Experimental Analysis of Algorithms for Coflow Scheduling

Modern data centers face new scheduling challenges in optimizing job-level performance objectives, where a significant challenge is the scheduling of highly parallel data flows with a common performance goal (e.g., the shuffle operations in MapReduce applications). Chowdhury and Stoica introduced the coflow abstraction to capture these parallel communication patterns, and Chowdhury et al. proposed effective heuristics to schedule coflows efficiently. In our previous paper, we considered the strongly NP-hard problem of minimizing the total weighted completion time of coflows with release dates, and developed the first polynomial-time scheduling algorithms with O(1)-approximation ratios. In this paper, we carry out a comprehensive experimental analysis on a Facebook trace and extensive simulated instances to evaluate the practical performance of several algorithms for coflow scheduling, including the approximation algorithms developed in our previous paper. Our experiments suggest that simple algorithms provide effective approximations of the optimal, and that the performance of our approximation algorithms is relatively robust, near optimal, and always among the best compared with the other algorithms, in both the offline and online settings.Comment: 29 pages, 8 figures, 11 table

Shop scheduling with availability constraints

Scheduling Theory studies planning and timetabling of various industrial and human activities and, therefore, is of constant scientific interest. Being a branch of Operational Research, Theory of Scheduling mostly deals with problems of practical interest which can be easily (from a mathematical point of view) solved by full enumeration and at the same time usually require enormous time to be solved optimally. Therefore, one attempts to develop algorithms for finding optimal or near optimal solutions of the problems under consideration in reasonable time. If the output of an algorithm is not always an optimal solution then the worst-case analysis of this algorithm is undertaken in order to estimate either a relative error or an absolute error that holds for any given instance of the problem. Scheduling problems which are usually considered in the literature assume that the processing facilities are constantly available throughout the planning period. However, in practice, the processing facility, e.g. a machine, a labour, etc. can become non-available due to various reasons, e.g. breakdowns, lunch breaks, holidays, maintenance work, etc. All these facts stimulate research in the area of scheduling with non-availability constraints. This branch of Scheduling Theory has recently received a lot of attention and a considerable number of research papers have been published. This thesis is fully dedicated to scheduling with non-availability constraints under various assumptions on the structure of the processing system and on the types of non-availability intervals

Taking the High Road: How the City of New York Can Create Thousands of Good Retail Jobs Through Neighborhood Rezoning

In 2014, Mayor de Blasio announced a plan to redevelop multiple neighborhoods across the five boroughs through an elaborate rezoning effort. Despite the plan's unprecedented scale and the impact it will undoubtedly have on our landscape, little if any attention has yet to be paid to the issue of jobs -- specifically, the quality of permanent retail jobs in stores and businesses that will occupy the ground floors of many new apartment buildings and developments throughout the rezoned areas. These areas include East New York, Brooklyn, Long Island City, Queens, the Jerome Avenue Corridor in The Bronx, Flushing West in Queens, East Harlem in Manhattan, and the Bay Street Corridor in Staten Island. Mayor de Blasio's plan to rezone neighborhoods offers enormous potential for building a better retail economy in our city. This is the first report of its kind to offer a policy roadmap for how the de Blasio administration and local communities can together ensure that the thousands of jobs created in rezoned neighborhoods are high-road retail jobs with living wages and full-time hours for city residents

Four decades of research on the open-shop scheduling problem to minimize the makespan

One of the basic scheduling problems, the open-shop scheduling problem has a broad range of applications across different sectors. The problem concerns scheduling a set of jobs, each of which has a set of operations, on a set of different machines. Each machine can process at most one operation at a time and the job processing order on the machines is immaterial, i.e., it has no implication for the scheduling outcome. The aim is to determine a schedule, i.e., the completion times of the operations processed on the machines, such that a performance criterion is optimized. While research on the problem dates back to the 1970s, there have been reviving interests in the computational complexity of variants of the problem and solution methodologies in the past few years. Aiming to provide a complete road map for future research on the open-shop scheduling problem, we present an up-to-date and comprehensive review of studies on the problem that focuses on minimizing the makespan, and discuss potential research opportunities

Empirical study of dense schedule performance ratio on open-shop scheduling problem

In this paper, we study properties of dense schedules for the open-shop problems and their average performance ratio. After using two sets of test problems, we show that the average performance ratio of dense schedules is actually much better than ( ), the worst-case performance ratio in the conjecture. The results from randomly generated problems which have large sizes show that when the dimension of open-shop problems become larger, the average performance ratio is getting even smaller. Twelve heuristic algorithms to generate dense schedules are presented in Chapter 3 and the computational results of two sets of test problems are also provided

Spartan Daily, February 12, 2020

Volume 154, Issue 9https://scholarworks.sjsu.edu/spartan_daily_2020/1008/thumbnail.jp

Encontrando la Comida Saludable: Identifying Food Access Barriers for the Adams County, Pennsylvania Latino Community

Overwhelming research indicates that recent national trends in U.S. food systems have led to the increased prevalence of processed foods and associated diet-related diseases. The effects of unhealthy diets have been distributed unevenly across the country’s socioeconomic and ethnic groups. Certain socioeconomic and ethnic groups face greater geographic, financial and cultural barriers to healthy food access. In Adams County, Pennsylvania, Latinos comprise 5.6% of the population, making them the county’s largest minority group, yet little is known about the food access barriers they face. In this study, we used a combination of surveys and focus groups with Latino residents and personal interviews with community leaders to identify the geographic, financial, and cultural barriers to food access for the county’s Latino community. We found that, though geographic and financial barriers had little effect on the community’s access to healthy food, cultural barriers presented a significant obstacle that needs to be addressed. We hope this study will inform the Adams County Food Policy Council in proposing policy measures that address specific food access issues in the county