LoRaWAN has become a foundational technology in the Internet of Things (IoT) landscape due to its long-range communication and energy efficiency. However, its default Adaptive Data Rate (ADR) mechanism struggles to adapt to dynamic environments and dense network deployments, where co-channel interference and the coupling between transmission parameters limit its ability to ensure reliable and energy-efficient communication. To address these challenges, this paper proposes MARLTC, an ADR mechanism based on Multi-Agent Rein-forcement Learning (MARL) that jointly optimizes spreading factor and transmission power using realistic observable metrics, including recent transmission history, observed signal-to-noise ratios, and distribution of spreading factors in the network. The transmission configuration problem is modeled as a cooperative Markov Game and solved using the Centralized Training and Decentralized Execution (CTDE) paradigm, where pre-trained policies are deployed at end devices to infer suitable transmission parameters with reduced convergence time. The results using a realistic LoRaWAN simulator show that MARLTC achieves up to 67.9% faster convergence, 62.1% higher energy efficiency, and a 5.0% better packet delivery ratio compared to state-of-the-art approaches, highlighting its scalability and responsiveness in dense deployments. The practical feasibility of MARLTC is further validated using physical LoRaWAN hardware, proving that the resulting policies meet the memory and timing constraints of resource-constrained IoT devices.

Air pollution poses a major environmental challenge, raising concerns about human health in urban environments. It leads to diseases such as asthma, exacerbates pulmonary conditions, and creates murky skies, lowering inhabitants’ quality of life. To quantify air pollution, cost-effective IoT (Internet of Things) devices are being deployed in cities, making air quality monitoring available for a wide range of end-users, including public administrations. However, full urban coverage is unfeasible, and awareness of the carbon footprint of IoT deployments is increasing. Therefore, new techniques are needed to maximize the value of IoT networks with reduced infrastructure. To address these challenges, this paper presents an air pollution analytical forecasting solution based on deep-learning/machine-learning techniques to estimate air quality in locations without deployed devices. Different combinations of well-known deep-learning models are compared with machine-learning techniques to determine the best approach for monitoring polluting gases and airborne particles based on well-defined evaluation metrics. Additionally, two new deep-learning techniques, Multipath-CNN-LSTM (M-CNN-LSTM) and Multipath-CNN-BiLSTM (M-CNN-BiLSTM), are proposed to conduct a more exhaustive comparison. Combinations of LSTM (Long Short-Term Memory) techniques give the best results, with different models working best for each pollutant. Specifically, LSTM was optimal for O 3 , and combinations of CNN (Convolutional Neural Networks) and BiLSTM (Bidirectional LSTM) worked best for NO 2 . GRU (Gated Recurrent Unit) was more efficient for PM 2.5 , and BiLSTM performed best for PM 10 . This demonstrates that the best strategy to accurately predict the time evolution of each pollutant’s behavior depends on the selection of the most suitable machine-learning or deep-learning technique. • M-CNN-LSTM and M-CNN-BiLSTM models are proposed for air pollution forecasting. • Forecasting is performed in locations without deployed sensor devices. • LSTM is optimal for O 3 , M-CNN-BiLSTM for NO 2 , GRU for PM 2 . 5 , and BiLSTM for PM 10 .

The rapid expansion of the Internet of Things (IoT) landscape, notably in smart cities, smart metering, environmental monitoring, and smart agriculture, highlights the critical need for seamless and efficient device roaming within Long Range Wide Area Network (LoRaWAN) infrastructures. Although LoRaWAN shows great potential, its deployment faces significant challenges, especially under the constraints of the version 1.0 specifications, to enable efficient device mobility. This study introduces a comprehensive approach to enhance LoRaWAN-supported mobility, using three key advancements: the decoupling of Gateways (GWs) from the core network infrastructures to facilitate flexible deployments, the adoption of an adaptive GW-to-network connection protocol responsive to real-time traffic demands, and the enhancement of GW interoperability to provide dynamic and efficient network configurations. A notable innovation of this research is developing a mechanism that enables packet forwarding through an unidentified GW, eliminating the need for pre-established network agreements. The empirical evaluations of the article detail the effectiveness of the architecture in IoT applications, showcasing significant improvements in LoRaWAN’s roaming capabilities and reporting average latencies of up to 0.39 s in experimental tests. Extensive simulations with up to 100 roaming devices and 100 stationary devices further confirmed scalability, keeping the average roaming-to-stationary latency gap below 0.16 s and the worst-case end-to-end delay below 1.2 s even in highly congested scenarios. This contribution addresses pivotal challenges within the current LoRaWAN networks and sets the background for future advancements in IoT network technologies.

Even though the initial design of LoRa did not specifically aim at provisioning mobile devices, onboard IoT devices are paving the way for safer, more efficient, and ultimately, autonomous transportation. The LoRaWAN Adaptive Data Rate (ADR) mechanism enables the minimization of energy consumption and the optimization of data rates and airtime values. However, it has been demonstrated to have limited adaptability in mobile devices. In this paper, we propose a proactive ADR mechanism for LoRaWAN based on trajectory estimation and well-known machine-learning methods used to forecast the signal-to-noise ratio (SNR). This enables the efficient selection of the most suitable transmission parameters beforehand. We compare our approach with existing mechanisms in a realistic simulator and several urban environments. Results prove that our method achieves a proper balance between minimizing energy consumption and satisfying performance constraints over time even in highly dynamic and unpredictable environments.

The development of Low-Power Wide-Area Networks (LPWAN) has significantly boosted the uptake of Internet of Things technologies, fostering their adoption in such domains as Smart Cities and Industry 4.0. In the context of LPWANs, LoRa is one of the most promising developments, experiencing massive growth in recent years. This situation has led to the steadily growing trend of redundant deployments across locations, or scenarios, where it would be more natural to be able to leverage (e.g., rent) LoRa infrastructure belonging to a third party. Key to reversing this unsustainable trend is roaming approaches. Although the LoRa specifications define mechanisms for roaming, gaps and challenges make roaming difficult to deploy and operate in real-world scenarios. This paper analyzes these concerns and proposes a novel architecture compliant with the LoRa specification to design and accommodate roaming services in a consistent, efficient, and scalable way.

Flow-guided electromagnetic nanonetworks will enable innovative medical applications for monitoring, information gathering, and data transmission inside the human body. These nanonetworks will have to operate under extreme computational and powering-related constraints, and in very hostile environments inside human vascular systems. Under these circumstances, successful transmissions between in-body nanonodes and an on-body nanorouter rarely occur, thus requiring new approaches to improve the network throughput in this scenario. Along this view, in classical flow-guided nanonetworks the nanonodes are envisioned to transmit packets if they have enough energy for the transmission, regardless of their vicinity to the nanorouter. In this paper, we propose a nanorouter awareness model that can provide significant throughput gains compared to the baseline based on blind transmissions, facilitating the roll-out of nanocommunication-supported medical applications.

In this paper, we propose a flow-guided nano-network deployed inside of a human vascular system. The network consists of bio-sensors reporting medical events, small nano-nodes working as information carriers, and nano-routers communicating with external systems. In order to evaluate the performance and feasibility, a preliminary analytical model for this type of flow-guided nano-network is derived and validated through simulations. Results reveal that the network can meet medical requirements in terms of reported events per minute with a feasible number of nano-nodes.

Implicit Error Correction (IEC) is a near Video-on-Demand (nVoD) scheme that trades bandwidth utilization for initial playback delay to potentially support an infinite number of users. Additionally, it provides error protection without any further bandwidth increase by exploiting the implicit redundancy of nVoD protocols, using linear combinations of the segments transmitted in a given time slot. However, IEC packet loss protection is weaker at the beginning of the playback due to the lack of implicit redundancy and lower decoding efficiency, resulting in worse subjective playback quality. In tackling this issue, this paper contributes with an extension of the original nVoD architecture, enhancing its performance by adding a new element namely, subchannels. These subdivisions of the original channels do not provide further packet loss protection but significantly improve the decoding efficiency, which in turn increases playback quality, especially at the beginning. Even for very high packet loss probabilities, subchannels are designed to obtain higher decoding efficiency which results in greater packet loss protection than that provided by IEC. The proposed scheme is especially useful in wireless cooperative networks using techniques such as network coding, as content transmissions can be split into different subchannels in order to maximize network efficiency.

By empowering the Internet of Things (IoT) with nanoscale communications, thousands of small devices, called nano-nodes, are enabled to monitor complex environments in a nonintrusive way, giving rise to the Internet of Nano-Things (IoNT) paradigm. It is in one of these very complex and critical environments, the human cardiovascular system, where IoNT might stand out. However, the supervision of human health poses significant challenges: first, to reduce costs and allow in vivo monitoring nano-sensor networks, the number of deployed nano-routers must be limited, which could cause nano-nodes to undergo long out-of-coverage periods. Lastly, nano-nodes rely on harvested energy from the medium, which severely reduces the number of potential transmissions. To overcome these two problems, smart policies that direct devices on how to proceed with sensed events are crucial. In this line, we propose a generic Markov decision process (MDP) model which can be exploited to derive optimal transmission policies that are easily employed by nano-nodes. These policies maximize nano-node throughput and cope with the energy and coverage problems. We have also run a set of simulations to validate our proposal and to compare it to other alternative policies. Results reveal that: 1) our policy systematically outperforms the rest of policies by a large margin and 2) precision in placing nano-routers and average distance between them strongly affect the nano-network performance. The Python code for the MDP model and simulations has been programmed to be easily adaptable to researchers' needs, making it easier for future IoNT works to add intelligence to the network.

LoRa is an extremely flexible low-power wide-area technology that enables each IoT node to individually adjust its transmission parameters. Consequently, the average per-node throughput of LoRa-based networks has been mathematically formulated and the optimal network-level configuration derived. For end nodes to update their transmission parameters, this centrally computed global configuration must then be disseminated by LoRa gateways. Unfortunately, the regional limitations imposed on the usage of ISM bands - especially those related to the maximum utilization of the band - pose a potential handicap to this parameter dissemination. To solve this problem, a set of tools from the machine learning field have been used. Precisely, the updating process has been formulated as a reinforcement learning (RL) problem whose solution prescribes optimal disseminating policies. The use of these policies together with the optimal network configuration has been extensively analyzed and compared to other well-established alternatives. Results show an increase of up to 147% in the accumulated per-node throughput when our RL-based approach is employed.

Low-power wide-area network (LPWAN) technologies enable Internet of Things (IoT) devices to efficiently and robustly communicate over long distances, thus making them especially suited for industrial environments. However, the stringent regulations on the usage of certain industrial, scientific, and medical bands in many countries in which LPWAN operate limit the amount of time IoT motes can occupy the shared bands. This is particularly challenging in industrial scenarios, where not being able to report some detected events might result in the failure of critical assets. To alleviate this, and by mathematically modeling LPWAN-based IoT motes, we have derived optimal transmission policies that maximize the number of reported events (prioritized by their importance) while still complying with current regulations. The proposed solution has been customized for two widely known LPWAN technologies: 1) LoRa and 2) Sigfox. Analytical results reveal that our solution is feasible and performs remarkably close to the theoretical limit for a wide range of network activity patterns.

IoT is rapidly expanding to all productive sectors; however, as thousands of devices are envisioned to be deployed, a careful study of the radio spectrum (and its interferences) must be considered to predict and improve the network performance. In this sense, radio-channel characterization is essential; in particular, path-loss characterization allows to mathematically predict the propagation behavior and interferences of IoT devices with precision. In this paper, we show that by means of a set of mathematical corrections and measuring procedures, we can soundly employ the received signal strength indicator (RSSI), available in most IoT motes, to derive accurate path-loss models of industrial infrastructures. Experimental results reveal that the proposed scheme substantially improves the characterization accuracy of a real smart grid environment. This, in turn, is proven to have a measurable positive impact on the planning stage of an IoT network, whose life-of-time and cost analysis can be better anticipated.

The smart grid (SG) represents the present and the future of electric power grids. Wireless networks (WNs) are a key technology for this updating process, empowering electric networks to be easily managed in a flexible and cost-effective way. However, as with any wireless technology and especially in a harsh multipath environment such as the SG, reckoning with an extensive channel characterization is crucial. This paper presents an exhaustive characterization of two representative scenarios, both in the transport and distribution segment of an SG: a 400-kV outdoor substation and a main power room. The 2.4-GHz ISM band-in which most wireless communication technologies applied to SG operate-is examined in depth to characterize the radio-propagation phenomena. Large and small-scale fading, RMS delay, coherence bandwidth, and electromagnetic interferences are studied under different line-of-sight, polarizations, and frequency conditions to derive empirical models allowing to estimate the aforementioned parameters in other SGs of a similar nature. Finally, to further evaluate and compare our channel characterization, a WN was simulated in a substation to examine the channel modeling impact on its suitable design and operation.

In Opportunistic Spectrum Access (OSA), conventional secondary users' (SU) radios can not transmit and detect primary user (PU) activity simultaneously, and therefore SU and PU transmissions may overlap, causing harmful interference at PU receivers. The extended approach of periodically interrupting SU transmission to perform spectrum sensing mitigates but does not completely solve the problem. Our proposal consists of a collision detection mechanism simultaneous to reception at the SU receiver (Background Detection), which aborts the ongoing secondary transmission if a collision is detected. While some previous works assumed the existence of a collision detection scheme, little work has been done in proposing a specific one for OSA systems, capable of operating during SU reception. Our proposal exploits local characterization of the PU activity, power levels and packet errors at each time slot. Based on these data, we develop a Maximum A Posteriori (MAP) estimator as the basis for the collision detection system. We describe the general methodology to build this estimator, and study the system's robustness against parameter misestimations. The proposed scheme can be incorporated to existing OSA protocols. Our results show a notable throughput improvement for the SUs while assuring a lower collision probability with PU transmissions in most cases, even under severe estimation inaccuracies.

Wireless Mesh Sensor Networks (WMSNs) have recently received a great deal of attention in the scientific and developers communities due to the significant advances of this technology in the wireless communication field. The main reason was that competing WMSN approaches that emerged in the last few years provide mesh capabilities (e.g., robustness, scalability, multi-hop mesh routing, or energy efficiency, among others) to conventional WSN-based applications, encouraging researchers and end users to adopt new perspectives and solutions. Unfortunately, each one of these approaches lacks some (or many) of the aforementioned mesh capabilities, not assuring, a priori, the feasibility and, especially, the long-term stability of WMSN applications. The IEEE 802.15.5 standard and, in particular, its Asynchronous Energy Saving (ASES) mode was conceived to fill this gap since it integrates, in a single solution, most of these capabilities, guaranteeing, among other benefits, a long network lifetime. However, the ASES mode has no built-in mechanisms to mitigate the negative effects of hidden terminals, which sharply degrades the network performance. This fact leads us to conclude that any current WMSN approach is non-exempt of some problem, which prevents the definitive boost of this technology in the consumer market. Under these circumstances, our contribution to the WMSN field in this paper is a twofold proposal addressed to alleviating the hidden terminal problems in a scenario running under the most relevant design premises of ASES mode. Therefore, we first formulate a multi-objective optimization and then solve it by using Goal Programming. Both mathematical techniques are applied to obtain the best solution that simultaneously minimizes the aggregate message collision time due to hidden terminals and maximizes the network lifetime. Secondly, we propose the design of a MULti-channel TIme-scheduled algorithm for the HIdden Terminal problem avoidance (MULTI-HIT) which appropriately exploits the available bandwidth and accomplishes a straightforward coordination between any sender–receiver pair. Finally, the analysis and simulation experiments are presented and their results carefully discussed, demonstrating the effectiveness of both proposals in the WMSN arena.

We consider a scenario in which a licensed wireless operator or primary network (PN) coexists with an ad-hoc, cognitive, secondary network. To minimize harmful interference on the primary users (PUs), secondary users (SUs) sense the PU activity on the licensed spectrum band before transmitting in spectrum opportunities. We study a bandwidth reservation (BR) scheme by which the PN keeps a set of adjacent channels free of PU transmissions. These reserved channels only accommodate PU traffic when all the non-reserved channels are used, and the SUs only occupy available channels within the reserved spectrum. Intuitively, this strategy reduces collision probability and simplifies the design of opportunistic spectrum access (OSA) mechanisms. However, from the point of view of the PN, BR entails a tradeoff between the benefits of an improved coexistence with SUs, and the capacity reduction associated to having fewer options for PU channel allocation. The main objective of this paper is to determine when BR improves the overall PN performance under SU activity. The SUs are characterized by a hardware limited radio, imperfect spectrum sensing, bayesian estimation of PU activity and multichannel access. Because PU capacity is the central issue, we assume a PN capable of exploiting all the available bandwidth at every moment. By means of a Markov-reward model, we compute the expected PU capacity with and without BR, considering propagation effects, interference and random locations. The results show that, in a non-congested PN with SU activity, the interference reduction capability of BR increases the overall capacity of the PN compared to not using BR.

MANETs are experiencing unstoppable growth due to their decentralized topology and their easy and low-cost deployment. The dynamic nature of MANETs entails the use of appropriate routing protocols to obtain good performance in the services supported by the network; even more if these services present tough temporal requirements, such as multimedia or VoIP services. One routing protocol to which notable research effort has been devoted is the BATMAN protocol, which proposes an interesting paradigm avoiding the explicit interchange of routing information among nodes. In this paper, we focus on evaluating the performance of BATMAN supporting VoIP traffic on low power-consumption nodes, from a Quality of Experience (QoE) point of view. Specifically, we evaluate the impact on BATMAN performance of 1) the PHY layer, by employing a fading characterization of the transmission channel; 2) the number and density of ad-hoc nodes; and 3) node mobility. All the results obtained for BATMAN are compared with those attained by using the widely used OLSR routing protocol. From the results, we conclude that neither BATMAN nor OLSR in their respective current implementations are suitable enough for VoIP traffic support in MANETs composed of energy-saving nodes.

Computer simulation is the preferred approach when investigating Vehicular Ad-hoc Networks (VANET). Dur- ing the last years different platforms have emerged, regarding the evaluation of next-generation autonomous vehicular mobility and car-to-car wireless connectivity. NCTUns (now Estinet) is a relevant networking plat- form that provides support for IEEE 802.11p-based connectivity between vehicles. This paper describes the implementation of an inter-module communications' scheme in NCTUns designed to allow reciprocal mes- sage transmission and processing between a mobility and a messaging agent in vehicles supporting Coopera- tive chain Collision Avoidance(CcCA) for improving safety even under rear-end collision risky circumstances. Contributions hold in the bidirectional inter-module channel that features the management of mobility in these environments according to the communication's protocol that implements the CcCA application, and vicev- ersa. As an additional characteristic of the implementation, a Nakagami-m channel model is implemented to recreate intervehicular communications more realistically.

In dense radio frequency identification (RFID) systems, reader-to-reader interference may appear among readers operating nearby. When the anticollision algorithm is Frame Slotted Aloha (FSA), a usual solution is to multiplex the frames of interfering readers by means of a central controller. The scenario studied considers RFID tags attached to objects carried by conveyor belts or vehicles so that each tag crosses, in constant motion, one reader's interrogation region. The problem addressed consists of determining the length of the multiplexed FSA frames such that each object is successfully identified, with high probability, before exiting its interrogation region. In this paper, we develop a mathematical model, based on dynamic system theory, allowing us to obtain the configurations attaining the desired reliability objective, to show that some configurations present multiple equilibrium points and should be avoided, and to define the operating boundaries of the system. The model can also incorporate fading and capture effects.

Traffic safety is a key aspect in new-generation intelligent transportation systems. Among other areas, an active field of research is cooperative collision avoidance, where vehicles cooperatively calculate trajectories under tight time constraints to avoid colliding under specific road-traffic domains (overtaking, intersections, etc.). In this paper, we particularly analyze the problem of collision avoidance in scenarios in which high-speed vehicles need to generate evasive maneuvers within very short time intervals to avoid or at least mitigate a hypothetical (multiple) collision. We pose this as a multiobjective optimization problem and simplify it by considering only lateral motion for the optimization process, thus having to solve a 1-D trajectory generation problem. The routes of vehicles are optimized according to a weighted aggregation functional that: 1) maximizes the lateral distances between vehicle-vehicle and vehicle-obstacle pairs at the time of overcoming the obstacles; 2) minimizes the lateral speeds at the end of the path; and 3) minimizes the instantaneous lateral acceleration (inertia) along the maneuver. In addition, we compute trajectories by following an optimization strategy that divides the problem into a set of independent subproblems, which are optimized in parallel by using a gradient-descent-based methodology. From this set of solutions, the most suitable option, according to our selected criteria, is chosen. Results show the utility of our approach and its flexibility to compute evasive trajectories adapted to different requirements. Additionally, a simulation of the mechanical response of the vehicles during the evasive maneuvers is conducted.

Nowadays, research on Vehicular Technology aims at automating every single mechanical element of vehicles, in order to increase passengers' safety, reduce human driving intervention and provide entertainment services on board. Automatic trajectory tracing for vehicles under specially risky circumstances is a field of research which is currently gaining a lot of attention. In this paper we show some results on how to develop useful policies to execute maneuvers by a vehicle at high speeds with the mathematical optimization of some already established mobility conditions for the car. Different strategies are presented as well as a discussion on how communications can be used to implement these schemes.

Improvement of traffic safety by cooperative vehicular applications is one of the most promising benefits of vehicular ad hoc networks (VANETs). However, to properly develop such applications, the influence of different driving parameters on the event of vehicle collision must be assessed at an early design stage. In this paper, we derive a stochastic model for the number of accidents in a platoon of vehicles equipped with a warning collision notification system, which is able to inform all the vehicles about an emergency event. In fact, the assumption of communications being used is key to simplify the derivation of a stochastic model. The model enables the computation of the average number of collisions that occur in the platoon, the probabilities of the different ways in which the collisions may take place, as well as other statistics of interest. Although an exponential distribution has been used for the traffic density, it is also valid for different probability distributions for traffic densities, as well as for other significant parameters of the model. Moreover, the actual communication system employed is independent of the model since it is abstracted by a message delay variable, which allows it to be used to evaluate different communication technologies. We validate the proposed model with Monte Carlo simulations. With this model, one can quickly evaluate numerically the influence of different model parameters (vehicle density, velocities, decelerations, and delays) on the collision process and draw conclusions that shed relevant guidelines for the design of vehicular communication systems, as well as chain collision avoidance applications. Illustrative examples of application are provided, although a systematic characterization and evaluation of different scenarios is left as future work.

This paper proposes a scheduling algorithm for non-real-time traffic in Vehicle to Infrastructure (V2I) networks. The scheduler operates at the link layer and uses the contention-free, poll-based access mode of the 802.11e standard. Our proposal exploits two specific features of V2I that are not present in other wireless systems. First, the fact that vehicles are constrained to a predefined area (the road segment under radio coverage) which can be characterized in terms of packet error ratio (PER). Second, that it is possible to know the vehicle speed, either accurately or approximately. These characteristics allow us to model the data transmission process in V2I as a dynamical system. However, the unpredictable arrivals of new vehicles make it difficult to directly apply dynamic programming to obtain the optimum scheduler. We overcome this limitation by developing a tractable formulation of the problem, similar to a classical linear quadratic regulator design problem but with the significant difference that constraints are included. We propose a novel algorithmic solution that can be efficiently computed and can easily incorporate quality of service differentiation. The scheduler is compared to three other feasible schemes, assessing the impact of the system parameters in the performance. Numerical results show that the proposed scheme is more beneficial when the average PER values have notable variations along the covered area.

Relaying mechanisms for Chain Collision Avoidance (CCA) applications in Vehicular Ad-hoc Networks (VANETs) are crucial when one hop transmissions are not enough to reach all of the vehicles in a platoon at risk of accident. Taking into account that CCA-related information must be distributed to as many vehicles as possible in the shortest affordable time, a reasonable way to determine the viability of using such relay policies is by evaluating the delay to spread information to all recipients and the associated occupation of the communications channel. Furthermore, the inherent transition to reach full technology penetration in the market requires to study how the system of vehicles will behave at different stages of deployment and how different relaying mechanisms may affect the general functionality of the system and what is the influence of background data traffic which can obviously worsen the successful delivery rate (SDR) of warning notification messages.

In cooperative automatic repeat request (C-ARQ) protocols, one or more nodes can act as relays, collaborating in the frame retransmission process between a sender and a destination node. In the framework of a broadband mobile access network, we consider a relay enhanced cell where the sender represents the base station, and an undefined number of relays can cooperate with a single user (destination). In this paper we present a Markov model complemented with a reward model to analyze the throughput performance and the efficiency in the bandwidth utilization at the base station, highlighting a clear tradeoff between them. Both performance metrics are balanced by means of a multi-objective optimization algorithm resulting in a retransmission strategy for the access node that notably improves the bandwidth efficiency while maintaining the throughput very close to its maximum. The benefits of the proposed approach are evaluated in two scenarios. In the first one, the relays are part of the network infrastructure. In the second one, the relays are cooperative users.

Wireless personal area networks (WPAN) are wireless sensor networks (WSN) designed for allowing a low-cost, low-power and short-range wireless communication. The IEEE 802.15.4 is the WPAN standard which satisfies these features and facilitates diverse self-configuring operation processes for adapting to different environments and applications. One of these processes is responsible for resolving the loss of coverage of a device, namely an orphan device. It has associated a long procedure when the device has to return to the wireless network, incurring in a high delay and energy consumption. This behavior implies that the Orphan device does not perform its assigned tasks during this delay increasing simultaneously its power consumption. We have designed a new algorithm, called optimized orphan algorithm (OOA), which offers a significant better delay and energy consumption performance. The OOA algorithm is implemented on real devices and evaluated under different scenarios. In this paper, the results obtained are presented and discussed as well.

IEEE 802.15.4 is a wireless technology aimed at the transmission of information at low rates and short distances. Therefore, the expected traffic carried by these networks is one whose transmission rates are low, i.e. information captured by sensors. The extension of this technology to higher data rates is a challenge that gives us the opportunity to support additional services. This paper deals with this issue and evaluates the feasibility of transmitting MPEG-4 video information by computer simulation. Another subject to take into consideration is the computation of the human quality perception when the video streaming is received. To achieve these objectives, the GTS slots of the IEEE 802.15.4 MAC are implemented in the currently available simulation tools. The results obtained are also presented and discussed.

Software technologies to implement distributed multimedia services currently require intensive network and computing resources. In many environments, the design of these services on top of a general-purpose middleware layer is the usual choice. CORBA, Java RMI and .NET are major representatives of this approach. This paper describes and compares the three aforementioned middleware alternatives by evaluating the performance of the implementation of A/V Streaming services on top. From this comparison, several key points and implementation details are highlighted.

The deployment of optical packet switching (OPS) in dense wavelength division multiplexing (DWDM) backbone networks is perceived as a medium term promising alternative. Scalability restrictions imply that conventional switching architectures are unfeasible in this large-scale scenario. In a previous paper, the wavelength-distributed knockout architecture was proposed as a cost-effective scaling strategy for OPS switching fabrics. In this paper, this growable architecture is applied to OPS switching fabrics able to emulate output buffering. We also propose an scheduling algorithm which provides optimum performance if knockout packet losses are made negligible. The mathematical analysis to evaluate the knockout packet loss probability of this architecture is obtained, under uniform and non-uniform traffic patterns. To complement the switch dimensioning process, an upper bound assuring 0-knockout packet losses is compared with the exact analytical results.

In this paper, we analyze a multicast protocol called MUST (multicast synchronous transfer), which offers multicast file transfer service to the application layer, in an intracampus environment (several interconnected LAN networks). Synchronicity is one of its more remarkable attributes since MUST guarantees that all clients are receiving the information at the same time. For an efficient bandwidth utilization, MUST transmits IP packets by using multicast addressing. Also, it achieves a notable acknowledgement packets reduction by an appropriate mechanism. Flow control and error recovery algorithms are also developed to satisfy features such as reliability, high throughput and low delay. To evaluate the protocol, we first implemented an application based on it that we extensively tested in a lab with up to ten computers in an intracampus environment. Then, we also developed a mathematical model validating analytically the most important protocol parameters. The methodology used to study this multicast protocol is in fact another contribution and can be extrapolated easily to other protocols.

In this paper, we study a multicast transport protocol called MUST (multicast synchronous transfer), which offers multicast synchronous file transfer service to the application layer, in an intra-campus environment. For an efficient bandwidth utilization, MUST transmits IP packets by using multicast addressing. Also, it achieves a notable acknowledgement packets reduction by an appropriate mechanism. Flow control and error recovery algorithms are also developed to satisfy features such as reliability, high throughput and low delay. We present in this work some test results of the protocol transfer delay, some flow control features and the UDP buffer overflow probability (this last parameter is also verified by simulation). We also compare the experimental and simulation results with a mathematical model, validating analytically the most important protocol parameters.

The counter-based modified (CBM) traffic conditioner was presented in a previous work as a feasible election for the assured service implementation with Diffserv. In this work, we evaluate the end-to-end performance of TCP Reno sources with the CBM traffic conditioner in topologies with one and three networks nodes under miscellaneous characteristics, i.e. variable contracted target rates and roundtrip times. In addition and for the same scenarios, the robustness of the couple CBM-RIO is tested when assured service and best-effort sources coexist and compete target bandwidths and even allocation of spare bandwidth across different flows can be provided as shown in simulation results.

Commercial applications of optical packet switching to backbone WDM networks are still far from reality due to hardware costs. The two envisaged alternatives for network control and operation of this type of networks is scattered wavelength path (SCWP) and shared wavelength path (SHWP). The advantages and drawbacks of both approaches involve many different issues. In this paper, the impact of SCWP and SHWP switching modes on performance and hardware costs is discussed and evaluated for three different prominent OPS switch fabric designs: KEOPS switch, space switch, and output-buffered wavelength-routed switch. To achieve it, we conduct a necessary set of modifications for these architectures, which were not originally conceived for SCWP/SHWP. This normalization process is unavoidable to provide a true comparison among the switch fabric designs, and to advance to a global comparison between SCWP and SHWP operation modes, that under knowledge of the authors do not exist yet.

Because of the dramatic growth of the Internet and the requirement of quality of service (QoS) guarantees for new and future applications it is essential that the Internet ensures end-to-end QoS. To provide this level of QoS, many protocols have evolved in the last few years, and some end-to-end QoS architectures have been proposed to mix all of these protocols appropriately. Also, it is necessary to classify applications by QoS requirements to understand how they may reserve resources from the network. In this paper, we briefly review the existing end-to-end QoS protocols and an end-to-end QoS architecture that combines all of them. In addition, we classify Internet data flows by their QoS requirements. We focus our interest on the study of semi-elastic flows and the minimization of their transmission cost. First, we present a client-server system to transmit these flows while reducing the cost. Also, we analyze the buffer management required at the client. Finally, we implement the system in the Network Simulator 2 to demonstrate that our analytical study can be used in a real system in an efficient manner to minimize the cost.

In a wide area network (WAN) established infrastructure, one of the main problems ATM network planners and users face, when greater than T1/E1 bandwidth is required, is the high cost associated to T3/E3 links. The technology to cover the gap between T1/E1 and T3/E3 bandwidth at reasonable cost is known as inverse multiplexing for ATM (IMA). IMA allows multiple T1/E1 lines to be aggregated to support the transparent transmission of ATM cells over one single virtual trunk. In this paper, the fundamentals and major applications of IMA technology are described. Also, the behavior of IMA multiplexers is carefully analyzed and a method to dimension them proposed. For that purpose an IMA simulation tool has been developed, which permits the study of individual devices and the evaluation of the end-to-end performance of a logical trunk under several ATM input traffic patterns. The analytical study is based on the comparison with a M/D/C/(N+C) queue under Poisson input traffic.