Average Bandwidth Usage Research Articles

A Feedback-Driven DNN Inference Acceleration System for Edge-Assisted Video Analytics

With the proposal of edge computing, lots of intelligence applications have made significant progress. For enormous video analysis, how to further accelerate the process is still a major challenge. To overcome the challenge, researchers propose various video frame filtering systems to reduce the data transmission. In this work, we propose a Feedback-Driven DNN Inference Acceleration system (FDDIA). FDDIA is committed to further reducing the latency of DNN inference and the transmission according to the feedback information. Specifically, on the device side, FDDIA first uses the detection results of prior frames as feedback to determine the key candidate regions and uses the inter-frame difference to determine the new object regions. Those regions containing large objects are down-sampled to further reduce the frame. On the edge side, FDDIA first integrates all candidate regions into a smaller new image. Then it remaps the detection result for the new image back to the original frame and returns the result to the device. We evaluate FDDIA on different video benchmarks for three object detection tasks. The results show FDDIA improves the average end-to-end latency by 44% and average bandwidth usage by 41% than the existing advanced method while maintaining a high accuracy.

AQuA: A New Image Quality Metric for Optimizing Video Analytics Systems

Millions of cameras at the edge are being deployed to power a variety of different deep learning applications. However, the frames captured by these cameras are not always pristine—they can be distorted due to lighting issues, sensor noise, compression etc. Such distortions not only deteriorate visual quality, they impact the accuracy of deep learning applications that process such video streams. In this work, we introduce AQuA, to protect application accuracy against such distorted frames by scoring the level of distortion in the frames. It takes into account the analytical quality of frames, not the visual quality, by learning a novel metric, classifier opinion score , and uses a lightweight, CNN-based, object-independent feature extractor. AQuA accurately scores distortion levels of frames and generalizes to multiple different deep learning applications. When used for filtering poor-quality frames at edge, it reduces high-confidence errors for analytics applications by 17%. Through filtering, and due to its low overhead (14 ms), AQuA can also reduce computation time and average bandwidth usage by 25%. Finally, we discuss numerous new avenues of optimizations of video analytics pipelines enabled by AQuA.

Websocket to Support Real Time Smart Home Applications

As we already know, the IoT (Internet of Thing) system has developed and is used in many fields, such as agriculture, security, industry etc. The IoT system requires real time monitoring and this is one of the problems that exists today. Transfering data from the sensor via the internet network to a monitoring device must be less than 300 ms. One process that can cause non-fulfillment of these requirements is a method for displaying the data on a monitor. There are several methods for delivering data from the sensor to a monitor. This paper has been compared between two methods, namely the polling method and the websocket method. The experiment was conducted to compare these two method. The result obtained that the websocket method was better in presenting real time data compared to the polling method. It can be shown in bandwidth usage and memory usage. In the experiment was found that the average of bandwidth usage is 478KB for polling method, and 91KB for web socket method in web based and the memory consumption of websocket less as much as 16% compared to polling method. In android smartphone the average bandwidth usage is 5.1 KB for web socket method and 15 KB for polling method and the memory consumption of websocket less as much as 22% compared to polling method.

Analisis Bandwidth Jaringan Internet PLIK dengan Metode Fuzzy Sugeno

Internet is a major part in the development and progress of the nation, especially the Indonesian nation, government issued a policy in Candy Kominfo about PLIK program (District Internet Service Center) which has a strategic role in sustaining and supporting economic activity, strengthening defense and security and the intellectual life of the nation. In the implementation of the program PLIK (District Internet Service Center) have not been targeted in a side benefit, this program should have as a means to meet the needs of information and knowledge, but rather the mere entertainment and more oriented to the business, which is equated with the cafe. This study attempts to retrieve the data in bandwidth usage that will be processed by the method of Fuzzy Sugeno and will generate average maximum bandwidth usage in applications Browsing, Download and Streaming. In determining the average bandwidth usage using Fuzzy Sugeno, From the average bandwidth will be used as a reference in determining the usage restrictions Browsing, Download and Stream with the aim to give control over bandwidth usage for applications Browsing, Download and Streaming.

Unified Capacity Limit of Non-Coherent Wideband Fading Channels

In non-coherent wideband fading channels where energy rather than spectrum is the limiting resource, peaky and non-peaky signaling schemes have long been considered species apart, as the first approaches asymptotically the capacity of a wideband AWGN channel with the same average SNR, whereas the second reaches a peak rate at some finite critical bandwidth and then falls to zero as bandwidth grows to infinity. In this paper it is shown that this distinction is in fact an artifact of the limited attention paid in the past to the product between the bandwidth and the fraction of time it is in use. This fundamental quantity, called bandwidth occupancy, measures average bandwidth usage over time. For all signaling schemes with the same bandwidth occupancy, achievable rates approach to the wideband AWGN capacity within the same gap as the bandwidth occupancy approaches its critical value, and decrease to zero as the occupancy goes to infinity. This unified analysis produces quantitative closed-form expressions for the ideal bandwidth occupancy, recovers the existing capacity results for (non-)peaky signaling schemes, and unveils a trade-off between the accuracy of approximating capacity with a generalized Taylor polynomial and the accuracy with which the optimal bandwidth occupancy can be bounded.

Multicast Communication for Video Broadcasting Service over IPv4 Network Using IP Option

In this paper, we propose a protocol for multicast communication called Multicast Datagram Transfer Protocol (MDTP) to provide multicast for video broadcasting service on the Internet. MDTP is a one-to-many multicast communication protocol, which is constructed based on IPv4 unicast protocol by utilizing IP Router Alert Option, and it uses unicast addressing and unicast routing protocol. A mechanism is presented to allow a router to remove identical video stream, to duplicate a video stream, and to forward each copy of the duplicated video stream to its destinations. Ordinary IP routers that do not support MDTP will treat the MDTP packets as normal unicast packets. Hence, gradual deployment is possible without tunneling technique. With a delegation mechanism, MDTP router is also able to handle request from clients, and serve the requested video stream. The simulation results show that the average bandwidth usage of MDTP is close to the average bandwidth usage of IP multicast. MDTP also has greater efficiency than XCAST, and its efficiency becomes significant for a large number of clients.