Compelling features such as low power consumption and low complexity make LoRaWAN one of the most promising technologies to provide long-range connectivity to resource-constrained devices. However, LoRaWAN suffers from limited scalability since it uses an Aloha-based protocol for accessing the channel that causes a huge amount of frame collisions when the number of devices (or the network load) is high. This paper presents LFS-CSMA, a new medium access control mechanism that enhances the scalability of LoRaWAN networks by just combining the well-known slotted Aloha and CSMA schemes in a novel manner. With LFS-CSMA, longer frames are transmitted earlier within a given timeslot. Thus, devices with short frames to be transmitted can check the channel availability before sending them and avoid collisions if they detect an ongoing transmission. Performance results show that LFS-CSMA causes far less collisions than traditional MAC mechanisms, thus improving the scalability of LoRaWAN networks significantly.

The IEEE 802.3bj standard defines two potential low power operating modes for high speed energy efficient ethernet (EEE) physical interfaces working at 40 and 100 Gb/s: a not-so-efficient low power mode that requires very short transition times to restore normal operation (Fast-Wake) and a highly efficient low power mode with longer transition times (Deep-Sleep). In this paper, we present a new frame coalescing mechanism that dynamically adjusts the coalescing queue threshold in order to minimize the energy consumption of dual-mode EEE interfaces and maintains, at the same time, the average frame delay close to a target value. The proposed mechanism has been validated through simulation under different types of traffic (Poisson, self-similar, and real Internet traffic). In addition, we show that, with the current transition times and efficiency profiles of the standardized low power modes, our proposal renders the Fast-Wake mode unnecessary in most practical scenarios.

The widespread use of computing and communications technologies has enabled the popularity of social networks oriented to learn. In this work, we study the nature and strength of associations between students using an online social network embedded in a learning management system. With datasets from two offerings of the same course, we mined the sequences of questions and answers posted by the students to identify structural properties of the social graph, patterns of collaboration among students and factors influencing the final achievements. The results show some hints to pursue and investigate deep user analytics in online social learning systems, e.g., to build accurate prediction models for the success of effectiveness of the learning tasks based on the patterns of students' participation in the platform.

It is commonly accepted that contemporary cohorts of students witness and experience the benefits of information technologies in their learning processes. The so-called “digital natives” acquire, as a consequence of their early exposure to these technologies, different patterns of work, distinct attention conducts, new learning preferences and, generally, better skills for learning and working within rich online social contexts. So, it seems reasonable that the traditional education systems evolve, and shape their practice to leverage those new patterns. Though online social networks (OSNs) stand as a powerful tool to extend existing online learning management systems (LMSs) by using them as a gateway to OSNs, LMSs do not exploit fully the advantages of an active social environment for reinforcing the learning experience. We report in this paper the design, development and use of a software platform which enlarges and adapts the basic features of an OSN in order to be useful for very general learning environments. The software allows the creation, assessment and reporting of a range of collaborative activities based on social interactions among the students, and offers a reward mechanism by means of ranking and reputation. We argue that this approach is helpful in increasing the students' motivation, besides improving the learning experience and performance. The software has been tested in an undergraduate course about computer networks. Different tests confirm that the impact on learning success is statistically significant and positive.

The discontinuous reception (DRX) mechanism is commonly employed in current LTE networks to improve energy efficiency of user equipment (UE). DRX allows UEs to monitor the physical downlink control channel (PDCCH) discontinuously when there is no downlink traffic for them, thus reducing their energy consumption. However, DRX power savings are achieved at the expense of some increase in packet delay since downlink traffic transmission must be deferred until the UEs resume listening to the PDCCH. In this paper, we present a promising mechanism that reduces energy consumption of UEs using DRX while simultaneously maintaining average packet delay around a desired target. Furthermore, our proposal is able to achieve significant power savings without either increasing signaling overhead or requiring any changes to deployed wireless protocols.

Social networks are being massively utilized for targeting consumers, as entertainment channels and in personal communications, but also offer an appealing potential as a tool for learning in higher education, largely unexplored yet. This paper describes the design and implementation of a social network platform aimed at integrating informal learning processes (games, questions and answers, group ranking) in the university curricula. We present the design principles, the major software modules and the workflow of our tool, which is based on open-source software.

The IEEE 802.3az standard provides a mechanism to build energy efficient Ethernet interfaces via a low power idle mode that they can enter when there is no data to transmit. Several competing algorithms have appeared that make use of this mode to minimize energy consumption with little disruption to the traffic. Two algorithms stand out among those because of their simplicity and performance: frame transmission and burst transmission. Although these algorithms have been shown to be very efficient in simulated scenarios, there is a lack of general analytical models for their behavior. In fact, to this date, the only analyzed traffic patterns have been variants of Poisson traffic. In this paper we provide a general GI/G/1 model for energy consumption and traffic delay for both algorithms. We then develop specializations of the general model for Poisson and deterministic traffic. Finally, we validate the model with the help of both synthetic traffic and real Internet traffic traces.

In this paper, we research the feasibility of adapting the packet coalescing algorithm, used successfully in IEEE 802.3az Ethernet cards, to upstream EPON channels. Our simulation experiments show that, using this algorithm, great power savings are feasible without requiring any changes to the deployed access network infrastructure nor to protocols.

Contrary to Optical Circuit Switching (OCS), Optical Burst Switching (OBS) is efficient for bursty traffic but also weak in guaranteeing the delivery of real-time traffic. We have proposed an OBS enhancement approach, called Labeled OBS with Home Circuits or LOBS-HC, which provides each source-destination pair with a wavelength sharable home circuit for the real-time traffic, so it can guarantee lossless transmission with a short delay. In previous works, we have shown that LOBS-HC requires less resources and provides a better QoS to the real-time traffic than OCS, since it does statistical multiplexing. Here, we extend the study of LOBS-HC. First, we study a few possible design choices in LOBS-HC. Then we evaluate its performance under not only real-time traffic, but also best-effort traffic. Finally, we analyze the effects of the switching speed and the burst size on the performance.

In this paper, we propose probabilistic splitting of a packet stream at the edge routers as the basic method to provide end-to-end proportional QoS to packet flows carried through an OBS network, in terms of loss probability. We argue that the only requirement that the optical transport infrastructure has to satisfy is the support for two internal burst classes with wide separation between their respective service levels. Under this condition, we show how quantifiable end-to-end per-flow guarantees can be attained without diminishing network resource usage. The scheme is analyzed theoretically and evaluated through numerical simulations, both in regular topologies (ring networks) and in a mesh network. Our results suggest that a layered approach to the problem of end-to-end QoS provisioning can be very effective when a proportional service model is offered, and that the research on sophisticated scheduling algorithms at the optical switches could be too narrow-focused for that purpose.

Network interfaces in most LAN computing devices are usually severely under-utilized, wasting energy while waiting for new packets to arrive. In this paper, we present two algorithms for opportunistically powering down unused network interfaces in order to save some of that wasted energy. We compare our proposals to the best known opportunistic method, and show that they provide much greater power savings inflicting even lower delays to Internet traffic.

With the increasing popularity of multimedia applications, video data represents a large portion of the traffic in modern networks. Consequently, adequate models of video traffic, characterized by a high burstiness and a strong positive correlation, are very important for the performance evaluation of network architectures and protocols. This paper presents a new model for traffic with persistent correlations based on the M/G/infin process. We use a new discrete distribution for the service time of the M/G/infin queueing system, flexible enough to give rise to a wide range of correlation structures of the resulting M/G/infin process in a parsimonious way. The corresponding simulation model is easy to initialize in steady state. Moreover, as the distribution has subexponential decay, we can apply a highly efficient and flexible generator of synthetic traces of the M/G/infin process. As an example, we analyze the capabilities of our model for capturing the empirical distribution and correlation structure of VBR MPEG video traffic.

This paper addresses the provision of proportional differentiated services to an arbitrary number of traffic classes in terms of the class packet loss probability measured between the ingress node and the egress node of an OBS network. Our solution relies on a key idea: OBS networks consist of bufferless nodes and can therefore be regarded as a whole like a one-hop bufferless subnetwork characterized by a collection of loss probabilities computable with simple, approximate circuit switching models. Consequently, we believe it is possible to attain packet loss proportionality merely using a simple stochastic algorithm to assemble two classes of bursts, provided there exists some form of internal relative differentiation such that one of the burst classes has a much lower loss probability than the other. In order to evaluate the algorithm accuracy in attaining the proportionality, we present an analytical study of two idealized scenarios (a single link and a multi-node symmetrical network), including the effect caused by the flow dynamics of the traffic received at the ingress nodes. Our results show that, despite its simplicity, this approach is able to provide the desired proportionality over a wide range of operating conditions.

We propose a new hybrid congestion control protocol for multimedia streaming. While dominant proposals in the field have generally dealt with either pure single-rate or multiple-rate proposals, these either lack the ability to adapt to heterogeneous receivers or are too complex to be fully understood and safely deployed. Recent advances have suggested the use of hybrid approaches, but so far these approaches fail to take into account the real capabilities of the receivers. Our proposal works by sampling the allowed transmission rate of the set of receivers and adjusting the minimum transmission rate of each multicast group according to these data. Then a single-rate congestion control protocol guarantees in each group the TCP-fairness of the approach.

One of the more challenging research issues in the context of assured forwarding (AF) is the fair distribution of bandwidth among aggregates sharing the same AF class. Several studies have shown that the number of microflows in aggregates, the round trip time, the mean packet size and the TCP/UDP interaction are the key factors in the throughput obtained by the competing aggregates. Dynamic RIO (DRIO) is an interesting RIO technique suggested to improve assurances among heterogeneous flows in AF-based services. In this paper, we propose applying DRIO to aggregated traffic instead of the individual flows. Working at the aggregate level not only makes DRIO more appropriate to be used in AF networks, but also improves scalability substantially. In addition, we also mitigate some unfairness issues found in the original scheme. Several simulation experiments have been conducted to verify that the proposed improvements allow DRIO to fulfill fairness requirements more satisfactorily.

Congestion control of multicast real-time flows in the Internet has different requirements and poses further difficulties than common end-to-end unicast congestion control. In this paper we present a novel congestion control protocol, the layered datagram protocol (LDP), aimed at solving such problems. LDP has been designed to be fair against competing TCP traffic and, at the same time, exhibit smoothness in the instantaneous throughput, making it attractive for real-time multimedia transmission. Furthermore, the open-loop approach makes the protocol highly scalable, as the server load is not affected by the number of clients present in the transmission. Our simulations show that the protocol exhibits the expected TCP fairness while still being highly tunable to smooth the instantaneous throughput.