additionally, the economic analysis revealed that the investment cost of the nuclear power plant is significantly higher than those of coal or gas power plant the unit cost of electricity generated by the nuclear installation could be about twice lower than from other technologies. It results from an operating cost: the cost of fuel and the fee of direct GHG emissions are higher for coal and gas technology than for nuclear power plant. The nuclear power plants seem to be the competitive technologies for the coal or gas installation and should be taken into account while planning the policy for energy generation.