Dense passive radio frequency identification (RFID) systems are particularly susceptible to reader collision problems, categorized by reader-to-tag and reader-to-reader collisions. Both may degrade the system performance decreasing the number of identified tags per time unit. Although many proposals have been suggested to avoid or handle these collisions, most of them are not compatible with current standards and regulations, require extra hardware and do not make an efficient use of the network resources. This paper proposes the Geometric Distribution Reader Anti-collision (GDRA), a new centralized scheduler that exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA provides higher throughput than the state-of-the-art proposals for dense reader environments and, unlike the majority of previous works, GDRA is compliant with the EPCglobal standard and ETSI EN 302 208 regulation, and can be implemented in real RFID systems without extra hardware.Note to Practitioners -UHF RFID systems with multiple readers are commonly installed in many scenarios, where readers are placed in strategic places for checking specific areas. In these scenarios, the reader interferences occur and they can degrade the performance of our system. An efficient anticollision scheduler is necessary for avoiding and minimizing these interferences, and the current standards and regulations do not propose any efficient solution. In this work, a new scheduler is proposed to get the best performance of a typical UHF RFID system with multiple readers. Our proposal is compatible with the global standard and the current European regulations and is designed to be implemented in any commercial UHF reader in the market without extra hardware cost.Index Terms-EPCglobal, ETSI EN 302 208, reader collision problems, radio frequency identification (RFID, sift geometric distribution function.

5G envisages a "hyper-connected society" where an enormous number of devices are interconnected anywhere and at any time. Cloud-enabled radio access networks (RAN) where intelligence is placed in conjunction with the radio heads at the proximity of end users is a promising solution to fulfil the 5G expectations of sub-millisecond latency, huge traffic volumes and higher data rates. Network Functions Virtualization (NFV) and Software Defined Networking (SDN) developments enable end users to access advanced features such as configurability, automation, scalability, improved resource utilization and multi tenancy over the cloud-enabled RANs. Management and orchestration techniques are the ultimate factor that determine the effectiveness of the novel SDN/NFV features being introduced. Our focus in this study is the resource allocation in a realistic cloud-enabled RAN, taking into account the dynamics of ~100,000 persons movement in a crowded event, i.e. a football match. The proposed solution jointly orchestrates NFV and bandwidth resources, as one resource affects the other. Simulation results clearly verify the benefits of the proposed solution over traditional disjoint schemes.

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Abstract-Cooperative inter-vehicular applications rely on the exchange of broadcast single-hop status messages among vehicles, called beacons. The aggregated load on the wireless channel due to periodic beacons can prevent the transmission of other types of messages, what is called channel congestion due to beaconing activity. In this paper we approach the problem of controlling the beaconing rate on each vehicle by modeling it as a Network Utility Maximization (NUM) problem. This allows us to formally apply the notion of fairness of a beaconing rate allocation in vehicular networks and to control the trade-off between efficiency and fairness. The NUM methodology provides a rigorous framework to design a broad family of simple and decentralized algorithms, with proved convergence guarantees to a fair allocation solution. In this context, we focus exclusively in beaconing rate control and propose the Fair Adaptive Beaconing Rate for Intervehicular Communications (FABRIC) algorithm, which uses a particular scaled gradient projection algorithm to solve the dual of the NUM problem. The desired fairness notion in the allocation can be established with an algorithm parameter. Simulation results validate our approach and show that FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.

This paper addresses the problem of finding a static virtual topology design and flow routing in transparent optical WDM networks under a time-varying (multi-hour) traffic demand. Four variants of the problem are considered, using fixed or dynamically adaptable (i.e., variable) flow routing, which can be splittable or unsplittable. Our main objective is to minimize the number of transceivers needed which make up for the main network cost. We formulate the problem variants as exact ILPs (Integer Linear Programs) and MILPs (Mixed ILPs). For larger problem instances, we also propose a family of heuristics based on the concept of domination between traffic matrices. This concept provides the theoretical foundations for a set of techniques proposed to reduce the problem complexity. We present a lower bound to the network cost for the case in which the virtual topology could be dynamically reconfigured along time. This allows us to assess the limit on the maximum possible benefit that could be achieved by using optical reconfigurable equipment. Extensive tests have been conducted, using both synthetically generated and real-traced traffic demands. In the cases studied, results show that combining variable routing with splittable flows obtains a significant, although moderate, cost reduction. The maximum cost reduction achievable with reconfigurable virtual topologies was shown to be negligible compared to the static case in medium and high loads.