Job Income Research Articles

Queueing with future information

We study an admissions control problem, where a queue with service rate 1 - p receives incoming jobs at rate λ ε (1? p , 1), and the decision maker is allowed to redirect away jobs up to a rate of p , with the objective of minimizing the time-average queue length. We show that the amount of information about the future has a significant impact on system performance, in the heavy-traffic regime. When the future is unknown, the optimal average queue length diverges at rate ~ log 1/1- p 1/1-λ, as λ → 1. In sharp contrast, when all future arrival and service times are revealed beforehand, the optimal average queue length converges to a finite constant, (1 - p )/ p , as λ → 1. We further show that the finite limit of (1 - p )/ p can be achieved using only a finite lookahead window starting from the current time frame, whose length scales as O(log 1/1-λ), as λ → 1. This leads to the conjecture of an interesting duality between queuing delay and the amount of information about the future.

OL-DEC-MDP Model for Multiagent Online Scheduling with a Time-Dependent Probability of Success

Focusing on the on-line multiagent scheduling problem, this paper considers the time-dependent probability of success and processing duration and proposes an OL-DEC-MDP (opportunity loss-decentralized Markov Decision Processes) model to include opportunity loss into scheduling decision to improve overall performance. The success probability of job processing as well as the process duration is dependent on the time at which the processing is started. The probability of completing the assigned job by an agent would be higher when the process is started earlier, but the opportunity loss could also be high due to the longer engaging duration. As a result, OL-DEC-MDP model introduces a reward function considering the opportunity loss, which is estimated based on the prediction of the upcoming jobs by a sampling method on the job arrival. Heuristic strategies are introduced in computing the best starting time for an incoming job by each agent, and an incoming job will always be scheduled to the agent with the highest reward among all agents with their best starting policies. The simulation experiments show that the OL-DEC-MDP model will improve the overall scheduling performance compared with models not considering opportunity loss in heavy-loading environment.

A job submission manager for large-scale distributed systems based on job futurity predictor

As compared with supercomputers and PCs, the higher rate of unsuccessful job execution in today's distributed and large systems like clusters and grids is a significant reason behind squandering of their resources. Although many approaches have been proposed in order to make these environments more fault tolerant, their great overhead convinces the researchers to look for preventive methods. In this work, we employ a job futurity predictor to manage the arriving jobs efficiently. To this end, a novel meta-scheduler sub-component called Job Submission Manager JSM is proposed. The main role of JSM is to filter the incoming jobs according to some parameters such as current system load, job failure probability. The experimental results based on two different modelling approaches indicate that this managing component can effectively influence the system throughput and increase the utilisation of computing resources.

Matrix-geometric solution for semi-open queuing network model of autonomous vehicle storage and retrieval system

In this paper, we model the autonomous vehicle storage and retrieval system (AVS/RS) as a semi-open queuing network (SOQN) and apply a matrix-geometric method (MGM) for analyzing it. An AVS/RS is an automated material handling system for the high-rise pallet storage area of a warehouse and allows pallets to be stored and retrieved quickly and efficiently from their storage locations. It is an alternative to the traditional crane-based AS/RS (automated storage and retrieval system). A combination of lifts and autonomous vehicles store pallets into and retrieve them out of their respective rack storage locations. The crane based AS/RS typically utilizes aisle-captive, mast-mounted cranes that can access any storage location in an aisle via horizontal movement of the mast and vertical movement of the crane on the mast.In an SOQN, it is assumed that an arriving job or customer is paired with another device and the two visit all the stations that must process the job in the appropriate sequence. After all operations are completed on the job, it exits the system, but the device returns back to a device pool and awaits the next customer. Sometimes a job may have to wait for a device to arrive at the pool or a device may have to wait for a job to arrive. Although closed queuing networks (CQNs) and open queuing networks (OQNs) model systems that require pairing of an incoming job with a device, unlike the SOQN, they ignore the time that a device waits for a job or the time that a job waits for a device.In the context of an AVS/RS, the jobs correspond to storage/retrieval (S/R) transaction requests and the autonomous vehicles (AVs) correspond to the devices. Because an AV may sometimes have to wait for an S/R transaction or vice versa, we model the AVS/RS as an SOQN. We build the queuing network by deriving general travel times of pre-defined servers. We model the AVS/RS system as a single-class, multiple-server, SOQN. Then, we solve the network using the MGM and obtain its key performance measures. We apply the MGM technique for solving the SOQN model to a warehouse in France that uses AVS/RS.

Decay of tails at equilibrium for FIFO join the shortest queue networks

In join the shortest queue networks, incoming jobs are assigned to the shortest queue from among a randomly chosen subset of $D$ queues, in a system of $N$ queues; after completion of service at its queue, a job leaves the network. We also assume that jobs arrive into the system according to a rate-$\alpha N$ Poisson process, $\alpha<1$, with rate-1 service at each queue. When the service at queues is exponentially distributed, it was shown in Vvedenskaya et al. [Probl. Inf. Transm. 32 (1996) 15-29] that the tail of the equilibrium queue size decays doubly exponentially in the limit as $N\rightarrow\infty$. This is a substantial improvement over the case D=1, where the queue size decays exponentially. The reasoning in [Probl. Inf. Transm. 32 (1996) 15-29] does not easily generalize to jobs with nonexponential service time distributions. A modularized program for treating general service time distributions was introduced in Bramson et al. [In Proc. ACM SIGMETRICS (2010) 275-286]. The program relies on an ansatz that asserts, in equilibrium, any fixed number of queues become independent of one another as $N\rightarrow\infty$. This ansatz was demonstrated in several settings in Bramson et al. [Queueing Syst. 71 (2012) 247-292], including for networks where the service discipline is FIFO and the service time distribution has a decreasing hazard rate. In this article, we investigate the limiting behavior, as $N\rightarrow \infty$, of the equilibrium at a queue when the service discipline is FIFO and the service time distribution has a power law with a given exponent $-\beta$, for $\beta>1$. We show under the above ansatz that, as $N\rightarrow\infty$, the tail of the equilibrium queue size exhibits a wide range of behavior depending on the relationship between $\beta$ and $D$. In particular, if $\beta>D/(D-1)$, the tail is doubly exponential and, if $\beta<D/(D-1)$, the tail has a power law. When $\beta=D/(D-1)$, the tail is exponentially distributed.

Load Balancing Approach for Scheduling Sequential Task in Grid Computing Environment

In grid computing environment, the efficiency of computing node is affected by several factors such as node utilization, allocation of jobs etc. The incoming job is allocated to appropriate node in such a way that the node utilization is maximized and a well-balanced load across all the participating computing nodes that enhances the overall performance of grid computing. This paper presents an amended hybrid approach for scheduling sequential task. The proposed approach uses combination of first-come-firstserved (FCFS) and genetic algorithm (GA). A sliding-window technique is presented to initiate alteration between the FCFS and GA, to offers a rapid task assignment. For GA we initially generate random population and use straightforward encoding. The proposed method is evaluated in the terms of makespan value and node utilization with a varying set of simulation cases and parameters after then it is compared with a well design first-come-first-server (FCFS) and hybrid genetic algorithm (HGA). Experimental results have shown significant improvement compared to the both FCFS and HGA algorithms. The result gives minimized makespan value with increased node utilization for both homogeneous and heterogeneous types of nodes.

Part-Time Versus Full-Time Work: The Case of Nurses in Spain

Nursing has been described as a stressful occupation with nursing staff reporting high levels of job dissatisfaction in many countries. For various reasons an interesting paradox exists; on the one hand there is a global shortage of nurses which has potential adverse effects on nursing staff job satisfaction and the quality of patient care. On the other hand, many nurses opt for working on a part time basis, which adds to the shortage issue. Some nursing staff have opted to work part-time by choice or out of necessity while some full-time nursing staff would prefer to work part-time. This research explores antecedents and factors related to the decisions of nursing staff to work part time with the intention of identifying reasons that might be addressed and result in their choosing to work full-time and reduce nursing shortages. Data were collected from 2094 nurses in Spain using anonymously completed questionnaires, of which 290 indicated they were currently working part-time. Respondents indicated how important a role in their decision to work part time was played by each of the items. Most common reasons for working part time were: caring for others, personal health issues, losing a full-time job, staying active in the profession, and exploring a new career or occupation. Factor analysis of 15 items yielded Part-time versus full-time work: The case of nurses in Spain 4 a five-factor solution: job loss, career and income benefits, personal needs (caring for others, health issues), exploring new career options, and the unavailability full-time jobs. Full-time and part-time nursing staff were then compared on a number of personal demographic and work situation characteristics, job demands, sources of support, work outcomes and indicators of psychological well-being. Generally, part-time nursing staff was younger, had fewer years of nursing-related tenure, fewer job resources, and indicated lower levels of job involvement, affective commitment and work engagement. Part time and full-time nurses were similar on levels of work and extra-work social support, burnout, psychological well-being and accident propensity. Efforts to encourage and support the transition of part-time nursing staff to full-time nursing staff are offered.

SCH_ACR and SCH_LD based Job Scheduling Algorithm in Grid Environment

To achieve the promising potentials by using tremendous distributed resources, effective and efficient scheduling algorithms are fundamentally important. Scheduling such applications is challenging because target resources are heterogeneous, their load and availability varies dynamically. Previous parallel system was assumed to be organized with homogeneous platform and connected via memory, bus, or LAN. But today its platform is heterogeneous and connected via Internet so each platform has different ability of computation performance and different network bandwidth. So, traditional list scheduling algorithms are inefficient to current parallel system. This research paper proposes and discusses in detail, the two new algorithms for Job scheduling on computational Grids so that the jobs are executed in minimum time and also all nodes of Grid execute equal load relative to their executing power. The main objective of this research paper is to allocate all the incoming jobs to the available computing power.

Employability of Psychology Graduates and their Job Satisfaction in Turkey: An Online Survey

The interest in studying psychology has dramatically increased in the recent decades in Turkey. However, only 60% of psychology graduates work in jobs related to psychology. Moreover, there is no data on employability and job distribution of psychology graduates or on their job satisfaction. In the current study, the authors' first aim was to assess the employability of psychology graduates, and their job satisfaction in Turkey. Secondly, they examined the specific advantages of having a postgraduate degree over a bachelor's degree. Using an online survey they compared psychologists with and without postgraduate degrees on different aspects of employability as well as their job satisfaction, income, and promotion opportunities. Results showed that psychology graduates were mostly working in clinical and educational settings, and about half of them had a postgraduate degree. The majority of psychologists were somewhat satisfied with their jobs. Additionally, the authors found that having a postgraduate degree, compared to a bachelor's degree, meant less time spent on job searching, a higher salary, and higher job satisfaction. Findings are discussed in relation to teaching of psychology and challenges that face psychology graduates regarding employability in Turkey.

Health Insurance in California, Its Effect on Public Health Nursing

Health insurance coverage and the means by which it is paid have been topics of intense interest in recent years, but in the United States, creation of a uniform system for provision of medical care has been debated for nearly a century. During the Great Depression, before large group insurance plans, workers who formerly had been able to adequately support their families found themselves without employment or in low income jobs that barely put food on the table and a roof over their heads. Medical care was a luxury they could not afford. Health professionals suffered the effects of the economy too. Published in Public Health Nursing in 1936, this paper reflects a time period when the ravages of the Great Depression were manifest. California had received an influx of poor, migrant workers from other states hoping to provide for their families as pickers, canners, and manual laborers. The author, Marion E. Russell, described a 1935 health insurance proposal to cover all state residents. Selected excerpts illustrate differences in philosophy still evident in current considerations of national health care reform, particularly as related to mandated coverage. Russell worked in the State Relief Administration in San Francisco.

Performance Improvement in a Multi Cluster using a Modified Scheduling and Global Memory Management with a Novel Load Balancing Mechanism

In Cluster Computing Environment the data latency time has significant impact on the performance when the data is accessed across clusters. In this case, streamlining data access through the usage of the memory management technique with a proper scheduling mechanism will improve the performance of the entire operation. Memory management becomes a prerequisite criterion while handling applications that require large volume of data in various scientific applications. If memory management is not properly handled the performance will have a proportional degradation, even if the other factors perform to the maximum possible levels. Hence it is critical to have a fine memory management technique. The existing scheduling algorithms consider only data availability as the sole criterion in allotting an incoming job to a node in a cluster. But this process would not yield optimum performance because bandwidth is also a major factor in determining the performance level. So to overcome this problem a new scheduling algorithm is what required. Load balancing is a key technique used to improve the performance of cluster application by utilizing machines to the full extent without any idle or underutilized resources. We have tested our CWA load balancing algorithm for face recognition system and results are encouraging.

On the Improvement of Grid Resource Utilization: Preventive and Reactive Rescheduling Approaches

One of the key motivations of computational and data Grids is the ability to make coordinated use of heterogeneous computing resources which are geographically dispersed. However, the provision of Quality of Service (QoS) to Grid users is still a challenge that needs the attention of the research community. Reservation of resources in advance has been proposed as a way of providing QoS guarantees but they may not always be possible. For this reason, this work focuses on meta-scheduling of jobs in advance as a way of enhancing the provision of QoS. Thereby, jobs are scheduled some time before they are actually executed, but no resource is physically reserved. One of the drawbacks of this scenario is that fragmentation may appear in resources (free time slots but not large enough to execute a job) which leads to poor resource utilization. For that reason, two techniques have been developed to tackle poor resource utilization, whose main idea consists of rescheduling already scheduled jobs so that a new incoming job can be allocated. These rescheduling techniques have been implemented within a middleware that supports meta-scheduling in advance, which relies on the GridWay meta-scheduler. Finally, these proposals have been tested using a real testbed involving heterogeneous computing resources distributed across different national organizations, with different experiments showing their efficiency.

Relative Income and Job Satisfaction: Evidence from Australia

Using the first six waves of the Household, Income and Labour Dynamics in Australia (HILDA) Survey dataset, a linear fixed effects model is used to examine the link between relative income and overall job satisfaction in Australia. In this paper, relative income is constructed using cell average by age group, gender and education level. The findings indicate that (i) relative income has a significant negative impact on overall job satisfaction for men but not for women; and (ii) for the whole sample and for men, income comparisons are asymmetric and upwards, meaning that the loss in overall job satisfaction by the poor from having an income below that of their reference group is significantly greater than the gain by the rich from knowing that they earn above that of their reference group. Overall, the evidence found is consistent with Dueseneberry’s hypothesis that relative income matters and comparison effect is asymmetric and mostly upwards.

Design of Stochastic Simulator for Analyzing the Impact of Scalability on CPU Scheduling Algorithms

Process scheduling with scalable performance is an issue in computer system. Scalability of scheduling algorithm is its ability to don’t decrease the performance when large processes are under run. The performance of job scheduling policies strongly depends on the properties of the incoming jobs. In this paper, we have analyzed the impact of scalability on different CPU scheduling algorithms with reference to average waiting time, average turnaround time and average response time to determine which algorithm is most suitable for uniprocessor environment. The burst time, arrival time and priority is randomly generated using exponential probability distribution and the performance of all algorithms has been evaluated with reference to arrival time or without arrival time. We use a simulative approach to evaluate the performance and scalability of each algorithm with reference to different number of processes.

An Adaptive Scheduling System for Computational Grid using Autonomic Computing

Grid computing provides an environment to be share software and hardware resources.Ontheonehand, environmentofGridcomputingis inherently large, complex, heterogeneous and dynamic and its state changes over time, on the other hand, incoming job to Grid show unstable behavior, which before that is not known and changes over time. As regards that scheduling in Grid has a vital role in overall system performance, the need to scheduling methods to adapt themselves to conditions in Grid, and regarding current state of the environment and jobs the scheduler must be able to make decisions. In this article, for the scheduling of computational Grid, we have used Autonomic Computing principles to enable Grid scheduler dynamically adapt itself totheenvironmentandincreaseefficiency. Autonomic computing systems are inspired by biologically systems which their goal is to manage themselves with minimal involvement of managers. Autonomic computing is suitable for a computational Grid because of the large, heterogeneous, dynamic and autonomous nature of the Grid. The proposed method in this study, in terms of makes pan, execution time and resource utilization has shown higher performance, compared to other methods and related numerous experiments. General Terms Adaptive Algorithms, Grid Scheduling, Autonomic Grid.

Results of Arthroscopic Labral Reconstruction of the Hip in Elite Athletes (SS-39)

Results of Arthroscopic Labral Reconstruction of the Hip in Elite Athletes (SS-39)

Coalitions within the Egyptian Banking Sector: Catalysts of the Popular Revolution

Among the triggers of the Egyptian Revolution are the sentiments of resentment against the convoluted alliances between private businesses and policymakers that deprived the masses of their fair share of the high GDP growth. But does this indictment extend to the Egyptian banking sector? Based on a field survey and a dataset of 3218 business loans made by 33 banks during 1999–2010, this research differentiates between growth catalysts and crony coalitions within the Egyptian banking sector. The results of the Generalized Estimating Equations reveal that preferential lending to politically-connected businesses has a negative impact on employment and income distribution. Loans to small and medium enterprises and public firms help enhance income distribution and job generation, albeit that the soft-budget constraint on loans to public firms deters growth. The paper presents some policy recommendations that could help exorcise patrimonialism and clientelism and enhance growth alliances within the sector that controls most of the credit flow in the Egyptian economy. The study is not only of grave importance to the Egyptian nation whose members are actively engaged in refurbishing its institutional framework, but is of equal significance to other emerging economies that are keen to install equity, political stability and socioeconomic prosperity.

Stochastic bounds for randomized load balancing

Randomized load balancing is a cost efficient policy for job scheduling in parallel server queueing systems whereby, with every incoming job, a central dispatcher randomly polls some servers and selects the one with the smallest queue. By exactly deriving the jobs' delay distribution in such systems, in explicit and closed form, Mitzenmacher [5] proved the socalled 'power-of-two' result, which states that by randomly polling only two servers yields an exponential improvement in delay over randomly selecting a single server. Such a fundamental result, however, was obtained in an asymptotic regime in the total number of servers, and does do not necessarily provide accurate estimates for practical finite regimes with small or moderate number of servers. In this paper we obtain stochastic lower and upper bounds on the jobs' average delay in non-asymptotic regimes, by borrowing ideas for analyzing the particular case of the Join-the-Shortest-Queue (JSQ) policy. Numerical illustrations indicate not only that the obtained bounds are remarkably accurate, but also that the existing exact but asymptotic results can be largely misleading in some finite regimes.

Improved Task Graph-based Parallel Data Processing for Dynamic Resource Allocation in Cloud

In recent years large-set parallel data processing has gained quantum as one of the predominant applications of Infrastructure-as-a-Service (IaaS) clouds. Data processing frameworks like Google's MapReduce and its open source implementation Hadoop, Microsoft's Dryad and so on are currently in use for parallel data processing in cloud-based companies. But the problem with them is that they are designed for homogeneous environments like clusters and disregard the dynamic and heterogeneous nature of a cloud. As a result, allocation and de-allocation of compute nodes at runtime is ineffective thereby increasing processing time and cost. In this paper we present our approach towards parallel data processing exploiting dynamic resource allocation in IaaS clouds. Our architecture ensures parallel data processing using Directed Acyclic task graph. To reduce the latency and to improve throughput, load balancing is introduced in the architecture. Incoming jobs are divided into tasks that are assigned to different types of virtual machines that are dynamically instantiated and terminated during job execution.

Le degré de déqualification professionnelle et son effet sur les revenus d'emploi des femmes immigrantes membres d'une minorité visible du Québec

In recent decades, the increased participation of women in the labour market and the rise in the number of landed immigrants in Canada have largely contributed to transforming the employment market. However, several studies have shown that women, immigrants, and members of visible minority groups continue to make up the most vulnerable segments of the job market. The issue we want to address in this article speaks particularly to outdated skills, which means working in a job that requires an academic level below the one held by that individual. In fact, an individual who is too qualified for a position is not fully using his or her human capital, which constitutes a loss for the individual as well as for society. The author's objective is to verify if the skills of immigrant women who are members of a visible minority in Québec are more at risk of becoming outdated than those of men and women from other groups, resulting in a cross-over between immigrant status and belonging to a visible minority. She also wants to analyze the impact of outdated skills on job income in these different groups in order to identify which group is most penalized by outdated skills in the matter of employment income. Her results, based on the 2006 Census files, show that immigrant women who are members of a visible minority in Québec are indeed the most affected by outdated skills and have, as a general rule, the lowest average weekly employment income of all groups. However, this group does not incur the highest income loss associated with outdated skills.