Approximation Algorithms for Scheduling Parallel Jobs: Breaking the Approximation Ratio of 2

In this paper we study variants of the non-preemptive parallel job scheduling problem in which the number of machines is polynomially bounded in the number of jobs. For this problem we show that a schedule with length at most (1 + ε)OPT can be calculated in polynomial time. Unless P = NP, this is the best possible result (in the sense of approximation ratio), since the problem is strongly NP-hard. For the case, where all jobs must be allotted to a subset of consecutive machines, a schedule with length at most (1.5 + ε)OPT can be calculated in polynomial time. The previously best known results are algorithms with absolute approximation ratio 2. Furthermore, we extend both algorithms to the case of malleable jobs with the same approximation ratios

A moldable online scheduling algorithm and its application to parallel short sequence mapping

Abstract. A crucial step in DNA sequence analysis is mapping short sequences generated by next-generation instruments to a reference genome. In this paper, we focus on efficient online scheduling of multi-user parallel short sequence mapping queries on a multiprocessor system. With the availability of parallel execution models, the problem at hand becomes a moldable task scheduling problem where the number of processors needed to execute a task is determined by the scheduler. We propose an online scheduling algorithm to minimize the stretch of the tasks in the system. This metric provides improved fairness to small tasks compared to flow time metric and suits well to the nature of the problem. Experimental evaluation on two workload scenarios indicate that the algorithm results in significantly smaller stretch compared to a recent algorithm and it is more fair to small sized tasks.

Impact of a Remote Monitoring Programme Including Lifestyle Education Software in Type 2 Diabetes: Results of the Educ@dom Randomised Multicentre Study

International audienceINTRODUCTION: Telemonitoring in type 2 diabetes (T2D) is mainly based on glucose monitoring. A new type of connected device which routinely gathers data on weight, physical activity and food intake could improve patients' diabetes control. The main aim of this study was to assess the efficacy of an at-home interventional programme incorporating such devices and lifestyle education software on diabetes control, i.e., change in HbA1c, compared to standard care. METHODS: This multicentre study randomly assigned 282 people with T2D to either a telemonitoring group (TMG) or a control group (CG) for a 1-year intervention period. While routine follow-up was maintained in the CG, TMG subjects were provided with interactive lifestyle educational software (with artificial intelligence algorithms) and connected objects (blood glucose meters, scales and actimeters) for use in their own homes and were remotely monitored by their diabetologists. Changes in HbA(1c) were compared between groups using a mixed linear model. RESULTS: The mean HbA(1c) dropped from 7.8 ± 0.8% (62 mmol/mol) to 7.4 ± 1.0% (57 mmol/mol) in the TMG and from 7.8 ± 0.8% (62 mmol/mol) to 7.6 ± 1.0% (60 mmol/mol) in the CG, resulting in an intergroup difference of - 0.16 (p = 0.06) in favour of TMG, after adjustment for confounding factors. Within TMG, the decrease in HbA(1c) was greater in frequent users: - 0.23% (p = 0.03) in the case of connections to telemonitoring synthesis above the median and - 0.21% (p = 0.05) in the case of connections to tele-education software above the median compared to the CG. Significant weight loss was observed in the TMG but only in women (p = 0.01). FINDINGS: The EDUC@DOM telemonitoring and tele-education device did not highlight a significant decrease in HbA1c levels compared to routine management although a slight, albeit significant improvement in glycaemic control was observed in the frequent user subgroup as well as significant weight loss but only in women. A high level of satisfaction with the connected device was recorded amongst all participants. TRIAL REGISTRATION: This trial was registered in the Clinical Trials Database on September 27, 2013, under no. NCT01955031 and bears ID-RCB number 2013-A00391-44