Mechanisms for detecting communication errors are crucial in industrial networks where reliability is a primary requirement. Even if the Cyclic Redundancy Check (CRC) polynomial generator is given for each transmission protocol, an application designer could choose a specific protocol according to its robustness, or additional error detection mechanisms can be freely added at the application level (e.g., nested CRC). Therefore, a methodology is desired to evaluate the residual error probability of a given protocol, i.e., considering its packet structure and error detection mechanism. Symbolic approaches proposed in the literature are not scalable for usual packet sizes. Monte Carlo simulation can be a valid alternative to inject errors and see what happens. However, the brute force generation of error patterns takes too much simulation time if the channel error probability is very low, as in realistic scenarios. This paper presents a Monte Carlo approach enriched with Importance Sampling, implemented in a tool11https://github.com/guarinopaolo/residual-error-probability-simulator. The framework takes the packet structure and the error detection mechanism as input, thus being independent of them. Experimental results validate the approach with respect to state-of-the-art approaches and show its effectiveness in exploring protocol alternatives.

There is an increasing interest in exploiting human pose estimation (HPE) software in human-machine interaction systems. Nevertheless, adopting such a computer vision application in real industrial scenarios is challenging. To overcome occlusion limitations, it requires multiple cameras, which in turn require multiple, distributed, and synchronized HPE software nodes running on resource-constrained edge devices. We address this challenge by presenting a real-time distributed 3D HPE platform, which consists of a set of 3D HPE software nodes on edge devices (i.e., one per camera) to redundantly extrapolate the human pose from different points of view. A centralized aggregator collects the pose information through a shared communication network and merges them, in real time, through a pipeline of filtering, clustering and association algorithms. It addresses network communication issues (e.g., delay and bandwidth variability) through a two-levels synchronization, and supports both single and multi-person pose estimation. We present the evaluation results with a real case of study (i.e., HPE for human-machine interaction in an intelligent manufacturing line), in which the platform accuracy and scalability are compared with state-of-the-art approaches and with a marker-based infra-red motion capture system.

Many recent pattern recognition applications rely on complex distributed architectures in which sensing and computational nodes interact together through a communication network. Deep neural networks (DNNs) play an important role in this scenario, furnishing powerful decision mechanisms, at the price of a high computational effort. Consequently, powerful state-of-the-art DNNs are frequently split over various computational nodes, e.g., a first part stays on an embedded device and the rest on a server. Deciding where to split a DNN is a challenge in itself, making the design of deep learning applications even more complicated. Therefore, we propose Split-Et-Impera, a novel and practical framework that i) determines the set of the best-split points of a neural network based on deep network interpretability principles without performing a tedious try-and-test approach, ii) performs a communication-aware simulation for the rapid evaluation of different neural network rearrangements, and iii) suggests the best match between the quality of service requirements of the application and the performance in terms of accuracy and latency time.

In mixed human-robot work cells the emphasis is traditionally on collision avoidance to circumvent injuries and production down times. In this paper we discuss how long in advance a collision can be predicted given the behavior of a robotic arm and the current occupancy of both the robot and the human. Assuming that the behavior of the robot is a combination of a set of predefined operations, we propose an approach to learn this behavior and use it to estimate the time before a collision. The pose of the human is estimated by a multicamera inference application based on neural networks at the edge to preserve privacy and enforce scalability. The occupancy of the manipulator and of the human are modeled through the composition of segments which overcomes the traditional "virtual cage" and can be adapted to different human beings and robots. The system has been implemented in a real factory scenario to demonstrate its readiness regarding both industrial constraints and computational complexity.

Digital twins of production lines do not focus solely on the management of the production process, they can also monitor and optimize other extra-functional aspects such as energy consumption and communications. This paper proposes the extension of digital twin concept in such directions. First, we extend the digital twin with models of energy consumption, that allow the monitoring of production line components throughout production lifetime. Then, we propose a flow to design the communication network starting from information obtained from the digital twin concerning the production, usage and flowing of information through the plant. All these methodologies start from the production line specification, then they enrich it with data collected during operation, and finally information is used to perform design and optimization. Results have been shown on a real Industry 4.0 research facility.

Today's factory machines are ever more connected with SCADA, MES, ERP applications as well as external systems for data analysis. Different types of network architectures must be used for this purpose. For instance, control applications at the lowest level are susceptible to delays and errors while data analysis with machine learning procedures requires to move a large amount of data without real-time constraints. Standard data formats, like Automation Markup Language (AML), have been established to document factory environment, machine placement and network deployment, however, no automatic technique is currently available in the context of Industry 4.0 to choose the best mix of network architectures according to spacial constraints, cost, and performance. We propose to fill this gap by formulating an optimization problem. First of all, spatial and communication requirements are extracted from the AML description. Then, the optimal interconnection of wired or wireless channels is obtained according to application objectives. Finally, this result is back-annotated to AML to be used in the life cycle of the production system. The proposed methodology is described through a small, but complete, smart production plant.

Development of cyber-physical systems' control algorithms usually relies on architecture-agnostic abstract models, often leading to ineffective implementations. This paper presents a technique to automatically integrate cycle-accurate models of digital HW components with continuous-time physical models. It proposes a solution to the semantic gap between the involved models of computation. Furthermore, model generation and integration for both Simulink-based proprietary environment and FMI-based portable standard are presented. The aim of such techniques is to produce cyber-physical virtual-platforms: a powerful tool to refine control algorithms up to their SW implementations on the actual HW platform.

Smart wireless techniques are at the core of many today's telecommunication and networked embedded systems where performance are enhanced by intertwining radio frequency (RF) and digital aspects. Therefore their design requires to focus on both domains. Traditional approaches for their simulation rely either on different domain-specific tools or on analog-mixed-signal modeling languages. In the former case, the simulation of the whole platform in the same session is not possible while in the latter case, simulation performance is limited by the computationally most intensive domain (usually RF). We present an extension of the SystemC Network Simulation Library that allows to simulate antenna details and node position together with digital hardware and software. The validation on a real wearable system shows that the proposed simulation approach achieves a good trade-off between accuracy and speed thus allowing fast exploration of various configurations in the early phase of the design flow without recurring to the expensive and time-consuming creation of physical prototypes.

Functional safety is a major concern in today's networked cyber-physical systems such as connected machines, autonomous vehicles, and intelligent environments. Simulation is a well-known methodology for the assessment of functional safety. Simulation models of networked cyber-physical systems are very heterogeneous relying on digital hardware, analog hardware, and network domains. Current functional safety assessment is mainly focused on digital hardware failures while minor attention is devoted to analog hardware and not at all to the interconnecting network. We propose a holistic methodology for simulation-based safety assessment in which safety mechanisms are tested in a simulation environment reproducing the high-level behavior of digital hardware, analog hardware, and network. Also faults are tested at high abstraction level to speed up analysis.

The amazing proliferation of communication technologies for embedded systems opens the way for completely new applications but forces designers to adopt new methodologies to meet time-to-market constraints. Computer-Aided Design (CAD) has been traditionally applied to computers and embedded systems in isolation without considering them as a global inter-connected system. The paper contributes to fill this gap by proposing 1) a communication-aware design flow for network-interconnected embedded systems and 2) a formal framework to efficiently synthesize their network aspects by formulating and solving an optimization problem. Presented case studies show the potentiality of the proposed approach to address heterogeneous scenarios, e.g., related to smart spaces up to the ever-more-mentioned Internet-of-Things.

Analog components are fundamental blocks of smart systems, as they allow a tight interaction with the environment, in terms of both sensing/actuation and communication. This impacts on the design of the overall system, and mainly on the validation phase, that thus requires the joint simulation of digital and analog aspects. In this scenario, this paper proposes the automatic conversion of analog models to C++-based languages, to remove the overhead of co-simulation with traditional virtual platform tools. The proposed methodology allows to convert a given analog description to either: 1) a fully equivalent description or 2) an abstract representation for faster simulation which models only the aspects of interest. Effectiveness and correctness have been proved on a number of case studies that highlight the effectiveness and potentiality of the proposed methodology.

Augmented reality (AR) applications greatly benefit from direction estimation. In current AR devices, direction estimation is enabled by power hungry technologies such as GPS, management of inertial data and video processing. We present a low-complexity eyewear prototype capable of obtaining directional information from a set of environmental radio sources by using a multi-antenna system patented by Wagoo LLC. Eyewear devices are the natural match for this technology under the assumption that user line of sight represents the main reference for user interaction and orientation. In the demonstration, the prototype detects when a user aims at objects or people that are associated to standard Bluetooth Low Energy emitters (beacons) with a current 30° sensitivity and 5% error rate.

The increasing processing power of today's HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. The paper presents the CONTREX European project and its preliminary results. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels.

In the above paper, the location for the Arab Academy for Science and Technology was incorrect in the biography of author, Emad Ebied. The correct location is Cairo, Egypt. The correct biography is provided.

The paper focuses on techniques for the verification of software implementing communication functionality in networked embedded systems. We discuss the merits and limitations of tools for the simulation of a networked embedded system executing the binary code of the network protocol stack. In particular, we compare different solutions to extend a virtual platform to simulate the node of interest in a realistic communication scenario involving different network nodes. We then explain how this solution has the potentiality to perform verification of the protocol stack, which would be a great asset for industry and academia to validate the communication software under development or use.

The design of distributed embedded systems is a challenging task that requires raising the level of abstraction to handle the different involved concerns. In particular, standard modeling languages and precise semantics specification are necessary to address the networking-related aspects at a high level of abstraction. The Unified Modeling Language (UML) and its MARTE profile are valid formalisms to model real-time embedded systems but they lack precise modeling elements when addressing applications and platforms forming distributed embedded systems. In this work, we formalize a coherent set of modeling elements for the design and deployment of distributed embedded systems. A novel UML profile for networking is proposed as a semantic and syntactic extension to the UML Profile for MARTE: The Network Profile.

Design of distributed embedded systems is a challenging task and it requires raising the level of abstraction to overcome the complexity of the design. In particular, modeling languages and semantic specification are necessary to address network description at high level of abstraction. Starting from this abstraction view, model manipulation is needed to explore various design alternatives and code generation is required for their simulation. In this paper, we propose the use of unified modeling language diagrams combined with a formal computational model as a key solution to specify requirements, generate design alternatives, and code for simulation. This paper proposes a formal framework and supporting tools to represent the application requirements, the library of network components, the environment description, and the rules to compose them. The framework allows to generate code for design validation by simulation and provides back annotation mechanism of the simulation results to refine the original model.

Networked embedded systems are essential building blocks of a broad variety of distributed applications ranging from agriculture to industrial automation to healthcare and more. These often require specific energy optimizations to increase the battery lifetime or to operate using energy harvested from the environment. Since a dominant portion of power consumption is determined and managed by software, the software development process must have access to the sophisticated power management mechanisms provided by state-of-the-art hardware platforms to achieve the best tradeoff between system availability and reactivity. Furthermore, internode communications must be considered to properly assess the energy consumption. This article describes a design flow based on a SystemC virtual platform including both accurate power models of the hardware components and a fast abstract model of the wireless network. The platform allows both model-driven design of the application and the exploration of power and network management alternatives. These can be evaluated in different network scenarios, allowing one to exploit power optimization strategies without requiring expensive field trials. The effectiveness of the approach is demonstrated via experiments on a wireless body area network application.

This paper proposes an energy-efficient security-aware architecture for wireless control systems to be used in factory automation. We face deception attacks that corrupt commands and measurements in a smart way and with intermittent behavior to produce the highest damage without being discovered. The intrusion is hard to distinguish from normal disturbance. Furthermore, protection against attacks is energy-consuming and it would be desirable to activate protection only when needed. We propose packet-based selective encryption to reduce energy consumption, and to detect when an attack starts and ends. Since energy consumption depends also on packet transmission rate, especially during attacks, we also propose to adapt it according to instantaneous control performance.

The design of wireless embedded systems needs their efficient and realistic simulation to verify that requirements are met. The reproduction of communication behavior is crucial to assess the performance of hardware and software components, e.g., dependability and energy consumption. This work presents and discusses different levels of abstraction for the simulation of the communication behavior. Each level addresses different aspects of the communication and allows to specify different kinds of detail; furthermore, it requires a specific modeling approach. Their use and the corresponding computational overhead is shown in the specific case of the Bluetooth standard. We also show that simulation results obtained at a low abstraction level can be used at a higher one to drive design choices.

Networked control systems are a well-known sub-set of cyber-physical systems in which the plant is controlled by sending commands through a digital packet-based network. Current control networks provide advanced channel access mechanisms to guarantee low delay on a limited fraction of packets (low-delay class) while the other packets (un-protected class) experience a higher delay which increases with channel utilization. We investigate the extension of model predictive control to choose both the command value and its assignment to one of the two classes according to the predicted state of the plant and the knowledge of network condition. Experimental results show that more commands are assigned to the low-delay class when either the tracking error is high or the network condition is bad.

This paper presents abstraction techniques and modeling approaches to include physical-level antenna and receiver performance effects in a system-level network simulation for Wireless Body Area Networks (WBAN). The simulation platform is based on SystemC which can be used to model digital HW and SW aspects of an embedded application. By using the SystemC Network Simulation Library also a distributed network scenario can be simulated. Here, this platform has been extended to take into account the bit error rate and the path loss associated with antenna positioning in close proximity to the human body and with the design parameters of the wireless receiver. Antenna effects are modeled through a database of performance values based on physical measurements on a human phantom. Path loss information is fed in the SystemC simulator to model the received signal strength as a function of the position of nodes. The same information is used in the physical-level simulation of the receiver to extract bit error rate curves to be used by the SystemC simulator to build a statistical model of packet corruption. Instead of physical-level details, their effects are modeled in a parametric way into the system-level simulation thus combining speed and fidelity and allowing cross-domain design space exploration.

The behavior of Networked Embedded Systems (NES) is not only driven by network components but also by the surrounding environment. To verify the correct behavior of such systems, different tests should be performed under different environmental conditions. The complexity and expense of testing such systems in real environments leads us to propose a simulation-based approach to tackle this problem. In this work, we propose UML-based methodology and a framework for modeling NES applications together with the environment and a mechanism to automatically generate simulation code for design verification. The approach is supported by a novel UML profile and a set of tools for simulation code generation.

This paper proposes a novel architecture for networked embedded systems which exploits a differentiated services approach to guarantee control performance even in case of time-varying network condition. Control commands are transmitted as high-priority packets when the plant behavior is far from the desired target or network condition does not assure the reliable and prompt reception of commands and measurements. The assignment of different priorities to packets belonging to the same flow (i.e., commands or measurements) may lead to out-of-sequence forwarding which may compromise the plant stability and the estimation of the state at the controller side. As far as we know this is the first work which solves such important issues by combining priority-based forwarding with the passivity mechanism to ensure stability. Moreover, we adopt an optimized filter for plant state estimation which takes into account the vector of the last commands used by the plant (updated through information received from the plant together with measurements) and the vector of the last measurements. Different packet marking strategies are compared: the best one leads to the same performance of random marking by using a smaller fraction of the high-priority bandwidth.

Network design in distributed embedded applications is a novel challenging task which requires 1) the extraction of communication requirements from application specification and 2) the choice of channels and protocols connecting physical nodes. These issues are faced in the paper by adopting UML/MARTE as specification front-end and repository of refined versions of the model obtained by both simulation and analytical exploration of the design space. The emphasis is on using standard UML/MARTE elements for the description of networked embedded systems to allow re-use, tool interoperability and documentation generation. The approach is explained on a case study related to building automation.

Networked control systems are feedback systems where plant and controller are connected through lossy wired/wireless networks. To mitigate communication delays and packet losses different control solutions have been proposed. In this work the model predictive control (MPC) has been improved by introducing transmission options offering different probabilities of packet drops (high priority service and low priority service). This Differentiated Services architecture introduces Quality-of-Service (QoS) guarantees and can be used to jointly design the control command and the transmission strategy. A novel MPC-QoS controller is proposed and its design is obtained by solving a mixed integer quadratic problem.

Verification of real time embedded systems at high level of abstraction is a challenging task that requires the simulation of the system and the checking of its timing and functional properties as well as constraints. The paper presents a methodology which starts from UML sequence diagrams with MARTE timing constraints and generates a SystemC/TLM model with checkers. The execution of the model allows to verify the specified sequence of exchanged information between components while checkers allow to verify that properties and timing constraints are met. The application of the methodology to the design of a wireless sensor node shows the validity of the approach and its simulation overhead.

Verification of real time embedded systems is becoming more and more complex in terms of maintaining the code size and keeping equivalence between the specification. It requires the simulation of the system and the checking of its timing and functional properties as well as constraints. The paper presents a methodology which starts from UML sequence diagrams with MARTE timing constraints and generates a VHDL model with checkers. The simulation of the model allows to verify the specified sequence of exchanged information between components while checkers allow to verify that properties and timing constraints are met. The application of the methodology to the design of a wireless sensor node shows the validity of the approach and its simulation overhead.

The consideration of an embedded device's power consumption and its management is increasingly important nowadays. Currently, it is not easily possible to integrate power information already during the platform exploration phase. In this paper, we discuss the design challenges of today's heterogeneous HW/SW systems regarding power and complexity, both for platform vendors as well as system integrators. As a result, we propose a design flow concept that combines system-level power optimization techniques with platform-based rapid prototyping. Virtual executable prototypes are generated from MARTE/UML and functional C/C++ descriptions, which then allows to study different platforms, mapping alternatives and power management strategies. Our proposed flow combines system-level timing and power estimation techniques available in commercial tools with platform-based rapid prototyping. We propose an efficient code annotation technique for timing and power properties that enables fast host execution as well as adaptive collection of power traces. Combined with a flexible design-space exploration (DSE) approach our flow allows a trade-off between different platforms, mapping alternatives, and optimization techniques, based on domain-specific workload scenarios. The proposed flow is currently under implementation in the COMPLEX FP7 European integrated project.

Verification and design-space exploration of today's embedded systems require the simulation of heterogeneous aspects of the system, i.e., software, hardware, communications. This work shows the use of SystemC to simulate a model-driven specification of the behavior of a networked embedded system together with a complete network scenario consisting of the radio channel, the IEEE 802.15.4 protocol for wireless personal area networks and concurrent traffic sharing the medium. The paper describes the main issues addressed to generate SystemC modules from Matlab/Stateflow descriptions and to integrate them in a complete network scenario. Simulation results on a healthcare wireless sensor network show the validity of the approach.

HW-SW partitioning is a key problem in HW-SW code sign of embedded systems studied extensively in the past. All proposed approaches are top down flows, that start from a homogeneous formal specification of the system and determine an optimal partitioning. Thus, the proposed techniques do not exploit reuse nor reconsider the HWSW partitioning of an already designed platform. This paper proposes an extension of traditional flows that allows reuse and automatic generation of components and interfaces. The final flow has been applied to a complex industrial platform to prove the effectiveness and the advantages of the proposed approach.

The paper presents a design methodology for distributed applications of networked embedded systems. The original contribution is the joint perspective on communication aspects and dependability. The methodology allows to model the dependability requirements of the application under design and the degree of dependability of involved components, like nodes, communication protocols, and channels. By assessing the dependability degree of a candidate solution, the methodology allows to iterate the synthesis process until requirements are met. The effectiveness of the proposed design flow is shown by an actual case study.

Network design in distributed embedded applications is a novel challenging task which requires 1) the extraction of communication requirements from application specification and 2) the choice of a suitable communication infrastructure among physical nodes. These issues are faced in the paper by adopting a middleware-based design flow in which the middleware is also modeled and simulated as a component of the whole system. This way, the communication requirements are extracted from middleware calls and network design consists in the choice among different actual middleware implementations whose communication impact has been characterized. Experimental results on actual boards show the accuracy of the proposed methodology.

The paper addresses the design-space exploration of network alternatives for complex distributed systems of embedded devices, e.g., for smart power grid or telecommunication services. While past research mainly provided efficient programming abstractions and HW/SW simulation tools, this work introduces the network perspective in the verification of different design solutions (e.g., different task decomposition and assignment to network nodes). To do that, network simulation capability has been added to the so-called Abstract Middleware Environment and its effectiveness has been shown experimentally through the design of a wireless sensor network application taken from a real-world case study.

This article presents a methodology for the design of Networked Embedded Systems (NESs), which extends Transaction Level Modeling (TLM) to perform system/network design-space exploration. As a result, a new design dimension is added to the traditional TLM refinement process to represent network configuration alternatives. Each network configuration can be used to drive both architecture exploration and system validation after each refinement step. A system/network simulation taxonomy is investigated aiming at precisely identifying the role of cosimulation in system/network design-space exploration. Furthermore, a general criterion to map functionalities to system and network models is presented. As a case study, the proposed methodology is applied to the design of a Voice-over-IP client.

This paper presents an accurate and scalable implementation of an energy-aware simulator for wireless sensor networks (WSN's). Scalability and accuracy have been achieved through an energy-aware instrumentation of the Instruction Set Simulator of node's microcontroller and a functional SystemC TLM model of the radio module implementing the IEEE 802.15.4 protocol. The framework allows to execute actual software and to evaluate accurately its effect on the network lifetime. We first validate energy estimation results against a working hardware prototype of a wireless sensor node. The methodology, compared against state-of-the-art simulators such as NS-2, represents a flexible and scalable solution for fast and accurate prototyping of WSN software.

Dependability is becoming a key design aspect of today networked embedded systems (NES's) due to their increasing application to safety-critical tasks. Dependability evaluation must be based on modelling and simulation of faulty application behaviors, which must be related to faulty NES behaviors under actual defects. However, NES's behave differently from traditional embedded systems when testing activities are performed on them. In particular, issues arise on the definition of correct behavior, on the best point to observe it, and on the temporal properties of the faults to be injected. The paper describes these issues, discusses some possible solutions and presents a new time-varying network-based fault model to represent failures in a more abstract and efficient way. Finally, the fault model has been used to support the design of a network-based control application where packet losses, end-to-end delay and signal distortion must be carefully controlled.

The literature does not report a complete design methodology for WSN applications integrating all these aspects. The proposed methodology allows programmers to write WSN applications by using the system description language SystemC and the Abstract Middleware Environment (AME) framework for fast sim

Next-generation networked embedded systems pose new challenges in the design and simulation domains. System design choices may affect the network behavior and network design choices may impact on the system design. For this reason, it is important -at the early stages of the design flow- to model and simulate not only the system under design, but also the heterogeneous networked environment in which it operates. For this purpose, we have exploited a modeling language traditionally used for System design -SystemC- to build a system/network simulator named SystemC Network Simulation Library (SCNSL). This library allows to model network scenarios in which different kinds of nodes, or nodes described at different abstraction levels, interact together. The use of SystemC as unique tool has the advantage that HW, SW, and network can be jointly designed, validated and refined. As a case study, the proposed tool has been used to simulate a sensor network application and it has been compared with NS-2, a well-known network simulator; SCNSL shows nearly two-order-magnitude speed up with TLM modeling and about the same performance as NS-2 with a mixed TLM/RTL scenario. The simulator is partially available to the community at http://sourceforge.net/projects/scnsl/.

In this paper we present an energy-aware framework for the design of wireless sensor networks, based on a hardware/software/network co-simulation strategy. The framework enables fast development and optimization of software power management policies, since it allows to run real software that can be easily ported on target hardware nodes. The capabilities of the simulation framework have been stressed by comparing different power management strategies, exploring their power-performance trade-offs and their effectiveness in various network conditions.

This paper presents a comprehensive analysis of a variable time-scale streaming technique, VTSS, according to which rate changes are obtained by varying the inter-packet transmission interval, rather than altering, as in most cases, the source coding rate. Instead of constraining the transmitter to operate in real-time, the time scale of the packet scheduler can vary between zero, when the network is congested, to as faster than real-time as the channel bandwidth allows, when the network is lightly loaded. Although this approach is reportedly used in commercial streaming products, so far the technique has not yet been analyzed in a rigorous fashion, nor it has been compared to other state-of-the-art streaming techniques. This work first presents a theoretical analysis of the performance achievable by the VTSS approach, and it shows that, for the same channel conditions, VTSS yields a total distortion which is lower or, in the worst case, equal than the distortion of the standard real-time source-rate adaptive approach. A lower bound on receiver buffer size is also derived. Network simulations then analyze the performance of a TCP-friendly test implementation of VTSS compared with an ideal real-time source rate-adaptive technique, whose performance, being ideal, represents the upper bound of any transmission scheme based on source rate adaptation. The simulation results, also based on actual network traces, show that the VTSS approach delivers higher perceptual quality (up to 1.2 dB PSNR in the considered scenarios) and reduced video quality fluctuations (1.6 dB standard deviation PSNR, instead of 4.9 dB) for a wide range of standard video sequences. Perceptual quality evaluation by means of PVQM confirms such results. The gains, as expected, are even more pronounced (7.6 dB PSNR on average) if compared to real-time constant bit-rate video transmission.

This paper addresses the problem of modeling and simulating large set of heterogeneous networked embedded systems which cooperate to build cost-efficient, reliable, secure and scalable applications. The purpose of this task is an application-driven top-down design flow which starts from application requirements and then progressively decides the general architecture of the system and the type and structure of its HW, SW and network components. In the past, a considerable research effort has been done to create specific tools for each design domain - software, hardware and network - and to integrate them for data exchange between models and their joint simulation. However the advantages and drawbacks of different combinations of tools in the various stages of the design flow have not been discussed. The paper describes and discusses how to combine different modeling tools to provide different modeling and simulation alternatives for the design of networked embedded systems devoted to complex distributed applications. The problem is faced both theoretically and practically with a real application derived from a European project

The paper focuses on the design of networked embedded systems which cooperate to provide complex distributed applications. A milestone in the effort of simplifying the implementation of such applications has been the introduction of a service layer, named middleware, which abstracts from the peculiarities of the operating system and HW components. However, the presence of the middleware has not been yet introduced in the design flow as an explicit dimension. This work presents an abstract model of middleware supporting different programming paradigms; it can be used as component in the design flow and allows to simulate and develop the application without doing premature assumptions on the actual HW/SW platform. At the end of the design flow the abstract middleware can be mapped to an actual middleware. The methodology has been analyzed both theoretically and practically with the actual application on a wireless sensor network

This paper addresses the problem of improving the quality performance of synthetic video sequences by means of standard frame-based coders. The proposed technique can exploit both the knowledge of the 3D model and the intermediate information computed during the rendering process. Firstly, objects are classified, either semantically or automatically, according to their importance. Then the object classification is translated into a macroblock classification, with particular attention to object boundaries. The classification influences the encoder parameters selection, for instance, the quantization parameter. In order to maximize the performance, we propose a rate-distortion formulation of the problem. Experimental results compared with model-unaware encoding show that the proposed techniques can deliver consistent visual quality improvements for different synthetic scenarios using the same bitrate or even less. Demo sequences are available at http://media.polito.it/perceptual3d.

In video encoding, block motion estimation represents a CPU-intensive task. For this reason, many fast algorithms have been developed to improve searching and matching phases. A milestone within the lossless approach is partial distortion elimination (PDE/SpiralPDE) in which distortion is the difference between the block to be coded and the candidate prediction block. In this paper, (i) we analyze distortion behavior from local information using the Taylor series expansion and show that our general analysis includes other previous similar approaches. (ii) Then, we propose two full-search (lossless), fast-matching, block motion estimation algorithms, based on the PDE idea. The proposed algorithms, called fast full search with sorting by distortion (FFSSD) and fast full search with sorting by gradient (FFSSG), sort the contributions to distortion and the gradient values, respectively, in order to quickly discard invalid blocks. Experimental results show that the proposed algorithms outperform other existing full search algorithms, reducing by up to 20% the total CPU encoding time (with respect to SpiralPDE), while the computation strictly required by the motion estimation is reduced by about 30%. (iii) Finally, we experimentally find an operational lower bound (based on standard test sequences) for the average number of checked pixels in the PDE approach, which measures the performance of the searching and matching phases. In particular, SpiralPDE achieves performances very close to the searching phase bound, while there is still a remarkable margin on the matching phase. We then show that our algorithms, aimed at improving the performances of the matching phase, achieve interesting results, significantly approaching this margin.

The paper addresses the problem of improving the MPEG compression of synthetic video sequences by exploiting the knowledge about the original 3D model. Two techniques are proposed for the specific case of a virtual walkthrough in which the point of view is the unique moving object in the scene. Technique 1 consists of using only P-frames when position and direction of the point of view do not change since, in this case, each frame is equal to the previous one; P-frames can be simply repeated without any encoding effort thus reducing the computational complexity. Technique 2 consists of increasing the quantization parameter when the direction of the point of view is changing, since the resulting increase of distortion is not perceived clearly for fast-moving objects because of the temporal masking effect. Experimental results compared with model-unaware encoding shows that Technique 1 reduces the bitstream size by about 9% without any appreciable decrease of perceptual quality while CPU encoding time is reduced by about 18%. The combination of both techniques reduces the bitrate by about 13% with a slight increase of the quantization noise which is partially hidden by the temporal masking effect.

In video communications over IP networks, quality of service (QoS) guarantees must be introduced to limit the effect of packet losses. In particular, end-to-end QoS can be improved if packets are protected according to the distortion that would be introduced at the receiver by their loss. In the traditional analysis-by-synthesis (AbS) approach, each packet is assumed lost, error concealment applied, the sequence decoded, and the resulting overall distortion computed. This process produces reliable distortion estimates, but is computationally demanding. In this work, we present a hybrid approach: the distortion introduced in the current frame is evaluated with the AbS method, while the distortion in future frames is estimated by means of a statistical error-propagation model. Results obtained on eight, widely different H.264 sequences show that the proposed model successfully estimates overall distortion with very low complexity. Network simulations also show that model-based packet classification, when used for video transmission over DiffServ networks, delivers PSNR results which are consistently within 0.1 dB compared to the AbS technique.

This paper presents the adaptive video over IP (AViP) approach to transmit video sequences. A rate-selection algorithm based on both delay and loss indication is presented and its performance measured using actual MPEG-2 video sequences, network simulations and objective measures of perceptual quality. The results show that the AViP approach leads to efficient use of available network resources, reactiveness to congestions and TCP-friendliness. Moreover, AViP delivers significantly higher perceptual levels of quality than traditional constant-bit-rate systems operating at the same average level.

This paper describes a technique to deliver video streams with constant perceptual quality of service (QoS) over time-varying packet erasure channels that support differentiated classes of service. During compression, the encoder estimates the distortion introduced at the decoder by each video packet both in case it is received and in case it is lost. Concealment and error propagation due to inter-frame prediction are taken into account. During transmission, an optimization algorithm assigns packets to different service classes according to the estimated distortion, the current channel status and a constraint on the desired quality at the receiver. This technique is compared with other video packet classification approaches in the specific case of a DiffServ IP network implementing the assured forwarding scheme. Network simulations show that the proposed technique delivers higher and more constant levels of perceptual QoS than traditional approaches. Moreover, the technique is characterized by reactiveness to congestion and fairness in the use of network resources.

We present an interactive educational DSP platform for realtime subband audio coding. The tool integrates a DSP course on advanced audio coding and focuses on wavelets, subband coding, and signal quantization. The package consists of a Windows control application running on a PC and real-time DSP code implemented on a Texas Instruments DSP Starter Kit (DSK), which performs the actual audio encoding and decoding process. The tool is interactive since students can customize the codec by changing some encoding parameters through the PC interface and then verify the effect on the coding process. The DSP codec accepts audio samples in real-time via the DSK audio analog input port and sends the reconstructed samples to the output port. The graphical user interface allows to choose the type of filter-bank and scalar quantization; the availability of the full source code and of a DSK makes possible to experience first-hand the main aspects of real-world DSP development, e.g., real-time programming, arithmetic precision and algorithmic delay. The software is available at http://multimedia.polito.it/dspwavelab.

Constant levels of perceptual quality of service is what ideally users of multimedia services expect. In most cases, however, they receive time-varying levels of quality of service. This paper describes a technique to deliver nearly constant perceptual quality of service when transmitting video sequences over differentiated services IP networks. MPEG video packets are transmitted either as low-loss premium packets or as regular best-effort packets depending on their individual perceptual importance. On a frame-by-frame basis, allocation to the premium class is performed depending on the perceptual importance of each macroblock, the desired level of quality of service and the instantaneous network state. The resulting perceptually-based, time-varying use of premium and best-effort network resources delivers nearly constant quality of service to end users and it yields significant higher PSNR values compared to constant allocation of premium bandwidth.

We present a distortion-based approach to packet classification for multimedia transmission over differentiatedservices packet networks. Instead of sending all traffic as premium or relying on a priori data partitioning, packets are individually examined and assigned to different service classes depending on the level of distortion that their loss would introduce at the decoder. Applied to video sequences encoded with the ISO MPEG-2 video coding standard, the proposed distortion-based packet marking scheme outperforms source-transparent techniques and provides substantial and consistent gains in PSNR over the regular best-effort case sending as little as 10% of the packets as premium traffic. Video samples are available at #####################################.

We present a new algorithm for the dynamic identification of perceptually important regions in pictures of a video sequence. For each macroblock, the distortion that its loss would cause at the decoder is computed. High-distortion macroblocks are then grouped together into slices to be protected with forward error correction or to be sent as "premium" packets. We developed the approach for the case of video sequences encoded with the ISO MPEG-2 video coding standard. We then applied the algorithm to classify video packets within a 1-bit differentiated services architecture: slices were grouped either into premium packets, to be sent on a "virtual wire", or into regular packets, to be sent as best-effort traffic. In packet losses, the proposed distortion-based classification scheme outperforms source-transparent packet-marking techniques and provides substantially higher PSNR values than the regular best-effort case sending as little as 10% of the packets as premium traffic. Video samples are available at http://multimedia.polito.it/mmsp2001/.