Free-space optics (FSO) communication system is mature, unique and promising technology which is used in various countries to meet high data rate demand and last mile connectivity. FSO link has a capacity to be utilized as a primary communication links by replacing RF communication systems because of its advantages of unregulated bandwidth, broader spectrum of frequency at low power consumption. Now a days researchers has great interest in this technology because of several features and benefits of larger bandwidth, less power consumption, low installations cost, simple to install, no congestion in spectrum, secure and reliable communication without issues of right of way. In free space optical communication, environment layer is used for signal transmission which can be effected from severe weather conditions like smog, dust, smoke, rain and fog etc. In all these severe weather environments, winter fog is one of the main problem because of it offers high optical attenuation on communication link. In this investigation the entire winter season has been observed. There are four fog events which attenuate the optical signal most. Optical attenuation is estimated using three famous fog prediction models like Al Naboulsi, Kim and at wavelengths of 850nm, 1350nm, and 1550 nm.
Increasing the size of memory in network devices leads to the problem of a persistently full buffer (a.k.a, bufferbloat). The objective of this study is to compare the recently introduced Controlled Delay (CoDel) scheme with the traditional method of active queue management, such as Random Early Detection (RED) algorithms over TCP variants. To explore the potential of CoDel over RED, TCP variants have been assessed at three settings: variable congestion and fixed payload (VCFP), variable payload and fixed congestion (VPFC), and high congestion and high payload (HCHP). We assessed the CoDel and RED schemes for active queue management (AQM) using three performance metrics: link utilization, drop rate, and queuing delay. The analytical results show that CoDel outperformed RED in most aspects over variants of TCP because of its auto‐tuning and auto‐adjustment features. However, RED outperformed CoDel in a few cases. In the VCFP setting, RED recorded a lower drop rate overall TCP variants. Moreover, in the VPFC setting, RED with a payload of 500–1000 bytes performed better in terms of drop rate. Finally, in the HPHC setting, there were two cases where RED, over TCP NewReno and Vegas, performed well in terms of drop rate.
Recently, the spy cameras spotted in private rental places have raised immense privacy concerns. The existing solutions for detecting them require additional support from synchronous external sensing or stimulus hardware such as on/off LED circuits, which require extra obligations from the user. For example, a user needs to carry a smartphone and laboriously perform preset motions (e.g., jumping, waving, and preplanned walking pattern) for synchronous sensing of acceleration signals. These requirements cause considerable discomfort to the user and limit the practicability of prevalent solutions. To cope with this, we propose CSI:DeSpy, an efficient and painless method by leveraging video bitrate fluctuations of the WiFi camera and the passively obtained Channel States Information (CSI) from user motion. CSI:DeSpy includes a self-adaptive feature that makes it robust to detect motion efficiently in multipath-rich environments. We implemented CSI:DeSpy on the Android platform and assessed its performance in diverse real-life scenarios, namely; (1) its reliability with the intensities of physical activities in diverse multipath-rich environments, (2) its practicability with activities of daily living, (3) its unobtrusiveness with passive sensing, and (4) its robustness to different network loads. CSI:DeSpy attained average detection rates of 96.6%, 96.2%, 98.5%, and 93.6% respectively.
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