FD-LTDA-MAC: Full-Duplex Unsynchronised Scheduling in Linear Underwater Acoustic Chain Networks

In-band full-duplex communication offers significant potential to enhance network performance. This paper presents the full-duplex linear transmit delay allocation MAC (FD-LTDA-MAC) protocol for full-duplex based underwater acoustic chain networks (FD-UACNs) for subsea pipeline monitoring. This incorporates a number of extensions to the LTDA-MAC protocol in order to fully exploit advantages of full-duplex communication to enhance the efficiency of underwater facility monitoring. The protocol uses a greedy optimisation algorithm to derive collision-free packet schedules for delivering data packets to the sink node of the underwater chain network. The purpose of this paper is to show the significant improvement that can be achieved in packet scheduling by exploiting temporal spectrum re-use of an underwater acoustic channel through full-duplex communication. Simulation results show that more efficient packet scheduling and reduced end-to-end packet delays can be achieved in large scale scenarios using FD-LTDA-MAC compared with LTDA-MAC and LTDA-MAC with full-duplex enabled nodes. It can provide much higher monitoring rates for long range underwater pipelines using low cost, mid range, low rate, and low power acoustic modems.

Optimal Control of Flight Delays Allocation at Airport

Aiming at improving the unreasonable situation of flight delay allocation, an optimization model which contains two cases was proposed. One of the cases is to transfer all the delay to several delayed flights to avoid delay spread, which can increase the flight punctuality rate to ensure the departure of the majority flights. Oppositely, the other is to balance the delay losses of airlines, as well as the passengers, for realizing the fairness. According to the latest data from an airport in western China, the model was verified with genetic algorithm, which indicates that the model not only decrease the total delay losses, but also optimize the flight delay allocation which achieves the initial goal.

Research on Hadoop Greedy Scheduler Based on the Fair

Job scheduling technology is one of the Hadoop platform’s key technologies, whose main function is to control the execute sequence of job and the distribution of computing resources, which directly relates to the Hadoop platform’s overall performance and system resources, usage. However, the existing job scheduling algorithms such as FIFO Scheduler, Fair Scheduler and Capacity Scheduler all have some defects. To overcome theses defects, this paper proposed a new algorithm Hadoop Greedy Scheduler Based on the Fair (HGSF). Firstly, the job pools are sorted by priority from high to low; pools in the same priority are sorted by their minimum requirements. Then their minimum requirements are met in turn. If have spare computing resources, it will be assigned to the job pool which has the highest priority and the minimum difference between the ideal requirement and the minimum requirement. Finally, the algorithm uses delay allocation strategy to improve the localization of the data for computing tasks. The experimental results testified the effectiveness of the proposed algorithm.