(1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.

https://link.springer.com/content/pdf/10.1057%2Fjors.1987.184.pdf

Applied Probability and Queues

Adaptive vector median filtering

From the Publisher:
Image Processing Handbook covers methods for two different purposes:
Improving the visual appearance of images to a human viewerPreparing images for measurement of the features and structures present.

The handbook presents an extensive collection of image processing tools, enabling the user of computer-based system to understand those methods provided in packaged software and to program additions needed for particular applications. Comparisons are presented of different algorithms that may be used for similar purposes, including a selection of representative pictures from light and electron microscopes as well as macroscopic, satellite, and astronomical images.
Image Processing Handbook examines the rapid, powerful developments in graphic information, covering the array of concepts and techniques in high-end imaging software. With balanced, complete descriptions, the text outlines frequency space methods with extensive mathematical presentation and spatial domain processing. This handbook teaches by example -- by seeing what various operations do to representative images, the reader will discover how and why to use them. The text encourages the reader to use its information with a real source of images and a computer-based system as well as to freely experiment with different methods to determine the most appropriate for his or her particular needs.To facilitate the learning process, Reindeer Games in Charlotte, North Carolina, offers The Image Processing Tool Kit, a CD-ROM containing more than 150 images and more than 150 Photoshop-compatible plug-ins that implement the algorithms discussed. This revision of the established standard acts as a singular resource for professionals in the medical, biological, and materials sciences as well as a range of engineering venues, including electrical and computer engineering, optical engineering, telecommunications, and artificial intelligence.

Image Processing Handbook, Fourth Edition

Security, privacy & efficiency of sustainable Cloud Computing for Big Data & IoT

Wireless sensor networks are one of the most promising emerging technologies, providing the opportunity for real-time monitoring of geographical regions (remote and hostile) that are prone to disasters. With a focus on landslide detection, this work reaffirms the capability of wireless sensor networks for disaster mitigation. A complete functional system consisting of 50 geological sensors and 20 wireless sensor nodes was deployed in Idukki, a district in the southwestern region of Kerala State, India, a highly landslide prone area. The wireless sensor network system has, for the past three years, gathered vast amounts of data such as correlated sensor data values on rainfall, moisture, pore pressure and movement, along with other geological, hydrological and soil properties, helping to provide a better understanding of the landslide scenario. Using the wireless sensor networks, system was developed an innovative three level landslide warning system (Early, Intermediate and Imminent). This system has proven its validity by delivering a real warning to the local community during heavy rains in the July 2009 monsoon season. The implementation of this system uses novel data aggregation methods for power optimization in the field deployment. A report on unanticipated challenges that were faced in the field deployment of the wireless sensor networks and the novel solutions devised to overcome them are presented here.

Design, development, and deployment of a wireless sensor network for detection of landslides

In this paper, we study the stability of the queue size in an AQM router that drops incoming packets with probability that is a function of the queue size. Using the newest analytical results we find the shape of the dropping function that is optimal in terms of minimization of the variance of the queue length.

Towards a Stable AQM via Dropping Function Shaping

Traditionally, video adaptive algorithms aim to select the representation that better fits to the current download rate. In recent years, a number of new approaches appeared that take into account the buffer occupancy and the probability of video rebuffering as important indicators of the representation to be selected. We propose an optimization of the existing algorithm based on rebuffering probability and argue that the algorithm should avoid the situations when the client buffer is full and the download is stopped, since these situations decrease the efficiency of the algorithm. Reducing full buffer states does not increase the rebuffering probability thanks to a clever management of the client buffer, which analyses the buffer occupancy and downloads higher bitrate representations only in the case of high buffer occupancy.

On Optimizing Adaptive Algorithms Based on Rebuffering Probability

In computer networking, the burst ratio is a parameter of the packet loss process, containing information about the tendency of losses to occur in blocks, rather than as separate units. Its value is especially important for real-time multimedia transmissions. In this paper, we report the measurements of the value of this parameter carried out in the networking laboratory. These measurements involved high volumes of traffic, different numbers of flows, different TCP/UDP traffic proportions and different packet sizes. In every case, a high value of the burst ratio was obtained. This is an experimental confirmation of the conjecture that the buffering mechanisms, commonly used in the contemporary networks, make the packet losses to group together.

Experimental Measurements of the Packet Burst Ratio Parameter

We performed a non-stationary analysis of a class of buffer management schemes for TCP/IP networks, in which the arriving packets were rejected randomly, with probability depending on the queue length. In particular, we derived formulas for the packet waiting time (queuing delay) and the intensity of packet losses as functions of time. These results allow us to observe how the evolution of the waiting time and losses depend on initial conditions (e.g., the full buffer) and system parameters (e.g., dropping probabilities, load, packet size distribution). As side results, the stationary waiting time and packet loss probability were obtained. Numerical examples demonstrate applicability of the theoretical results.

/pdf/non-stationary-characteristics-of-aqm-based-on-the-queue-qfjgdcqo.pdf

Andrzej Chydzinski

Papers

Towards a Stable AQM via Dropping Function Shaping

On Optimizing Adaptive Algorithms Based on Rebuffering Probability

Experimental Measurements of the Packet Burst Ratio Parameter

Non-Stationary Characteristics of AQM Based on the Queue Length

Per-flow structure of losses in a finite-buffer queue