Pyroelectric infrared (PIR) sensors are considered to be promising devices for device-free localization due to its advantages of low cost, energy efficiency, and the immunity from multi-path fading. However, most of the existing PIR-based localization systems only utilize the binary information of PIR sensors and therefore require a large number of carefully deployed PIR sensors. A few works directly map the raw data of PIR sensors to one's location using machine learning approaches. However, these data-driven approaches require abundant training data and suffer from environmental change. In this paper, we propose PIRATES, a PIR-based device-free localization system based on the raw data of PIR sensors. The key of PIRATES is to extract a new type of location information called azimuth change. The extraction of the azimuth change relies on the physical properties of PIR sensors. Therefore, no abundant training data are needed and the system is robust to environmental change. Through experiments, we demonstrate that PIRATES can achieve higher localization accuracy than the state-of-the-art approaches. In addition, the information of the azimuth change can be easily incorporated with other information of PIR signals (e.g. amplitude) to improve the localization accuracy.

Integrating solid-state drives (SSDs) and shingled magnetic recording (SMR) drives can build cost-effective hybrid storage systems. However, both SSD and SMR drives endure inherent defects that are mutually exclusive. The write endurance of SSD is limited while SMR drives should prevent from writes due to the cleaning-caused performance degradation. In this paper, we propose Duchy, an endurable SSD caching scheme that simultaneously respects SMR constraints. Duchy filters ineffectual write traffic out of SSD without exacerbating the performance degradation of SMR drives. Meanwhile, Duchy leverages SSD to regulate the written zones in SMR drives to achieve controllable cleaning duration. Our experimental results indicate that compared with legacy SSD caching designs, only Duchy can achieve both system performance improvement and SSD write traffic reduction.

In HPC, endpoint congestion is a bottleneck in the network and seriously affects the performance of the system. The endpoint congestion can be effectively mitigated by quickly responding to the network and reducing the injection rate of the source. However, most of the prior works do not consider the impact of flow completion time on system performance, but only focus on the packet latency and perform scheduling at packet granularity. For HPC applications, the flow completion time and throughput are the metrics that determines the speed of application execution. Although prior works reduce package latency, they do not fundamentally reduce the flow latency in flow level. In this paper, we propose the bilateral flow-based reservation protocol (BFRP). BFRP quickly responds to network conditions through light-weight bilateral reservation mechanism and can effectively avoid the formation of endpoint congestion. BFRP also schedules packets based on flows, and smallest flow is preferentially sent to decrease the average flow latency. BFRP ensures the source and destination send or receive flows according to the allocated time slices without any conflict at both ends. We evaluate our BFRP protocol against state-of-the-art reservation-based protocol, speculative reservation protocol(SRP), and the simulation results show that the flow latency can be reduced by 27.68% under hotspot traffic with fixed flow size and 24.59% under uniform traffic with fixed flow size.