Abstract IoT video applications such as public transportation, traffic monitoring, parking and surveillance systems in smart cities collect and transmit video over multi-hop wireless network fabrics which are known to be less reliable and responsive as their wired counterparts. While multipath routing has emerged as an effective strategy to help meet IoT video transmission’s, one of the main challenges current multipath routing approaches face is to be able to select routes that meet the requirements of the driving video applications in a timely manner. To fill this gap, we recently proposed FITPATH, an adaptive multipath selection mechanism for IoT video transmission that uses a heuristic-based iterative optimization approach to estimate in real time the conditions of the underlying network while accounting for the different bitrate requirements of the application video flows. To provide a complete understanding of FITPATH’s performance, limitations, and applicability in realistic IoT video transmission scenarios, this work presents a comprehensive experimental evaluation of FITPATH under a wide range of conditions. We demonstrate that FITPATH consistently outperforms existing multipath selection mechanisms in terms of both end-user Quality of Experience (QoE) and overall network performance. We also evaluate the performance and convergence of FITPATH’s heuristic, showing that it quickly generates feasible solutions and incrementally improves QoE as the algorithm iterates. Furthermore, we propose practical deployment strategies for FITPATH under both centralized and decentralized network control plane architectures. Additionally, we analyze the impact of control messages and network dynamics on video quality in decentralized network control plane environments.

This paper presents a HaLow wireless simulator, which provides a simulated environment based on the IEEE 802.11ah standard. The simulator allows generating metrics to evaluate network performance considering groups generated by the Restricted Access Window (RAW) mechanism. Users can also provide grouping configurations through input files for testing with custom grouping algorithms. Evaluation results show that the simulator scales efficiently while maintaining low memory footprint and execution time, even in large-scale network scenarios with 1,000 stations.

Video applications in the Internet of Things benefit from multipath routing strategies to meet Quality of Service requirements. Although several multipath selection mechanisms have been proposed, changes in topology and/or in video services requirements can impact video quality. This work presents a wireless network architecture that enables dynamic routing, adapting these changes to new path solutions that provide a better Quality of Experience for the users. Simulation results demonstrated that the proposed architecture is capable of recovering video quality in case of degradation due to topology change, as well as also confirming that the presence of control flows, essential for maintaining the topology, reduces the final video quality.

Connected and digital electricity substations based on IEC–61850 standards enable novel applications. On the other hand, such connectivity also creates an extended attack surface. Therefore, Intrusion Detection Systems (IDSs) have become an essential component of safeguarding substations from malicious activities. However, in contrast to traditional information technology systems, there is a serious lack of realistic data for training, testing, and evaluating IDSs in smart grid scenarios. Many existing substation IDSs rely on datasets from other contexts or on proprietary datasets that do not allow reproducibility, validation, or performance comparison with competing algorithms. To address this issue, we propose the Efficacious Reproducer Engine for Network Operations (ERENO) synthetic traffic generation framework based on the IEC–61850 standard specifications. As an additional contribution, and as a proof-of-concept, we create and make available a suite of realistic IEC–61850 datasets that model 8 use cases, namely traffic for 7 common attacks and one for normal network traffic. Based on those datasets, we further evaluate how enriched features combining raw data from the substation can significantly improve intrusion detection performance. Our results suggest that it can improve F1-Score up to 47.22% for masquerade attacks.

For Internet of Things devices, one of the main power demands comes from the radio interfaces. Hence, duty cycling, i.e., activating and deactivating the radio, becomes essential to energy savings. In asynchronous scenarios, scheduled-based duty cycle methods stand out for their low deployment cost. Recently, the literature reports many studies on asymmetric scheduled-based methods — i.e., different nodes operating under different duty cycles. In this work we propose an extension of this concept: the heterogeneous duty cycling. It allows nodes to operate under schedules generated by distinct methods, resulting in a wider range of duty cycle choices and also a better coexistence between devices from different manufactures. In particular, we study which combinations of methods present the rotation closure property, and what are the average and maximum latencies for those pairs. We also show that heterogeneous duty cycling can improve performance if schedules are properly selected.

Private blockchain platforms tend to apply deterministic consensus mechanisms as a more efficient alternative to the proof-based consensus. Deterministic mechanisms tolerate two types of failures, Byzantine, and Crash-Fault. Byzantine-Fault tolerant consensus assumes restrictive assumptions of time and number of failures to guarantee the validity, while the termination depends on node message broadcasting. Crash-Fault tolerant consensus mechanisms induce lower overhead and faster termination than Byzantine-Fault tolerant mechanisms at the cost of not tolerating malicious behaviors. This paper explores different overlay topologies to assess a lightweight consensus mechanism based on vicinity voting with reliable message broadcasting. The paper proposes different ways to compose the consensus quorum according to the vicinity models. Vicinity models applied in the overlay network allow for relaxing the trade-off between agreement and termination. Analytical and experimental results for different physical topologies show that certain vicinity models guarantee higher number of nodes reached at the time of reaching the consensus threshold (higher than 90% of all nodes) with a lower cost at the exchange of lower fault tolerance. Other models induce a lower agreement while increase fault tolerance (higher than 50%).

Evaluating wireless links is a common task for many control mechanisms. However, the inherent variability of those estimates negatively impacts network performance. To reduce this variability, the Hypothesis Test Estimator (HTE) was recently developed as an alternative to the commonly employed moving averages. Performance analyses carried out in recent works found that HTE returns more stable estimates at the cost of a typically larger average estimate error. This work uses numerical simulations to complement the previous analyses, but now under the perspective of convergence time –i.e., how long it takes for actual changes in the link quality to be reflected in the estimates. Our results indicate that HTE has, in general, a better convergence time than the moving averages. They also show that further improving HTE's convergence time is not trivial, as simple variations of the method that aim to improve convergence do not result in significant gains.

Cyber-Physical Systems (CPS) are the basis for the world’s critical infrastructure and, thus, have the potential to significantly impact human lives in the near future. In recent years, there has been an increasing demand for connectivity in CPS, which has brought to attention the issue of cybersecurity. Aside from traditional information systems threats, CPS face new challenges due to the heterogeneity of devices and protocols, as well as its strong reliability requirements. In this work, we provide a brief overview of the CPS architecture and applications and describe the security challenges in the three CPS layers of perception, transmission, and application. Besides, we discuss how feature selection (FS) may improve intrusion detection performance. In particular, we evaluate how metaheuristic approaches can improve classification performance in CPS perception, transmission, and application layers. Our results reveal that (i) Greedy Randomized Adaptive Search Procedure (GRASP) outperforms traditional filter-based methods, and (ii) using the proposed enhanced approaches in GRASP construction and local search phases can enhance the average F1-Score of five classifier algorithms.

Private blockchains tend to apply deterministic con-sensus mechanisms as a more efficient alternative to the proof-based consensus. Deterministic mechanisms tolerate two types of failures, byzantine and crash-fault. Byzantine fault-tolerant consensus assumes restrictive assumptions of time and number of failures to guarantee validity, while the termination depends on message broadcasting among nodes. Crash-Fault tolerant consensus is less rigorous to ensure termination and higher throughput while sacrificing agreement. This paper proposes a lightweight consensus mechanism based on vicinity voting with confirmed message broadcasting. Formation rules in the neighborhoods of the peer-to-peer network relax the trade-off between agreement and termination. Experimental results show that the proposal guarantees agreement and termination in case of more permissive formation rules. Besides, the cost of achieving consensus is reduced by up to 46% in more rigorous formation rules with limited impact on termination and agreement.

With the development of wireless technologies and the proliferation of sensors, Wireless Sensor Networks (WSNs) have been widely used in many applications. However, their energy constraints make energy reduction one of the main project concerns. Among the several solutions in the literature, schedule-based asynchronous duty cycle methods are the simplest because they do not require synchronization mechanisms, protocols nor specific hardware, while facilitating the entry of new nodes. However, scenarios with sporadic events can benefit from nodes operating on different schedules. This work evaluates asymmetric asynchronous duty cycle schedules for possible use in such scenarios. Using numerical simulations, we show that, for some asymmetrical pairs of schedules, the overlap of active slots is guaranteed which enables the communication between the nodes. Also, depending on the choice of the pairs of schedules, an asymmetric setup allows a reduction in the Neighbor Discovery Time in relation to the symmetric methods.

Advances in electronics have enabled the development of intelligent miniaturized biomedical sensors that can be used to monitor the human body. The use of wireless communication proved to be an alternative, which provides less discomfort to patients and good cost-benefit. In order to fully exploit the benefits of wireless technologies in e-health, a new type of wireless networks has emerged: Wireless Body Area Networks (WBANs). However, technical and social challenges must be addressed to enable their adoption. Some factors, such as the use of the human body as a propagation media, the effects of radiation on human tissue and human body movements, make WBANs a new paradigm of wireless communication networks. As a person moves, transmission channel quality may vary depending on body position, which may result in poor network performance. To meet the requirements of WBAN applications, while preserving the energy efficiency and the user's physical safety, this paper proposes B-Move, a WBAN transmission scheduler based on the movement of the human body. Our proposal was analyzed in Castalia Simulator and obtained results present improvements in packet delivery rate and energy efficiency, when compared to polling and contention-based medium access (CSMA/CA) used in the WBAN IEEE 802.15.6 standard.

Medical images are important elements for the diagnosis of diseases. Computer Aided Diagnostic has evolved in recent years along with the processing capacity of computers as well as the emergence of new computational techniques. Segmentation is a valuable approach for identifying a specific area in human body images, such as the lungs and heart. This work proposes an algorithm to segment anatomical structures using parallel 3D region growing. Experiments using different Computer Tomography scans show that the proposed approach can run 150 times faster than the typical sequential region growing algorithm while providing good results in the identification of the target region.

The Smart Grid is a high availability system that requires fault recovery protocols to minimize downtime. In addition, recovery, in most cases, must be made within certain temporal constraints. The IEC 62493-3 standard defines the Parallel Redundancy Protocol (PRP) and High-availability Seamless Redundancy (HSR) as protocols for dealing with link layer communication failures in electrical substations. There are variations that perform the same functionality handling packets at the IP layer, such as iPRP. Those protocols promise zero-time recovery by proactively sending duplicate packets across distinct and independent paths. In this paper, those fault recovery protocols are analyzed by means of simulations. Our results show that, in realistic setups, recovery time is never actually zero and that, under certain conditions, this time can exceed the temporal requirements that some protection applications demand for proper operation.

Electronic medical records (EMRs) are highly sensitive information shared among peers to keep up-to-date patient history. Providing security, privacy, and availability to these sensitive data is a challenge because, typically, after data publication the patient loses control over them. In this paper, we propose a blockchain-based approach to secure EMR for healthcare applications, where access control is patient-centric. Our proposal keeps encrypted EMRs in the blockchain, and the patient shares the decryption key only with healthcare professionals in which he/she trusts. Blockchain allows untrusted node, in a distributed peer-to-peer network to correctly and verifiably interact with each other, without any reliable intermediary. We investigate the scalability of our approach through simulations. Results show that it scales well since increasing the number of nodes in the network implies a linear increase in the size of the stored chain. Results also reveal that the time for inserting a new EMR in the blockchain remains low even when the number of nodes in the network increases.

Association instability is a common phenomenon in dense networks. The decision of whether or not to perform a handoff between access points in an infrastructured IEEE 802.11 network is taken exclusively by the wireless client stations. Even without mobility, static client devices may decide to migrate to another access point with the goal of improving performance. However, the criteria used to perform handoffs are not defined by the IEEE 802.11 standard and, thus, are dependent on specific vendor implementations. In this paper, we use data from a real large scale network and run experiments to demonstrate that such implementations are commonly deficient, resulting in high levels of association instability in dense environments. By analyzing the implementation used by the most common devices, we were able to conclude that this instability, known as the “ping-pong effect”, results from the direct usage of RSSI samples which are highly variable. Finally, we analyze the behavior of RSSI in indoor environments showing that its time series presents multimodal distribution. We argue that the findings presented in this study can help develop more stable handoff algorithms for dense wireless networks.

HTTP streaming has become a practical technique to distribute multimedia content. This work proposes an adaptation method that improves the user's quality of experience when they consume video streaming over HTTP, compared to other methods considered state of the art. Based on the study of existing adaptation methods, we propose a new approach called Relative Smoothed Throughput (RST) method. Experiments with varying bandwidth conditions and multiple flows show that RST is able to outperform state of the art methods in efficiency.

Simulating new protocols for e-health systems is very important, as it allows an initial evaluation before a real implementation is made. On the other hand, network simulators do not offer proper support to represent medical applications or components to facilitate running simulations modeling e-health applications. The lack of simulators that specify the sensor type and its communication requirements make real experiments harder. Aiming at fulfilling this gap, this paper proposes the use of ISO/IEEE 11073 standard for Personal Health Devices (X73-PHD) in e-health network simulations, representing realistic medical applications and investigating the behavior of medical devices (sensors or actuators) in Wireless Body Area Network (WBAN) scenarios. We developed a free and open-source implementation of X73-PHD for Castalia Simulator, providing five different PHD types to act like real ISO/IEEE 11073 devices in WBAN simulations. Our implementation supports Agent-initiated mode, where PHDs take the initiative to send measurements to the hub. Our implementation also supports the unconfirmed communication mode and the confirmed communication mode, where the receiver sends an acknowledgment to the sender every time it receives a packet. Simulation results showed that the confirmed communication mode did not perform well in WBANs when the interval between transmissions is too small, due to the long period of timeout proposed in the X73-PHD standard. Therefore, we propose a new extension to the confirmed mode standard that decreases the overhead of control packets over the network, using smaller timeouts and delivering more packets.

-In Wireless Sensor Networks, nodes typically employ batteries that cannot be easily recharged or replaced. Hence, optimizing energy consumption is a major concern. Among the several proposals in the literature, schedule-based asynchronous duty cycle methods are the simplest because they do not require mechanisms, protocols or specific hardware for clock synchronization between nodes. These solutions, however, result in high latency for multi-hop communication. In this work, we show how existing asynchronous mechanisms can benefit from a low level of synchronism, with resolution of slots. Assuming this possibility, we show through mathematical models, numerical and network simulations that the use of specific offsets between clocks of neighboring nodes, according to their distances to the sink node, significantly reduces latency.

Wireless mesh networks are multi-hop wireless networks which are useful in situations where there is little or no network infrastructure. Recently, those networks have been proposed for scenarios of Smart Grids and Internet of Things. The variability in routing metrics, which causes frequent changes in path choice, is a challenge in these networks. In this article, we propose a method, called Hypothesis Testing Estimator (HTE), for estimating the frame delivery probability of a link based on the concept of hypothesis testing. In this method, the estimate is fixed until the link behavior in the recent past significantly deviates from the expectation. The method was evaluated using simulations whose results show a significant reduction in the variability of the link quality estimates.

The Internet of Things (IoT) is increasingly a reality today. Nevertheless, some key challenges still need to be given particular attention so that IoT solutions further support the growing demand for connected devices and the services offered. Due to the potential relevance and sensitivity of services, IoT solutions should address the security and privacy concerns surrounding these devices and the data they collect, generate, and process. Recently, the Blockchain technology has gained much attention in IoT solutions. Its primary usage scenarios are in the financial domain, where Blockchain creates a promising applications world and can be leveraged to solve security and privacy issues. However, this emerging technology has a great potential in the most diverse technological areas and can significantly help achieve the Internet of Things view in different aspects, increasing the capacity of decentralization, facilitating interactions, enabling new transaction models, and allowing autonomous coordination of the devices. The paper goal is to provide the concepts about the structure and operation of Blockchain and, mainly, analyze how the use of this technology can be used to provide security and privacy in IoT. Finally, we present the stalker, which is a selfish miner variant that has the objective of preventing a node to publish its blocks on the main chain.

The search for service providers (e.g., ambulance, fire truck, etc.) after a disaster, must take place within a short time. Therefore, service discovery protocol which looks for providers that can attend victims, respecting time constraints, is crucial. In such a situation, a commonly solution for ensuring network connectivity between victims and providers is ad hoc networks (MANET), composed by battery-operated mobile nodes of persons (victims or not). However, an efficient service discovery protocol must care about energy consumption of mobile nodes and also prevent useless movement of providers. These are the aims of the Resource Reservation Protocol (ΔRRP), presented in this paper. Applying both Gauss-Markov [1] and Mission Critical Mobility [2] models to characterize human mobility, performance evaluation results on the Network Simulator NS2 confirm the effectiveness of ΔRRP protocol when compared to other protocols.

The inherent complexity of Wireless Mesh Networks (WMNs) makes management and configuration tasks difficult, specially for fault detection and diagnosis. In addition, manual inspections are extremely costly and require a highly skilled workforce, thus becoming impractical as the problem scales. To address this issue, this paper proposes a solution that makes use of machine learning techniques for automated fault detection and diagnosis (FDD) on solar-powered Wireless Mesh Networks (WMNs). We have used the Knowledge Discovery in Databases (KDD) methodology and a pre-defined dictionary of failures based on our previous experience with the deployment of WMNs. Thereafter, the problem was solved as a pattern classification problem. Several classification algorithms were evaluated, such as Naive Bayes, Support Vector Machine (SVM), Decision Table, k-Nearest Neighbors (k-NN) and C4.5. The SVM presented the best results, achieving a 90.59% overall accuracy during training and over 85% in validation tests.

The rapid growth of wireless networking technologies, the emergence of several new devices that offer or need Internet interconnection, and a pent-up demand for wide band access, especially away from the big cities, are hampered by the problem of the frequency spectrum exhaustion for telecommunications services. A more efficient use of the spectrum passes through solutions, such as the improvement and deployment of radios with cognitive ability. In this context, the problem of neighbor discovery extends not only for the initial blind rendezvous, but also for the maintenance of periodical encounters of neighbors after such initial encounter. At this stage, it will be necessary for a node that has already found a peer to interrupt its data communication, so that nodes can become aware of changes in their surroundings and the network can support the addition of new nodes. The contribution of this paper is the creation of asynchronous, distributed and robust schedules to guarantee multiple continuous rendezvous and communication opportunities between two or more cognitive radios using control channels, employing frequency hopping with new sequences and mappings based on combinatorial design theory.

Named Data Networking (NDN) is one of the promising proposals of Future Internet Architectures (FIAs). Similarly to most of the other FIA proposals, NDN promises better performance and resilience against current Internet attacks. However, NDN's resilience has not been largely analyzed yet, in special the flooding attacks that exploit the content request and distribution data structure in NDN routers (called Pending Interest Table - PIT). This paper focuses on analyzing this type of denial of service (DoS) attack. It proposes an analytical model that helps to understand the conditions that make the architecture more or less susceptible to this threat. Evaluation shows that the model is useful to analyze the circumstances in which the PIT is more vulnerable to flooding attack. An extension of the model is used to formulate an optimization function which maximizes the system throughput, minimizing the effects of a DoS attack.

This paper proposes LIBR, a routing protocol for Wireless Mesh Networks specially designed for linear topologies, i.e., topologies in which nodes are placed following a well-defined line-based pattern. This kind of topology may arise, for example, in power transmission lines, pipelines, roads, and railway lines. By exploring the intrinsic characteristics of these linear topologies, LIBR can achieve good performance and scalability, while being simple and incurring in low overhead for the network. Even employing a heuristic next hop selection procedure, in our simulation results, we found that LIBR was able improve network goodput in typical linear topologies up to 22%, when compared to traditional ad hoc routing protocols. Our analysis suggests that this improvement comes from a number of reasons, including better sharing of network resources (such as nodes' queues and the wireless medium itself). Finally, due to its heuristic nature, LIBR results in lower levels of control overhead, increasing the network energetic efficiency in 14% in our simulations.

Smart Grid represents the evolution of the current electrical power system. It is designed to meet the challenge of increasing demands for energy by fully integrating the electrical power grid with data communication networks. One of the main challenges faced by this kind of network is to fulfill reliability and resilience requirements in order to meet various types of services and applications. Wireless mesh networks can provide scalability and resilience to this communication network, but there are issues that need to be addressed before it can be used in practical smart grids. One of these issues relates to the robustness of the network when it faces gateway failures. In this situation, communication to smart meters may be unavailable for a considerable amount of time, which is prohibitive for many types of applications. In this sense, we present DDSA, an algorithm for dynamic selection of gateways in a multihoming smart grid network. The algorithm uses a probabilistic approach for choosing gateways, prioritizing those with the most reliable paths. Results indicate that DDSA increases network robustness and resilience in the presence of gateway failures compared to existing algorithms for dynamic gateway selection.

A basic property of wireless networks is the half duplex nature of their links. However, previous works have already shown, with real prototypes of full duplex radios, to be possible for a node to transmit and receive packets at the same time. Nevertheless, the gains that result from such techniques are not straightforward. In this work we analyze how frequently full duplex transmissions can occur in typical wireless network scenarios. Simulations were conducted in both infra-structured and multihop networks with several traffic patterns, and results show potential gains up to 99.96% and 36.93% in the infra-structured and multihop cases, respectively.

Traditional techniques for delay calculation between neighbor nodes involve the exchange of frames and assume link symmetry. This approach, besides being costly in terms of energy, is not a good fit for wireless sensor networks, where links are typically asymmetric. On the other hand, MAC layer timestamps eliminate the asymmetry problem, but depend on specific hardware. In this paper, we present a Simple Technique for Local delay Estimation (STELE) which is hardware independent, eliminates the need for bidirectional communication, and is therefore applicable to asymmetric links. Furthermore, experimental results with real sensors motes indicate that STELE is energy efficient in comparison to existing methods.

Content-Centric Networking is an architecture proposal for the future Internet that brings fundamental changes in the way the network operates. Contents are identified and requested based on their names and for security reasons they must be digitally signed by their publishers. Even though this new architecture was designed to be safe, one potential security threat is that malicious publishers may create polluted versions of legitimate contents, reducing their availability and degrading network resources. Because of the non-negligible overhead of checking a large number of signatures, it is not feasible to make it a mandatory task for every router, especially in the network core. In this paper, we propose CCNCheck: a mechanism in which CCN routers probabilistically check the content signatures. We evaluate the mechanism against simulations and found evidences that using CCNCheck increases the fraction of recovered contents and decreases the wastage of network resources.

ABSTRACT Security in wireless sensor networks demands an efficient key management scheme. As sensors typically operate unattended, it becomes quite important to ensure security to cryptographic keys stored in their memories. In this scenario, the development of lightweight encryption mechanisms is a challenge because of sensor‐constrained resources. In this work, we present a mechanism tailored to sensor networks calledSENSORLockapplying it to a specific case. Our main contribution is to propose, analyze, and demonstrate the feasibility ofSENSORLockfor secure symmetric key distribution solving the stored key exposure problem. Analytical results demonstrate that this approach increases the system's security against the tampering of sensor nodes. Additionally, the mechanism is evaluated using simulation and practical experiments, using the TinyOS platform. Simulation results reveal that this scheme introduces very low processing overhead, in the order of nanoseconds, and an estimated power consumption quite similar to existing approaches. Besides, practical experiments indicate that the scheme can be deployed by off‐the‐shelf sensors, such as MicaZ and TelosB. Copyright © 2013 John Wiley & Sons, Ltd.

This paper analyzes the process of sending a coded packet in the wireless medium. Understanding this basic network coding operation is fundamental for the recent work on coding aware routing. Unlike the transmission of a native (not coded) packet, a coded packet can be partially received, i.e., received by only a subset of its intended receivers. The literature on this subject has relied on strong assumptions to simplify the models for evaluating routes. Specifically, most works adopt the hypothesis of independence between the events of reception by different receivers. In this paper we present theoretical arguments and experimental results that show this hypothesis is not valid in practical cases. To overcome this issue, we present a simple, yet effective, method for estimating the joint reception probability for a coded packet. We also discuss the mechanisms that are used in the literature to implement the operation of transmitting a coded packet to a group of receivers and conclude that they are still inefficient. As a result of this analyses, we propose a new mechanism that maximizes the joint reception probability of the packet. Our experimental results show that this novel mechanism outperforms other commonly used techniques.

In Delay and Disruption Tolerant Networks (DTNs), the message delivery rate is impacted by the buffer management policy adopted by nodes once buffer overflows occur frequently. This paper proposes two new buffer management policies. The first one, called LPS (Less Probable Sprayed), uses the messages delivery probability and estimates the number of replicas already disseminated to decide which message to drop. The second one, named LRF (Least Recently Forwarded), drops the least recently forwarded message based on the assumption that messages not forwarded over a certain period of time have already reached several next hops. These two policies are implemented and compared with existing proposals found in the literature. The analysis considers traces of three real networks in which LPS and LRF policies provide higher delivery rates up to 75% and 37%, respectively, than the rate provided by the second best policy, with less overhead.

This paper presents MARA, a joint mechanism for automatic rate selection and route quality evaluation in wireless mesh networks. This mechanism targets at avoiding the problems of lack of synchronization between metric and rate selection decisions and inaccurate link quality estimates, common to main existing proposals of multihop wireless routing metrics and automatic rate adaptation. In this proposal, the statistics collected by the routing protocol are used by the rate adaptation algorithm to compute the best rate for each wireless link. This coordinated decision aims at providing better routing and rate choices. In addition to the basic MARA algorithm, two variations are proposed: MARA-P and MARA-RP. The first considers the size of each packet in the transmission rate decision. The second variation considers the packet size also for the routing choices. For evaluation purposes, experiments were conducted on both real and simulated environments. In these experiments, MARA was compared to a number of rate adaptation algorithms and routing metrics. Results from both environments indicate that MARA may lead to an overall network performance improvement.

This paper discusses wireless mesh network topology visualization tools and their requirements. It presents an interactive tool for visualizing mesh network topologies. The proposed tool uses the SVG — Scalable Vector Graphics — web standard, which is based on XML, to build the network map. In a wireless mesh network, link quality varies quite often, therefore the visualization tool dynamically displays the quality metric of each link, in addition to presenting router configuration information and other network statistics. This work also introduces a configuration tool designed to adapt the topology view to different wireless mesh environments.

This paper proposes an algorithm for the adaptive adjustment of the transmission rate of VoIP sources based on the voice quality estimated at the receiver. This adjustment is achieved through the appropriate use of differing voice codecs, as the conditions of the network change, in order to maintain an efficient utilization of the available resources. To validate our proposal realistically, we have made an effort to simulate VoIP calls using sources that follow Brady's model of human conversations. We investigate the effects of the proposed model on the aggregate network traffic and compare the results with existing related work. Simulation results show that the proposed algorithm makes better use of the available bandwidth, achieving superior performance in comparison to similar works.

The Internet's excellent scalability and robustness result in part from the end-to-end nature of Internet congestion control. End-to-end congestion control algorithms alone, however, are unable to prevent the congestion collapse and unfairness created by applications that are unresponsive to network congestion. To address these maladies, we propose and investigate a novel congestion-avoidance mechanism called network border patrol (NBP). NBP entails the exchange of feedback between routers at the borders of a network in order to detect and restrict unresponsive traffic flows before they enter the network, thereby preventing congestion within the network. Moreover, NBP is complemented with the proposed enhanced core-stateless fair queueing (ECSFQ) mechanism, which provides fair bandwidth allocations to competing flows. Both NBP and ECSFQ are compliant with the Internet philosophy of pushing complexity toward the edges of the network whenever possible. Simulation results show that NBP effectively eliminates congestion collapse and that, when combined with ECSFQ, approximately max-min fair bandwidth allocations can be achieved for competing flows.

The end-to-end nature of Internet congestion control is an important factor in its scalability and robustness. However, end-to-end congestion control algorithms alone are incapable of preventing the congestion collapse and unfair bandwidth allocations created by applications which are unresponsive to network congestion. In this paper, we propose and investigate a new congestion avoidance mechanism called Network Border Patrol (NBP). NBP relies on the exchange of feedback between routers at the borders of a network in order to detect and restrict unresponsive traffic flows before they enter the network. The NBP mechanism is compliant with the Internet philosophy of pushing complexity toward the edges of the network whenever possible. Simulation results show that NBP effectively eliminates congestion collapse, and that, when combined with fair queueing, NBP achieves approximately max-min fair bandwidth allocations for competing network flows.

Layered transmission of data is often recommended as a solution to the problem of varying bandwidth constraints in multicast video applications. Multilayered encoding, however, is not sufficient to provide high video quality and high network utilization, since bandwidth constraints frequently change over time. Adaptive techniques capable of adjusting the rates of video layers are required to maximize video quality and network utilization. We define a class of algorithms known as source-adaptive multilayered multicast (SAMM) algorithms. In SAMM algorithms, the source uses congestion feedback to adjust the number of generated layers and the bit rate of each layer. We contrast two specific SAMM algorithms: an end-to-end algorithm, in which only end systems monitor available bandwidth and report the amount of available bandwidth to the source, and a network-based algorithm, in which intermediate nodes also monitor and report available bandwidth. Using simulations that incorporate multilayered video codecs, we demonstrate that SAMM algorithms can exhibit better scalability and responsiveness to congestion than algorithms that are not source-adaptive. We also study the performance trade-offs between end-to-end and network-based SAMM algorithms.

Network architectures that can efficiently transport high quality, multicast video are rapidly becoming a basic requirement of emerging multimedia applications. The main problem complicating multicast video transport is variation in network bandwidth constraints. An attractive solution to this problem is to use an adaptive, multi-layered video encoding mechanism. We consider two such mechanisms for the support of video multicast; one is a rate-based mechanism that relies on explicit rate congestion feedback from the network, and the other is a credit-based mechanism that relies on hop-by-hop congestion feedback. The responsiveness, bandwidth utilization, scalability and fairness of the two mechanisms are evaluated through simulations. Results suggest that while the two mechanisms exhibit performance trade-offs, both are capable of providing a high quality video service in the presence of varying bandwidth constraints.

This paper presents and analyses a high performance manufacturing communication system. It consists in the standard TOP profile implemented in single processor computer connected to a LAN. High throughput is achieved by an efficient implementation architecture based on specific layer interfaces and data structures, specialized mechanisms of memory management, timer management and task scheduling. Performance measurement results show a throughput efficiency that attains 6 Mbit/s for a remote communication and 42 Mbit/s for loopback configuration. The most important bottlenecks are analysed and consist in the transport checksum, transport acknowledgment step frequency, LLC memory copy, memory management and task scheduling.>