Packet loss

About: Packet loss is a research topic. Over the lifetime, 21235 publications have been published within this topic receiving 302453 citations.

Server-based Inference of Internet Performance

Abstract: We investigate the problem of inferring the packet loss characteristics of Internet links using server-based measurements. Unlike much of existing work on network tomography that is based on active probing, we make inferences based on passive observation of end-to-end client-server traffic. We start with a brief analysis of end-to-end packet loss rate over widearea Internet paths, as observed from a busy Web site. We find that the end-to-end packet loss rate correlates poorly with topological distance (i.e., hop count), remains stable for several minutes, and exhibits a limited degree of spatial locality. These findings suggest that passive network tomography would be both interesting and feasible. Our work on passive network tomography focuses on identifying lossy links (i.e., the trouble spots in the network). We have developed three techniques for this purpose based on Random Sampling, Linear Optimization, and Bayesian Inference using Gibbs Sampling, respectively. We evaluate the accuracy of these techniques using both simulations and Internet packet traces. We find that these techniques can identify most of the lossy links in the network with a manageable false positive rate. For instance, simulation results indicate that the Gibbs sampling technique has over 80% coverage with a false positive rate under 5%. Furthermore, this technique provides a confidence indicator on its inference. In the case of Internet traces, validating the inferences is a challenging problem. We present a method for indirect validation, which suggests that the false positive rate is manageable.

Reliability for Emergency Applications in Internet of Things

Abstract: This paper addresses the Internet of Things (IoT) paradigm, which is gaining substantial ground in modern wireless telecommunications. The IoT describes a vision where heterogeneous objects like computers, sensors, Radio-Frequency IDentification (RFID) tags or mobile phones are able to communicate and cooperate efficiently to achieve common goals thanks to a common IP addressing scheme. This paper focuses on the reliability of emergency applications under IoT technology. These applications' success is contingent upon the delivery of high-priority events from many scattered objects to one or more objects without packet loss. Thus, the network has to be self-adaptive and resilient to errors by providing efficient mechanisms for information distribution especially in the multi-hop scenario. As future perspective, we propose a lightweight and energy-efficient joint mechanism, called AJIA (Adaptive Joint protocol based on Implicit ACK), for packet loss recovery and route quality evaluation in the IoT. In this protocol, we use the overhearing feature, characterizing the wireless channels, as an implicit ACK mechanism. In addition, the protocol allows for an adaptive selection of the routing path based on the link quality. .

Method of dynamically compensating for variable transmission delays in packet networks

Abstract: A method is described for playing out packets, such as voice or video packets, received through a packet network subject to variable transmission delays. The incoming packets are received in a delay buffer and a predetermined delay applied to the first packet of a sequence of packets. A variable delay is applied to subsequent packets to produce an appropriate constant play-out rate to reproduce the desired output. The fill level of the delay buffer is monitored and the predetermined delay applied to the first packet of a following sequence of packets adjusted to maintain the fill level within desired limits to minimize the risk of said buffer underflowing or overflowing.

A low redundancy data collection scheme to maximize lifetime using matrix completion technique

Abstract: Sensor nodes equipped with various sensory devices can sense a wide range of information regarding human or things, thereby providing a foundation for Internet of Thing (IoT). Fast and energy-efficient data collection to the control center (CC) is of significance yet very challenging. To deal with this challenge, a low redundancy data collection (LRDC) scheme is proposed to reduce delay as well as energy consumption for monitoring network by using matrix completion technique. Due to the correlation of the location-dependent sensing data, some data without being collected can still be recovered by the matrix completion technology, thereby reducing the data amount for data collection and transmission, reducing the network energy consumption, and accelerating the process of data acquisition. Based on matrix completion technique, LRDC scheme can select only part of the nodes to sense data and transmit less data to CC. By doing so, the data collected by the network can be greatly reduced, which can effectively improve the network lifetime. In addition, LRDC scheme also proposes a method for quickly compensate sample data in cases of packet loss, whereby part of redundant data is sent in advance to the area closer to CC. If the data required for matrix completion is lost, these redundant data can be quickly obtained by CC, so the LRDC scheme has low delay characteristics. Simulation results demonstrate that LRDC scheme can achieve better performance than the traditional strategy, and it can reduce the maximum energy consumption of the network by 27.6–57.9% and reduce the delay by 0.7–17.9%.