Juan J. Alcaraz

Multiframe Maximum-Likelihood Tag Estimation for RFID Anticollision Protocols

Automatic identification based on radio frequency identification (RFID) is progressively being introduced into industrial environments, enabling new applications and processes. In the context of communications, RFID rely mostly on Frame Slotted Aloha (FSA) anticollision protocols. Their goal is to reduce the time required to detect all the tags within range (identification time). Using FSA, the maximum identification rate is achieved when the number of contending tags equals the number of contention slots available in the frame. Therefore, the reader must estimate the number of contenders and allocate that number of slots for the next frame. This paper introduces the new MFML-DFSA anticollision protocol. It estimates the number of contenders by means of a maximum-likelihood estimator, which uses the statistical information from several frames (multiframe estimation) to improve the accuracy of the estimate. Based on this expected number of tags, the algorithm determines the best frame length for the next reading frame, taking into account the constraints of the EPCglobal Class-1 Gen-2 standard. The MFML-DFSA algorithm is compared with previous proposals and found to outperform these in terms of (lower) average identification time and computational cost, which makes it suitable for implementation in commercial RFID readers.

Control-based scheduling with QoS support for vehicle to infrastructure communications

This article is focused on data transmission scheduling in V2I communications, where a central station, the roadside beacon, decides how to allocate system resources among the vehicles under coverage. We consider non-safety applications whose commercial appeal is expected to accelerate the deployment of VANETs. In this case the main objective is to deliver as much information as possible during the connection lifetime of the vehicles, which is limited by their speed and the length of the road sections under coverage. In this environment the contention free poll-based access mechanism of the 802.11e standard included in current VANET specifications is especially suitable. The design of a scheduling mechanism is addressed in this article from a control theory point of view with the additional novelty of using an optimal control formulation comprising resource constraints. This design strategy allows QoS differentiation, assuring a fixed amount of bandwidth for each QoS class. The resulting algorithm not only maximizes the amount of data delivered, but also reduces performance differences between users traveling along different roads.

Optimizing TCP and RLC interaction in the UMTS radio access network

TCP, the dominant transport protocol for Internet applications, suffers severe performance degradation due to packet losses when a wireless link is present in the end-to-end path. For this reason, the 3G specification entity, 3GPP, has defined a reliable link layer protocol, RLC, to support packet switched services over UMTS. RLC provides error recovery in the radio access network by means of an ARQ algorithm. Early studies supported the benefit of using a reliable link protocol, while more recent studies outline new problems arising from RLC and TCP interaction and how to overcome them. This article describes the most relevant issues concerning TCP-RLC interaction and evaluates the most practical enhancement approaches, based on optimum parameter configuration at the transport and link layers. We devote special attention to RLC, whose specific configuration decisions are left to operators, and provide specific guidelines for setting its parameters. In addition, we propose two operational changes for enhancing the buffer management strategy, one of the main drawbacks of RLC

Performance of single-relay cooperative ARQ retransmission strategies

In cooperative automatic repeat request (C-ARQ) protocols, the retransmission process between a pair of nodes can be assisted by a relay node. We investigate the performance of C-ARQ algorithms in cellular access networks, where the use of relays is a promising strategy for future evolutions. By means of Markov analysis and simulation we show that the implementation of acknowledgment signals from the relays and the retransmission policy at the base station have a notable impact on the throughput of the system.

On the optimal random deployment of wireless sensor networks in non-homogeneous scenarios

Random scattering of WSNs is needed in many practical cases due to the large scale of the network required or to the inaccessibility of the terrain. However several important features of deployments of this type have been neglected due to their analytical complexity. Node placement must guarantee correct operation: if nodes are too separated many would be isolated and data would not reach the sinks. Besides, if the nodes are too close, the area covered would be small and little information would be retrieved. Moreover, the target area cannot be considered homogeneous since in real-life situations some zones are more important than others. This paper addresses these constraints by proposing and solving an optimization problem which maximizes network sensing coverage. In our model several clusters of nodes are spread over the target area following Gaussian random distributions, and the goal is to decide the optimal launch point and the dispersion for each cluster. This corresponds to real situations where clusters are dropped in an airborne launch in which dispersion is controlled by the release altitude. The problem is solved by considering iterative steps where single cluster deployments are addressed. Several tests validate our approach and indicate that our method outperforms previous approaches, especially in deployments with a low number of nodes, which are more challenging from the optimization perspective.

Statistical Beaconing Congestion Control for Vehicular Networks

Cooperative intervehicular applications rely on the periodic exchange of broadcast single-hop status messages among vehicles, which are called beacons. The aggregated load on a wireless channel due to beacons can prevent the transmission of other types of messages, which is called channel congestion due to beaconing activity. In this paper, we propose a novel statistical approach to transmit power control (TPC) for beaconing congestion control, which is called statistical beaconing congestion control (SBCC). Unlike previous proposals, SBCC uses local information and very limited feedback, and its implementation is simple. Each vehicle locally computes the power needed to comply with a given maximum beacon load as a function of estimated channel parameters, vehicle density, and beaconing rate. A realistic Nakagami- m fading and path-loss propagation model is assumed. We provide a final expression of the algorithm as a linear proportional controller, with two variants, i.e., channel-busy-time-(CBT) based SBCC (SBCC-C) and neighbor-based SBCC (SBCC-N), depending on how the parameters are estimated. Additionally, we derive an expression for the estimated communication range under interference, which approximates the average fraction of packets lost due to hidden-node collisions. Finally, we evaluate the performance degradation caused by differences in local vehicle densities and propose a mechanism, which is called edge correction (EC), to limit it while keeping the safety benefits of an extended range at the edge of a cluster of vehicles. SBCC is validated with a realistic hybrid network-traffic simulator, and results show that it effectively controls beaconing congestion.

Dynamic system model for optimal configuration of mobile RFID systems

In many practical RFID applications tags are attached to items that pass through the readers field moving at a constant speed, following a fixed path. The time-constrained presence of the tags in the identification region introduce the possibility that tags exit the system without being identified (lost tags). Reliability is a practical requirement in most applications, which implies that the portion of lost tags should be kept below a very small threshold. Therefore, we take this fact as the starting point in the design process. We present a mathematical model for RFID systems implementing Frame Slotted Aloha as the collision resolution protocol. Upon this model it is possible to compute the tag loss ratio and therefore to obtain the optimal frame size in terms of reliability. While previous works generally use a Markovian approach, our model is based on dynamic systems theory, having a smaller computational cost which, in addition, is independent of the dimension of the system. Moreover, the proposed model allows us to identify the multiplicity of the equilibrium points in the system, an interesting and relevant property that has been overlooked in RFID systems so far. Finally, we present a design procedure based on our model that allows to configure the physical parameters of the system in order to adjust both the throughput and the reliability.

Ambient intelligence assistant for running sports based on k-NN classifiers

Outdoor sport practitioners can improve greatly their results if they train at the right intensity. Nevertheless, in common training systems the athletes performance is used for evaluation at the end of the exercises, and the sensed data is incomplete because only human biometrics are analyzed. These systems do not consider environmental conditions, which may have direct influence on athletes performance during training. In this paper, we present the system architecture and implementation of an ambient intelligence assistant for runners. Our system is composed of a Wireless Sensor Network (WSN) deployed over a cross-country running circuit, and by mobile elements carried by the users, which monitor their heart rate (HR). The goal is to select, for a given user, suitable tracks where the heart rate will be in the selected HR range. The decision-taking process is based on k-NN classification and has achieved a success classification ratio of 70%.

A Stochastic Shortest Path Model to Minimize the Reading Time in DFSA-Based RFID Systems

RFID systems implementing Dynamic Frame Slotted Aloha (DFSA) can adjust the number of identification rounds (slots) within an inventory cycle (frame). The usual approach to reduce the identification time of the tag population is to select the frame size attaining the highest throughput in the frame. However, it is more accurate to minimize the identification time of all the tags considering an indefinite long decision horizon. This is done in this paper by means of a Stochastic Shortest Path (SSP) formulation that incorporates capture effect and differentiation among slot durations. Our results show that the optimal policy is even faster than previous approaches.

Link-Layer Scheduling in Vehicle to Infrastructure Networks: An Optimal Control Approach

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.