Job-to-Job Flows and Wage Dynamics in France and Italy

Job-to-job Flows and Wage Dynamics in France and Italy

SSRN Electronic Journal ◽

10.2139/ssrn.3659962 ◽

2020 ◽

Author(s):

Clemence Berson ◽

Marta de Philippis ◽

Eliana Viviano

Keyword(s):

Job Flows ◽

Wage Dynamics

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Are gross job flows in Australia sensitive to exchange rate fluctuations?

International Journal of Environment Workplace and Employment ◽

10.1504/ijewe.2007.019282 ◽

2007 ◽

Vol 3 (3/4) ◽

pp. 248

Author(s):

Bill Mitchell ◽

Jenny Myers

Keyword(s):

Exchange Rate ◽

Job Flows ◽

Exchange Rate Fluctuations

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Robust scheduling for flexible processing networks

Advances in Applied Probability ◽

10.1017/apr.2017.14 ◽

2017 ◽

Vol 49 (2) ◽

pp. 603-628 ◽

Cited By ~ 9

Author(s):

Ramtin Pedarsani ◽

Jean Walrand ◽

Yuan Zhong

Keyword(s):

Queueing Networks ◽

Complex Structure ◽

Job Flows ◽

Heterogeneous Servers ◽

Robust Scheduling ◽

System Parameters ◽

Balanced Allocation ◽

Service Rates ◽

Length Changes ◽

Processing Networks

Abstract Modern processing networks often consist of heterogeneous servers with widely varying capabilities, and process job flows with complex structure and requirements. A major challenge in designing efficient scheduling policies in these networks is the lack of reliable estimates of system parameters, and an attractive approach for addressing this challenge is to design robust policies, i.e. policies that do not use system parameters such as arrival and/or service rates for making scheduling decisions. In this paper we propose a general framework for the design of robust policies. The main technical novelty is the use of a stochastic gradient projection method that reacts to queue-length changes in order to find a balanced allocation of service resources to incoming tasks. We illustrate our approach on two broad classes of processing systems, namely the flexible fork-join networks and the flexible queueing networks, and prove the rate stability of our proposed policies for these networks under nonrestrictive assumptions.

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