Search

This paper studies vehicle platooning with communication channels subject to random data loss. We focus on homogeneous discrete-time platoons in a predecessor-following topology with a constant time headway policy. We assume that each agent in the platoon sends its current position to the immediate follower through a lossy channel modeled as a Bernoulli process. To reduce the negative effects of data loss over the string stability and performance of the platoon, we use simple strategies that modify the measurement, error, and control signals of the feedback control loop, in each vehicle, when a dropout occurs. Such strategies are based on holding the previous value, dropping to zero, or replacing with a prediction based on a simple linear extrapolation. We performed a simulation-based comparison among a set of different strategies, and found that some strategies are favorable in terms of performance, while some others present improvements for string stabilization. These results strongly suggest that proper design of compensation schemes for the communications of interconnected multi-agent systems plays an important role in their performance and their scalability properties.

Uniform reliable broadcast (URB) is an important abstraction in distributed systems, offering delivery guarantee when spreading messages between processes. Informally, URB guarantees that if a process (correct or not) delivers a message m, then all correct processes deliver m. This abstraction has been extensively investigated in distributed systems where all processes have unique identifiers. Furthermore, the majority of papers in the literature usually assume that the communication channels of the system are reliable, which is not always the case in real systems. In this paper, the URB abstraction is investigated in anonymous asynchronous message passing distributed systems with process crash failures and fair lossy channels. For that, we assume the availability of a random number generator that generates unique global values with very high probability. Firstly, a simple URB algorithm is given assuming a majority of correct processes. Then, we prove the impossibility of solving URB without a majority of correct processes if no failure detector is used. Subsequently, a new failure detector class $$A{\varTheta }$$ is proposed, which can be used to implement URB with any number of correct processes. However, the two previous URB algorithms are non-quiescent because every correct process, to offset the loss of messages caused by fair lossy channels, has to broadcast all URB $$\_$$ delivered messages forever. Hence, a perfect anonymous failure detector $$AP^*$$ is proposed, together with $$A{\varTheta }$$ , to make the URB algorithm quiescent. Finally, we discuss an alternative failure detector $$A{\varTheta }P^*$$ , which combines the properties of $$A{\varTheta }$$ and $$AP^*$$ .

In this letter, we consider a computationally efficient sensor fusion scheme for obtaining a remote state estimate of a single linear process based on the data packets from the smart sensors which are transmitted through several independent lossy channels. Local observability at each smart sensor is assumed. We transformed the problem of finding the optimal linear sensor fusion coefficients as a semi-definite programming (SDP), which can be efficiently solved. Simulation results are presented to illustrate the performance of the developed algorithm.

In this work we design a specific simulation tool for quantum channels which is based on the use of a control system. This allows us to simulate an average quantum channel which is expressed in terms of an ensemble of channels, even when these channel-components are not jointly teleportation-covariant. This design is also extended to asymptotic simulations, continuous ensembles, and memory channels. As an application, we derive relative-entropy-of-entanglement upper bounds for private communication over various channels, including non-Gaussian mixtures of bosonic lossy channels. Among other results, we also establish the two-way quantum and private capacity of the so-called `dephrasure' channel., Comment: 9 pages. 1 figure

Quantum teleportation enables the deterministic exchange of qubits via lossy channels. While it is commonly believed that unconditional teleportation requires a preshared entangled qubit pair, here we demonstrate a protocol that is in principle unconditional and requires only a single photon as an ex-ante prepared resource. The photon successively interacts, first, with the receiver and then with the sender qubit memory. Its detection, followed by classical communication, heralds a successful teleportation. We teleport six mutually unbiased qubit states with average fidelity $\overline{\text{F}}=(88.3\pm1.3)\%$ at a rate of $6\,\mathrm{Hz}$ over $60\,\mathrm{m}$.

In this work, we study the problem of supervisory control of networked discrete event systems. We consider lossy communication channels with bounded network delays, for both the control channel and the observation channel. By a model transformation, we transform the networked supervisor synthesis problem into the classical (non-networked) supervisor synthesis problem (for non-deterministic plants), such that the existing supervisor synthesis tools can be used for synthesizing networked supervisors. In particular, we can use the (state-based) normality property for the synthesis of the supremal networked supervisors, whose existence is guaranteed by construction due to our consideration of command non-deterministic supervisors. The effectiveness of our approach is illustrated on a mini-guideway example that is adapted from the literature, for which the supremal networked supervisor has been synthesized in the synthesis tools SuSyNA and TCT., This paper is under review for Automatica

Block compressed sensing belongs to one newly developed compression technique in recent years. Aside from conventional trend to look for compression performances, we aim at reliable transmission for block compressed sensing signals over lossy channels. Without any protection scheme, block compressed sensing may suffer from severe degradation after reception. We look for the inherent characteristics of original images, and apply variable block sizes with protection schemes for block compressed sensing. Simulation results have demonstrated the effectiveness of proposed scheme suitable for variable-sized block compressed sensing over lossy channels.

We show that reachability, repeated reachability, nontermination and unboundedness are NP-complete for Lossy Channel Machines that are flat, i.e., with no nested cycles in the control graph. The upper complexity bound relies on a fine analysis of iterations of lossy channel actions and uses compressed word techniques for efficiently reasoning with paths of exponential lengths. The lower bounds already apply to acyclic or single-path machines., Comment: Submitted for publication

Measurement incompatibility is a distinguishing property of quantum physics and an essential resource for many quantum information processing tasks. We introduce an approach to verify the joint measurability of measurements based on phase-space quasiprobability distributions. Our results therefore establish a connection between two notions of non-classicality, namely the negativity of quasiprobability distributions and measurement incompatibility. We show how our approach can be applied to the study of incompatibility-breaking channels and derive incompatibility-breaking sufficient conditions for bosonic systems and Gaussian channels. In particular, these conditions provide useful tools for investigating the effects of errors and imperfections on the incompatibility of measurements in practice. To illustrate our method, we consider all classes of single-mode Gaussian channels. We show that pure lossy channels with 50% or more losses break the incompatibility of all measurements that can be represented by non-negative Wigner functions, which includes the set of Gaussian measurements., 9 pages, 1 figure, 1 table

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the optimal linear sensor fusion coefficients as a convex optimization problem which can be efficiently solved. Moreover, the closed-form expression is also derived for the optimal coefficients. Simulation results are presented to illustrate the performance of the developed algorithm., Comment: 14 pages, 3 figures

Quantum communication relies on the transmission of photons across lossy channels. Here, we show how hyperentangled photons can improve the efficiency of generating high fidelity entangled pairs between two parties.

This paper focuses on a networked state estimation problem for a spatially large linear system with a distributed array of sensors, each of which offers partial state measurements, and the transmission is lossy. We propose a measurement coding scheme with two goals. Firstly, it permits adjusting the communication requirements by controlling the dimension of the vector transmitted by each sensor to the central estimator. Secondly, for a given communication requirement, the scheme is optimal, within the family of linear causal coders, in the sense that the weakest channel condition is required to guarantee the stability of the estimator. For this coding scheme, we derive the minimum mean-square error (MMSE) state estimator, and state a necessary and sufficient condition with a trivial gap, for its stability. We also derive a sufficient but easily verifiable stability condition, and quantify the advantage offered by the proposed coding scheme. Finally, simulations results are presented to confirm our claims.

Nonclassical correlations are a fundamental resource for applications involving multipartite systems. To assess nonclassicality, several different criteria can be applied to measured data. Here we compare three inequalities by applying them to a multi-mode twin-beam state, in which one of the two parties is transmitted through a varying lossy channel. We demonstrate, both theoretically and experimentally, that the asymmetry introduced by losses affects the three criteria in different ways, thus offering a tool for quantum optics applications.

In this paper, we take into account lossy channels and retransmission protocols in dataflow models of computation (MoCs).Traditional dataflow MoCs cannot easily cope with lossy channels, due to the strict notion of iteration that does not allow the re-emission of lost or damaged tokens. A general dataflow graph with several lossy channels will indeed require several phases, each of them corresponding to a portion of the initial graph’s schedule. Correctly identifying and sequencing these phases is a challenge. We present a translation of a dataflow graph, written in the well-known Synchronous DataFlow (SDF) MoC of Lee and Messerschmitt, but where some channels may be lossy, into the Boolean Parametric DataFlow (BPDF) MoC.

This paper presents the Heuristic Application Layer Joint Coding (Heuristic-ALJC) scheme for video transmissions aimed at adaptively and jointly varying both applied video compression and source encoding at the application layer used to protect video streams. Heuristic-ALJC includes also a simple acknowledgement based adaptation of the transmission rate and acts on the basis of feedback information about the overall network status estimated in terms of maximum allowable network throughput and link quality (lossiness). Heuristic-ALJC is implemented through two smartphone Apps (transmitter and receiver) and is suitable to be employed to transmit video streams over networks based on time varying and possibly lossy channels. A performance investigation, carried out through a real implementation of the Apps over Android smartphones, compares Heuristic-ALJC with static schemes.

One of the main challenges for continued wireless capacity growth is the difficulty in exploiting the multicast nature of the wireless medium: wireless end points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled access points that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario, by guaranteeing per-receiver (access point) rates unaffected by the presence of receivers with worse channel conditions.

TCP over wireless networks is challenging due to random losses and ACK interference. Although network coding schemes have been proposed to improve TCP robustness against extreme random losses, a critical problem still remains of DATA–ACK interference. To address this issue, we use inter-flow coding between DATA and ACK to reduce the number of transmissions among nodes. In addition, we also utilize a “pipeline” random linear coding scheme with adaptive redundancy to overcome high packet loss over unreliable links. The resulting coding scheme, ComboCoding, combines intra-flow and inter-flow coding to provide robust TCP transmission in disruptive wireless networks. The main contributions of our scheme are twofold; the efficient combination of random linear coding and XOR coding on bi-directional streams (DATA and ACK), and the novel redundancy control scheme that adapts to time-varying and space-varying link loss. The adaptive ComboCoding was tested on a variable hop string topology with unstable links and on a multipath MANET with dynamic topology. Simulation results show that TCP with ComboCoding delivers higher throughput than with other coding options in high loss and mobile scenarios, while introducing minimal overhead in normal operation.

This paper introduces a novel error correction scheme for the transmission of three-dimensional scenes over unreliable networks. We propose a novel Unequal Error Protection scheme for the transmission of depth and texture information that distributes a prefixed amount of redundancy among the various elements of the scene description in order to maximize the quality of the rendered views. This target is achieved exploiting also a new model for the estimation of the impact on the rendered views of the various geometry and texture packets which takes into account their relevance in the coded bitstream and the viewpoint required by the user. Experimental results show how the proposed scheme effectively enhances the quality of the rendered images in a typical depth-image-based rendering scenario as packets are progressively decoded/recovered by the receiver.

Testbeds play a crucial role in evaluating novel protocols, algorithms, and applications in controlled, but realistic environments. These testbeds are mainly used by researchers to realize diverse application environments, which are not realistic to be achieved in simulated environments (e.g., lossy channels in Wireless Sensor Networks (WSN)). Most researchers, especially bachelor or master students spend a large portion of their time familiarizing themselves and setting up test beds before performing the actual research work. This portion of time, when considering the overall time for such work (e.g., 6 months for a masters thesis), forms a major part compared to the time spent on designing and developing protocols and algorithms (i.e., the focus of research). Therefore, to minimize the aforementioned entry effort in using testbeds for experiments, we have setup a testbed called the Versatile Experiment Platform for Sensor Networks (VEPSNet), which has a common Linux based environment with a homogeneous backend to collect data and process results allowing researchers to spend their quality time in the actual research work. In this paper, we provide details of the VEPSNet highlighting how this testbed is used to perform research in the area of WSN.

H.264/AVC is currently the most popular standard in use for video encoding. To achieve efficient coding while maintaining the desired level of the visual quality and to combat the distortions that may get introduced while transmission through lossy channels, it is imperative to use the best possible coding methodologies. To this end, it is desirable to ascertain the available implementations of the standard under various conditions of coding and levels of network perturbations. We present here the results of evaluating the behavior of two widely used freely available (JM and x264) and one commercially available (Elecard) H.264/AVC based encoders for encoding of high definition (HD) videos through simulated error-prone networks. For the evaluation, we employed the widely used and well understood peak signal to nois ratio (PSNR). We use the Mann-Whitney test to reveal the differences in objective scores and prove a strong content dependency of results, which prevents us from favoring one implementation above the others. Interestingly, we find that for all implementations, that lossy transmission causes sequences encoded at higher bitrates to give worse scores than low bitrate videos subject to the same distortion.

In this paper, the conservativeness issue is addressed for networked control of discrete time systems through a quantized lossy channel. The quantized lossy channel is first characterized as an uncertainty disturbance in signal-to-noise-ratio forms with both the input and output signals of the channel. Then it is shown that appropriate uncertainty characterization should be applied to conduct robust stability control and robust performance control, in order to achieve less conservative design. Single-input-single-output quantized lossy channels with both relative-error and multiplicative-error quantization as well as a multiplicative random noise are presented to illustrate the main ideas.

Transmission of image/video over unreliable medium like wireless networks generally results to receive a damaged image/video. In this paper, a novel robust image transmission scheme based on data partitioning and data hiding is proposed. In the encoder side, coefficients of the wavelet decomposed image are split into separate partitions. In next step, a very low bit-rate, high quality reference is generated for each partition. This reference is then embedded into another partition using a robust data hiding scheme based on the quantization index modulation (QIM). In the decoder side, if a part of the image is lost, the corresponding reference is extracted to reconstruct the lost information, thus concealing transmission errors. Performance results show the proposed technique provides high perceptual quality of reconstructed images at the end-user despite the channel losses and outperforms the existing approaches.

This paper studies the mean square stabilization problem of vector LTI systems over power constrained lossy channels. The communication channel is with packet dropouts, additive noises and input power constraints. To overcome the difficulty of optimally allocating channel resources among different sub-dynamics, schedulers are designed with time division multiplexing of channels. An adaptive TDMA (Time Division Multiple Access) scheduler is proposed first, which is shown to be able to achieve a larger stabilizability region than the conventional TDMA scheduler, and is optimal under some special cases. In particular, for two-dimensional systems, an optimal scheduler is designed, which provides the necessary and sufficient condition for mean square stabilization., Comment: Submitted to 2016 American Control Conference

Reliable broadcast (RB) is a basic abstraction in distributed systems, because it allows processes to communicate consistently and reliably with each other. This abstraction has been extensively investigated in eponymous distributed systems (i.e., all processes have different identifiers) in contrast to the study in anonymous systems (i.e., all processes have no ID). Hence, this paper is aimed to study RB in anonymous distributed systems with fair lossy communication channels. Firstly, a non-quiescent RB algorithm tolerating an arbitrary number of crashed processes is given. Then, we introduce an anonymous perfect failure detector AP*. Finally, we propose an extended and quiescent RB algorithm using AP*, in which eventually no process sends messages.

The increasing complexity of Web contents and the growing diffusion of mobile terminals, which use wireless and satellite links to get access to the Internet, impose the adoption of more specialized protocols. In particular, we focus on SPDY, a novel protocol introduced by Google to optimize the retrieval of complex webpages, to manage large Round Trip Times and high packet losses channels. In this perspective, the paper characterizes SPDY over high latency satellite links, especially with the goal of understanding whether it could be an efficient solution to cope with performance degradations typically affecting Web 2.0 services. To this aim, we implemented an experimental set-up, composed of an ad-hoc proxy, a wireless link emulator, and an instrumented Web browser. The results clearly indicate that SPDY can enhance the performances in terms of loading times, and reduce the traffic fragmentation. Moreover, owing to its connection multiplexing architecture, SPDY can also mitigate the transport layer complexity, which is critical when in presence of Performance Enhancing Proxies usually deployed to isolate satellite trunks.

The increasing complexity of Web contents and the growing diffusion of mobile terminals, which use wireless and satellite links to get access to the Internet, impose the adoption of more specialized protocols. In particular, we focus on SPDY, a novel protocol introduced by Google to optimize the retrieval of complex webpages, to manage large Round Trip Times and high packet losses channels. In this perspective, the paper characterizes SPDY over high latency satellite links, especially with the goal of understanding whether it could be an efficient solution to cope with performance degradations typically affecting Web 2.0 services. To this aim, we implemented an experimental set-up, composed of an ad-hoc proxy, a wireless link emulator, and an instrumented Web browser. The results clearly indicate that SPDY can enhance the performances in terms of loading times, and reduce the traffic fragmentation. Moreover, owing to its connection multiplexing architecture, SPDY can also mitigate the transport layer complexity, which is critical when in presence of Performance Enhancing Proxies usually deployed to isolate satellite trunks.

Originally developed by Google, SPDY is an open protocol for reducing download times of content rich pages, as well as for manag- ing channels characterized by large Round Trip Times (RTTs) and high packet losses. With such features, it could be an efficient solution to cope with performance degradations of Web 2.0 services used over satellite net- works. In this perspective, this paper evaluates the SPDY protocol over a wireless access also exploiting a satellite link. To this aim, we imple- mented an experimental set-up, composed of an SPDY proxy, a wireless link emulator, and an instrumented Web browser. Results confirm that SPDY can enhance the performances in terms of throughput, and reduce the traffic fragmentation. Moreover, owing to its connection multiplexing architecture, it can also mitigate the transport layer complexity, which is critical when in presence of middleboxes deployed to isolate satellite trunks.

LTE-Advanced (LTE-A) systems support wider transmission bandwidths and hence, higher data rates for bulk traffic, as a result of Carrier Aggregation (CA). However, existing literature lacks efforts on channel-aware CA, especially in the uplink. The cell-edge users particularly suffer from exhaustion of resources, higher fading losses, lower SINR values (hence, requiring a higher power consumption) due to lossy channels that their traffic requirements are least-satisfied by channel-blind CA. This paper addresses the above concern by proposing an edge-prioritized channel- and traffic-aware uplink CA comprising Component Carrier (CC) assignment and resource scheduling. The LTE-A UEs are spatially-grouped and the under-represented edge UE groups, having the least assignable resources (good CCs), are prioritized for CA. This results in assigning the best channels to the edge groups. The frequency resources are scheduled to the groups based on inter-group and intra-group Proportional Fair Packet Scheduling (PFPS) in the time and frequency domains respectively, to resolve resource contention. The proposed approach outperforms the existing channel-blind Round-Robin and channel-aware Opportunistic CA, in terms of overall uplink throughput, by 33% in CC assignment and 21% in PFPS, in addition to significant throughput improvements for the edge UEs.

This paper considers data rate limitations for mean square stabilization of uncertain discrete-time linear systems via finite data rate and lossy channels. For a plant having parametric uncertainties, a necessary condition and a sufficient condition are derived, represented by the data rate, the packet loss probability, uncertainty bounds on plant parameters, and the unstable eigenvalues of the plant. The results extend those existing in the area of networked control, and in particular, the condition is exact for the scalar plant case.

The point symmetry group is studied for the generalized Webster-type equation describing non-linear acoustic waves in lossy channels with variable cross sections. It is shown that, for certain types of cross section profiles, the admitted symmetry group is extended and the invariant solutions corresponding to these profiles are obtained. Approximate analytic solutions to the generalized Webster equation are derived for channels with smoothly varying cross sections and arbitrary initial conditions., Comment: Revtex4, 10 pages, 2 figure. This is an enlarged contribution to Acoustical Physics, 2012, v.58, No.3, p.269-276 with modest stylistic corrections introduced mainly in the Introduction and References. Several typos were also corrected

Summary form only given. The explosive demand for high-bandwidth low-power chip-to-chip communication in severe channel conditions calls for innovations in transceiver architectures and circuits. Clock-and-data recovery he next three papers present innovative equalization techniques to address the adverse effects of lossy channels such as inter-symbol interference, crosstalk, and dispersion.

An algorithm for determining the distortion for different data partitions in H.264/AVC is proposed. In this algorithm the distortion for any data partition received at the decoder in lossy channels can be recursively derived at the encoder. The overall distortion caused by quantization, error propagation, and error concealment are all considered. Extensive simulation results demonstrate the algorithm can provide one way to accurately evaluate the importance of different data partitions to the reconstructed video quality.

In this paper a new method for robust image transmission over lossy channels using distributed multiple description coding is presented. We propose an efficient yet a simple method for encoding each description from multiple description scalar quantizer by exploiting the correlation information among descriptions. In this way the correlated information which we call side information can be extracted at the decoder from each description. The motivation to such a type of encoding is to improve the side decoding and to increase the overall robustness of the scheme. Simulation results show that the side distortion is comparable with the central decoding distortion. Performance evaluation of the proposed approach over packet erasure channel shows 0.2–0.7dB improvement compared to simple multiple description coding that uses non-distributed multiple description scalar quantizer and demonstrates the effectiveness of the scheme over lossy channels.

This paper investigates the optimal PET protection for streaming scalably compressed streams over networks where the delivery time constraints allow limited retransmissions (LR) and the communication channels exhibit both random losses and delays. A key property must be considered in this scenario is the possibility that a packet successfully arrives at the receiver in time, even if its acknowledgment is not received by the sender at certain deadlines. This paper proposes an extended LRPET scheme, namely random-delay LR-PET, in which additional streams may be sent to provide supplemental protection for the packets whose acknowledgments are still missing at a specified time after the transmission. To determine the optimal protection in each transmission opportunity, hypotheses concerning the number of acknowledged packets and the effect of future retransmission are considered. As the key contribution of this paper, we develop a method to derive the effective overall recovery probability versus redundancy characteristic, which significantly simplifies the actual protection assignment procedure. This paper also demonstrates the benefits of the optimization strategy proposed for this random-delay LR-PET scheme and the cruciality of time selection for scheduling retransmission.

Error is inevitable in data trans-receiving over communication channels and its concealment is indispensable for standard codecs to enhance their quality of services. In recently standard video codecs, error resilience is based on absolute spatial and temporal approaches being applied uniformly for several types of video sequences. In this paper, an adaptive error concealment method based on radial basis neuro-fuzzy networks is proposed. Simulation results show that the proposed algorithm can gain up to 5 dB compared to the standard median algorithm.

Real packet channels are characterized by losses and delays as they both affect the performance of applications. A large number of techniques have been proposed in the literature for coding and recovery of lost information. In this paper we introduce a design framework to analyze, the impact of packet interleaving at the transmitter on the quality of service (QoS). Preliminary results are presented for Markov-chain based losses and Gamma-distributed delays. The optimization furnishes optimal packet interleaving proportions depending on channel statistics and maximum allowed delay, which is typically application dependent.

Multiple distortion coding (MDC) is a promising solution for video transmission over lossy channels. In MDC, multiple descriptions of a source are generated which are dependently decodable and mutually refinable. When all descriptions are available, the corresponding quality is called central quality; otherwise it is called side quality. Generally, there exists a trade-off between side and central quality in all MDC schemes. MDC methods which provide better central-side quality trade-off are of more interest to designers.