GNSS spoofing is a growing threat to UAV operations, especially in decentralized drone swarms. In this paper, we present both a practical spoofing attack and a lightweight detection algorithm based on Wi-Fi RSSI and GNSS coordinates. The attack selectively compromises drones by transmitting a subset of satellite signals, causing drones to calculate wrong positions. Our detection method leverages geometric consistency checks to validate GNSS-based positions without requiring any infrastructure or additional sensors. Simulation results show that the proposed attack successfully misleads victim drones, and that the detection method reliably helps drones identify such attacks.

In unlicensed (shared) bands, wireless technologies typically operate without central coordination, which can lead to unwanted transmission interruptions, collisions, and resource wastage. We focus on Wi-Fi and NR-U coexistence in shared bands and solve the aforementioned problem with a deterministic backoff approach. The proposed scheme allows active transmitters to learn the number of nearby interferers in a distributed manner and, as a result, implement an ordered round-robin transmission schedule to minimize collisions. We show analytically that the scheme converges not only in equilibrium (when collisions are negligible), but also in a general case (when collisions are frequent at the beginning or in the middle of the proposed scheme's operation). Furthermore, extensive simulations prove that the proposed scheme guarantees fairness between contenting cells and technologies (both in terms of throughput and delay) as well as optimizes channel efficiency. We also study the impact of imperfect readings of the number of contending nodes (which may be the result of, e.g., asymmetric channel conditions) on the performance of the proposed scheme. In most cases, the deterministic backoff approach outperforms legacy channel access schemes. Additionally, our proposal does not add additional signaling overhead and is backward compatible with standard Wi-Fi and NR-U operation.

This survey explores the convergence of Internet of Things (IoT) technologies with Water Distribution Systems (WDSs), focusing on large-scale deployments and the role of edge computing (EC). Effective water management increasingly relies on IoT monitoring, resulting in massive deployments and the generation of Big Data. While previous research has examined these topics individually, this work integrates them into a comprehensive analysis. We systematically reviewed 255 studies on IoT in WDS, identifying key challenges such as interoperability, scalability, energy efficiency, network coverage, and reliability. We also examined technologies like LPWAN and the growing use of EC for real-time data processing. In large-scale WDS scenarios, where vast amounts of data are generated, we highlighted the importance of technologies like NB-IoT, SigFox, and LoRaWAN due to their low power consumption and wide coverage. Based on our findings, we provide guidelines for sustainable, large-scale IoT deployment in WDS, emphasizing the need for edge data processing to reduce cloud dependency, improve scalability, and enable smarter cities and digital twins.

This manuscript introduces a novel approach to integrate Large Language Models (LLMs) into wireless network testbeds for automated experimentation and optimization. We propose a framework that leverages LLMs to define system configurations using a structured format called Blueprint and analyse network behaviour through user-prompted queries. Our methodology combines few-shot prompting and prompt engineering to enable automated analysis of network configurations, enhancing decision-making and experimentation efficiency. We validated our approach in both simulated and real-world wireless environments and demonstrated its efficacy in streamlining experiment processes and extracting actionable insights. • Novel LLM-based framework for system configurations using standard Blueprints format. • Domain-agnostic few-shot prompting for automated wireless network configurations. • Real-world validation in Wireless network environments (e.g. LoRaWAN and Wi-Fi). • Practical LLM-driven anomaly detection to enforce network corrective actions.

This paper introduces an innovative Energy-Autonomous Wireless Sensing Node (EAWSN) that addresses power constraints by harnessing ambient light for energy. It combines this energy harvesting capability with the Time Domain to Digital Conversion (TDDC) technique for efficient and accurate measurements of resistive sensors. Bluetooth Low Energy (BLE) communication ensures data can be transmitted wirelessly to a base station, providing a promising solution for various applications, particularly in environments with limited access to wired power sources, enabling long-term, maintenance-free operation by eliminating batteries. Experimental results showed a linear relationship between the test resistance Rmand the measured number of clock pulses Nmwithin the sensor’s operating range.

In this paper, we present SDR-LoRa, an open-source, full-fledged Software Defined Radio (SDR) implementation of a LoRa transceiver. First, we conduct a thorough analysis of the LoRa physical layer (PHY) functionalities, encompassing processes such as packet modulation, demodulation, and preamble detection. Then, we leverage on this analysis to create a pioneering SDR-based LoRa PHY implementation. Accordingly, we thoroughly describe all the implementation details. Moreover, we illustrate how SDR-LoRa can help boost research on the LoRa protocol by presenting three exemplary key applications that can be built on top of our implementation, namely fine-grained localization, interference cancellation, and enhanced link reliability. To validate SDR-LoRa and its applications, we test it on two different platforms: (i) a physical setup involving USRP radios and off-the-shelf commercial devices, and (ii) the Colosseum wireless channel emulator. Our experimental findings reveal that (i) SDR-LoRa performs comparably to conventional commercial LoRa systems, and (ii) all the aforementioned applications can be successfully implemented on top of SDR-LoRa with remarkable results. The complete details of the SDR-LoRa implementation code have been publicly shared online, together with a plug-and-play Colosseum container.

With the advent of the modern pre-trained Transformers, the text preprocessing has started to be neglected and not specificly addressed in recent NLP literature. However, both from a linguistic and from a computer science point of view, we believe that even when using modern Transformers, text preprocessing can significantly impact on the performance of a classification model. We want to investigate and compare, through this study, how preprocessing impacts on the Text Classification (TC) performance of modern and traditional classification models. We report and discuss the preprocessing techniques found in the literature and their most recent variants or applications to address TC tasks in different domains. In order to assess how much the preprocessing affects classification performance, we apply the three top referenced preprocessing techniques (alone or in combination) to four publicly available datasets from different domains. Then, nine machine learning models - including modern Transformers - get the preprocessed text as input. The results presented show that an educated choice on the text preprocessing strategy to employ should be based on the task as well as on the model considered. Outcomes in this survey show that choosing the best preprocessing technique - in place of the worst - can significantly improve accuracy on the classification (up to 25%, as in the case of an XLNet on the IMDB dataset). In some cases, by means of a suitable preprocessing strategy, even a simple Naïve Bayes classifier proved to outperform (i.e., by 2% in accuracy) the best performing Transformer. We found that Transformers and traditional models exhibit a higher impact of the preprocessing on the TC performance. Our main findings are: (1) also on modern pre-trained language models, preprocessing can affect performance, depending on the datasets and on the preprocessing technique or combination of techniques used, (2) in some cases, using a proper preprocessing strategy, simple models can outperform Transformers on TC tasks, (3) similar classes of models exhibit similar level of sensitivity to text preprocessing.

In this paper, we present a novel intelligent management system (IMS) for smart retail environments that integrates various components to optimize user experience, energy efficiency, and seamless connectivity. The proposed architecture incorporates an Intelligent Handover Controller, an Energy Harvesting Module, Adaptive Resource Management, Edge Tracking and Localization. Preliminary testbed results show promising performance in maintaining seamless handovers between VLC and WiFi links, as well as accurate tracking of user mobility based on CSI. This advanced architecture offers the potential for significant improvements in smart retail operations by providing uninterrupted connectivity, targeted marketing, optimized store layouts, and enhanced user experiences.

According to IoT Analytics, NB-IoT, LoRaWAN, and Sigfox are today the most popular technologies for low-power wide-area networks (86% of the market), both in terms of end-user adoption as well as ecosystem support. While NB-IoT utilizes licensed bands, LoRaWAN and Sigfox both employ the sub-GHz ISM bands, potentially interfering with each other.In this paper, we present a thorough coexistence study between LoRaWAN and Sigfox, in realistic urban scenarios, with different duty cycles and traffic conditions. The choice of such scenarios and simulation parameters are supported by an in-depth lit-erature review, and simulations are based on the SEAMCAT simulator. The results offer new insights on the coexistence of LoRaWAN and Sigfox for emerging IoT applications. Finally, as interference mitigation strategy, we analyze the performance obtained applying protection distance mechanisms.

This article provides a survey on the adoption of LoRa in the agricultural field and reviews state-of-the-art solutions for smart agriculture, analyzing the potential of this technology in different infield applications. In particular, we consider four reference scenarios, namely, irrigation systems, plantation and crop monitoring, tree monitoring, and livestock monitoring, which exhibit heterogeneous requirements in terms of network bandwidth, density, sensors’ complexity, and energy demand, as well as latency in the decision process. We discuss how LoRa-based solutions can work in these scenarios, analyzing their scalability, interoperability, network architecture, and energy efficiency. Finally, we present possible future research directions and point out some open issues which might become the main research trends for the next years.

In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven different activities in a single environment. It is then tested on different setups, to assess its performance as the person, the day and/or the environment change with respect to those considered at training time. In the worst-case scenario, it reaches an average accuracy higher than$95\%$, validating the effectiveness of the extracted Doppler information, used in conjunction with a learning algorithm based on a neural network, in recognizing human activities in a subject and environment independent way. The collected CFR dataset and the code are publicly available for replicability and benchmarking purposes [1].

The legacy approach to solve coexistence problems between multiple wireless networks operating in the same frequency bands is through network planning. However, this approach is often unfeasible in unlicensed (shared) bands, where different network owners and technologies work without any coordination. In this paper, we adapt an existing channel access scheme for fair resource sharing between Wi-Fi and NR-U (the unlicensed version of 5G), in a completely distributed manner. The idea is to find an ordered schedule of transmissions granted to the active transmitters (regardless of their technology) and repeat this schedule in a round-robin fashion until the set of active transmitters changes. The mechanism works as a special extension of a random access scheme with deterministic backoff counters. Simulation-based results prove that the scheme guarantees airtime fairness between network cells and technologies while optimizing channel efficiency and minimizing channel access delays. Unlike other coexistence solutions, the scheme does not require the exchange of information between the coexisting cells; moreover, it is backward compatible with legacy access schemes.

The optimization and digitalization of Water Distribution Networks (WDNs) are becoming key objectives in our modern society. Indeed, WDNs are typically old, worn and obsolete. These inadequate conditions of the infrastructures lead to significant water loss due to leakages inside pipes, junctions and nodes. It has been measured that in Europe the average value of lost water is about 26 %. Leakage control in current WDNs is typically passive, repairing leaks only when they are visible. Emerging Low Power Wide Area Network (LPWAN) technologies, and especially IoT ones, can help monitor water consumption and automatically detect leakages. In this context, LoRaWAN can be the right way to deploy a smart monitoring system for WDNs. Moreover, most of the current smart WDNs solutions just collect measurements from the smart metres and send the data to the cloud servers, in order to execute the intended analyses, in centralised way. In this paper, we propose new solutions to improve monitoring, leak management and prediction by exploiting edge processing capabilities inside LoRaWAN networks. Our approach is based on an IoT system of water sensors that are placed at junctions of the WDN to have measurements in correspondence to various smart metres in the network and Machine Learning (ML) algorithms to process the data directly at the edge in order to visualise and predict leakages. We present a numerical simulation tool useful to evaluate the suggested monitoring method. Based on our results, we examine whether it is possible to identify network leaks using the edges without having a complete or accurate overview of the collected measurements of the full WDN. System performance is shown separately at gateways network.

Modern standards for IoT communications support fast deployment, large coverage in the order of kilometers, and physical layer adaptations to increase link robustness under time-varying propagation and interference conditions. A possible use of such IoT technologies is in case of emergency scenarios where first responders (FRs) arrive after a disastrous event. Indeed, an important challenge for emergency management is the need to (re)establish real-time communication capabilities and to offer integrated decision making facilities based on information gathered by FRs acting on the crisis site. In this paper, we present a system architecture based on LoRaWAN technology for connecting emergency operators in real-time and reliably communicating environmental information, audio streams/messages, and vital signs received from the first responders' sensors. In particular, based on LoRa modulation parameters, we propose an adaptation algorithm which adjusts user's voice messages and the resolution of the data flows to keep alive communications also when link quality is critically low, thus avoiding delay and saturation problems. Opportunistically, audio signals can be processed locally by the first responder's equipment with a speech-to-text conversion, thus significantly reducing traffic requirements. We demonstrate that the adaptation scheme can be performed real-time, even on a per-packet basis. Thanks this innovative system, FRs can communicate from the crisis site in an efficient and cost-effective way.

Wireless networks operating in unlicensed bands generally use one of two channel access paradigms: random access (e.g., Wi-Fi) or scheduled access (e.g., LTE License Assisted Access, LTE LAA and New Radio-Unlicensed, NR-U). The coexistence between these two paradigms is based on listen before talk (LBT), which was, however, designed for random access. Meanwhile, scheduled systems require that their transmissions start at the beginning of a slot boundary. Synchronizing this boundary to the end of LBT usually requires transmitting a reservation signal (RS) to block the channel. Since the RS is a waste of channel resources, we investigate an alternative self-deferral approach (gap-based access) using analytical and simulation models. We put forth a proposal to employ only self-deferral, treat the gap mechanism as a partial backoff, and adjust the contention window (CW) settings to the number of coexisting nodes. We demonstrate that this approach not only ensures fairness in Wi-Fi/NR-U coexistence but also avoids wasting radio channel resources and improves aggregate network throughput. Furthermore, we show that the proposed approach outperforms RS-based access and provides significant throughput and fairness gains. Finally, we implement a long short-term memory-based (LSTM) regression model to predict those Wi-Fi/NR-U CW settings which lead to coexistence fairness.

This paper presents a two-tier LiFi network and analyses the cross-tier handover rate between the primary and secondary cells. Based on the semiangle at half illuminance of the primary and secondary cells, we propose coverage model for the secondary cells. Using stochastic geometry, closed-form expressions are derived for the cross-tier handover rate and sojourn time in terms of the received optical signal intensity, time-to-trigger and user mobility. The analytical models are validated with simulation results.

Wireless technologies coexisting in unlicensed bands should receive a fair share of the available channel resources, even when they use different access methods. We consider the problem of coexistence between Wi-Fi and New Radio Unlicensed (NR-U) nodes, which employ, respectively, a random and scheduled access scheme. The latter typically resorts to reservation signals (RSs), which allow keeping the control of the channel until the start of the next synchronized slot. This mechanism, although effective for increasing the channel access opportunities of scheduled-based nodes, is also a waste of channel resources. We investigate alternative solutions, based on self-deferral only. We built analytical and simulations models for a Wi-Fi and NR-U coexistence scenario and found that (a) airtime fairness can be achieved with proper contention window (CW) settings and (b) this solution can be exploited for optimizing network performance for both Wi-Fi and NR-U. Additionally, we demonstrate how an artificial recurrent neural network-based regression model can be applied to predict such proper CW settings. Our research confirms that by embedding contending devices with machine learning intelligence in CW selection, scheduled-based systems such as NR-U do not have to resort to RSs.

Coexistence between cellular systems and Wi-Fi gained the attention of the research community when LTE License Assisted Access (LAA) entered the unlicensed band. The recent introduction of NR-U as part of 5G introduces new coexistence opportunities because it implements scalable numerology (flexible subcarrier spacing and OFDM symbol lengths), and non-slot based scheduling (mini-slots), which considerably impact channel access. This paper analyzes the impact of NR-U settings on its coexistence with Wi-Fi networks and compares it with LAA operation using simulations and experiments. First, we propose a downlink channel access simulation model, which addresses the problem of the dependency and non-uniformity of transmission attempts of different nodes, as a result of the synchronization mechanism introduced by NR-U. Second, we validate the accuracy of the proposed model using FPGA-based LAA, NR-U, and Wi-Fi prototypes with over-the-air transmissions. Additionally, we show that replacing LAA with NR-U would not only allow to overcome the problem of bandwidth wastage caused by reservation signals but also, in some cases, to preserve fairness in channel access for both scheduled and random-access systems. Finally, we conclude that fair coexistence of the aforementioned systems in unlicensed bands is not guaranteed in general, and novel mechanisms are necessary for improving the sharing of resources between scheduled and contention-based technologies.

This article proposes a new architecture for privacy-preserving data mining based on Multi Party Computation (MPC) and secure sums. While traditional MPC approaches rely on a small number of aggregation peers replacing a centralized trusted entity, the current study puts forth a distributed solution that involves all data sources in the aggregation process, with the help of a single server for storing intermediate results. A large-scale scenario is examined and the possibility that data become inaccessible during the aggregation process is considered, a possibility that traditional schemes often neglect. Here, it is explicitly examined, as it might be provoked by intermittent network connectivity or sudden user departures. For increasing system reliability, data sources are organized in multiple sets, called rings, which independently work on the aggregation process. Two different protocol schemes are proposed and their failure probability, i.e., the probability that the data mining output cannot guarantee the desired level of accuracy, is analytically modeled. The privacy degree, the communication cost and the computational complexity that the schemes exhibit are also characterized. Finally, the new protocols are applied to some specific use cases, demonstrating their feasibility and attractiveness.

LoRaWAN (Long 1 Range Wide Area Network) is an attractive network infrastructure and protocol suite for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative “sequential waterfilling” strategy for assigning spreading factors to End Devices. Our design relies on three complementary approaches: i) equalize the Time-on-Air of packets transmitted by the system's End Devices in each spreading factor's group; ii) balance the spreading factors across multiple gateways and iii) keep into account the channel capture, which our experimental results show to be very substantial in LoRa. While retaining an extremely simple and scalable implementation, this strategy yields a significant improvement (up to 38%) in the network capacity over the Adaptive Data Rate used by many network operators on the basis of the design suggested by Semtech, and appears to be extremely robust to different operating/load conditions and network topology configurations.

In recent years, underwater communications have seen a growing interest pushed by marine research, oceanography, marine commercial operations, offshore oil industry and defense applications. Generally, underwater communications employ audio signals which can propagate relatively far but are also significantly affected by Doppler distortions. In fact, physical properties of the water and spatial changes due to tides, currents and waves can cause channel variations or unwanted movements of the transmitter or receiver. This study shows how to compensate for the Doppler effect in transmission employing the JANUS standard, a popular modulation scheme for underwater communication. Differently form previous work, we use the pseudo-random symbols of the JANUS preamble to measure and compensate for Doppler distortions without changing the standard. The proposed method has been tested both on the Watermark simulator and real in-field experiments. Results show that the proposed technique allows to correctly receive over 90 % of the packets even with severe Doppler, compensating relative speeds up to 5 m/s.

Recent advances on WLAN technology have been focused mostly on boosting network capacity by means of a more efficient and flexible physical layer. A new concept is required at MAC level to exploit fully the new capabilities of the PHY layer. In this article, we propose a contention mechanism based on Repeated Contentions (ReCo) in frequency domain. It provides a simple-to-configure, robust and short-term fair algorithm for the random contention component of the MAC protocol. The throughput efficiency of ReCo is not sensitive to the number of contending stations, so that ReCo does not require adaptive tuning of the access parameters for performance optimization. Efficiency and robustness is gained through the power of repeated contention rounds. We also apply the ReCo concept to the emerging IEEE 802.11ax standard, showing how it can boost performance of random access with respect to the current version of IEEE 802.11ax OFDMA Back-Off (OBO). Our proposal is supported by an experimental test-bed that realizes ReCo by means of simultaneous transmission and reception of short tones, which is feasible on top of programmable OFDM PHY layers.

In this paper we study the capability of LoRa technology in rejecting different interfering LoRa signals and the impact on the cell capacity. First, we analyze experimentally the link-level performance of LoRa and show that collisions between packets modulated with the same Spreading Factor (SF) usually lead to channel captures, while different spreading factors can indeed cause packet loss if the interference power is strong enough. Second, we model the effect of such findings to quantify the achievable capacity in a typical LoRa cell: we show that high SFs, generally seen as more robust, can be severely affected by inter-SF interference and that different criteria for deciding SF allocations within the cell may lead to significantly different results. Moreover, the use of power control and packet fragmentation can be detrimental more than beneficial in many deployment scenarios. Finally, we discuss the capacity improvements that can be achieved by increasing the density of LoRa gateways. Our results have important implications for the design of LoRa networks: for example, allocating high SFs to faraway end devices might not improve the experienced performance in case of congested networks because of the increased transmission time and vulnerability period.

In this paper we show that inter-technology interference can be recognized by commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad PCS, invalid headers, etc.) and develop an Artificial Neural Network (ANN) to recognize the source of interference. The result is quite impressive, reaching an average accuracy of almost 99% in recognizing ZigBee, Microwave and LTE (in unlicensed spectrum) interference.

In this paper we propose ReCo, a robust contention scheme for emerging wireless technologies, whose efficiency is not sensitive to the number of contending stations and to the settings of the contention parameters (such as the contention windows and retry limits). The idea is iterating a basic contention mechanism, devised to select a sub-set of stations among the contending ones, in consecutive elimination rounds, before performing a transmission attempt. Elimination rounds can be performed in the time or frequency domain, with different overheads, according to the physical capabilities of the nodes. Closed analytical formulas are given to dimension the number of contention rounds in order to achieve an arbitrary low collision probability. Simulation results and a real implementation for the time-domain solution demonstrate the effectiveness and robustness of this approach in comparison to IEEE 802.11 DCF.

We present an innovative smartphone-centric tracking system for indoor and outdoor environments, based on the joint utilization of dead-reckoning and computer vision (CV) techniques. The system is explicitly designed for visually impaired people (although it could be easily generalized to other users) and it is built under the assumption that special reference signals, such as painted lines, colored tapes or tactile pavings are deployed in the environment for guiding visually impaired users along pre-defined paths. Thanks to highly optimized software, we are able to execute the CV and sensor-fusion algorithms in run-time on low power hardware such as a normal smartphone, precisely tracking the users movements.

In this demo we present and validate a LoRa cell traffic generator, able to emulate the behavior of thousands of low-rate sensor nodes deployed in the same cell, by using a single Software Defined Radio (SDR) platform. Differently from traditional generators, whose goal is creating packet flows which emulate specific applications and protocols, our focus is generating a combined radio signal, as seen by a gateway, given by the super-position of the signals transmitted by multiple sensors simultaneously active on the same channel. We argue that such a generator can be of interest for testing different network planning solutions for LoRa networks.

Most modern standards for wireless communications support physical layer adaptations, in terms of dynamic selection of channel central frequency, transmission power, modulation format, etc., in order to increase link robustness under time-varying propagation and interference conditions. In this demo, we demonstrate that another powerful solution for extending physical layer flexibility in OFDM-based technologies is the dynamic adaptation of the channel width. Although some standards already define the possibility of utilizing multiple channel widths (e.g. 20MHz, 10MHz, 5MHz for IEEE 802.11a standards), such an utilization is limited to a static configuration of a value defined during the network set-up. Conversely, we demonstrate that channel width adaptations can be performed in real-time during network operation, even on a per-packet basis. To this purpose, we propose an innovative and efficient receiver design, which allows the transmitter to take decisions about the channel width without explicitly informing the receiver.

In this paper, we present Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed demand response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. As overlay networks in communications establish logical links between peers regardless of the physical topology of the network, the Overgrid is able to apply some power balance criteria to its system of buildings, as they belong to a virtual microgrid, regardless of their physical location. We exploit an innovative distributed algorithm, called flow updating, for monitoring the power consumption of the buildings and the number of nodes in the network, proving its applicability in an Overgrid scenario with realistic power profiles and networks of up to 10 000 buildings. To quantify the energy balance capability of Overgrid, we first study the energy characteristics of several types of buildings in our university campus and in an industrial site to accurately provide some reference buildings models. Then, we classify the amount of “flexible” energy consumption, i.e., the quota that could be potentially exploited for DR programs. Finally, we validate Overgrid emulating a real P2P network of smart buildings behaving according to our reference models. The experimental results prove the feasibility of our approach.

In this demo we demonstrate the functionalities of a novel experimentation framework, called WiSHFUL, that facilitates the prototyping and experimental validation of innovative solutions for heterogeneous wireless networks, including cross-technology coordination mechanisms. The framework supports a clean separation between the definition of the logic for optimizing the behaviors of wireless devices and the underlying device capabilities, by means of a unifying platform-independent control interface and programming model. The use of the framework is demonstrated through two representative use cases, where medium access is coordinated between IEEE-802.11 and IEEE-802.15.4 networks.

In this paper we describe how a novel backoff mechanism called Moderated Backoff (MB), recently proposed as a standard extension for 802.11 networks, has been prototyped and experimentally validated on a commercial 802.11 card before being ratified. Indeed, for performance reasons, the time critical operations of MAC protocols, such as the backoff mechanism, are implemented into the card hardware/firmware and cannot be arbitrarily changed by third parties or by manufacturers only for experimental reasons. Our validation has been possible thanks to the availability of the so called Wireless MAC Processor (WMP), a prototype of a novel wireless card architecture in which MAC protocols can be programmed by using proper abstractions and a state-machine formal language, which enable easy modifications of legacy operations. Experimental results are in agreement with simulations and prove the effectiveness of Moderated Backoff, as well as the potentialities of the WMP platform.

This paper presents an approach to privacy-preserving data mining that relies upon a relatively simple secret sharing scheme. Its main feature is that users, sensitive data owners, are engaged in the secret sharing operations that protect their privacy. They are grouped in independent clouds connected to a central unit, the data miner, that only manages the aggregated data of each cloud, therefore avoiding the disclosure of information belonging to single nodes. We propose two privacy preserving schemes, with different privacy levels and communication costs. When designing them, we assume that some users' data might become inaccessible during the operation of the privacy preserving protocols, due to intermittent network connectivity or sudden user departures, and therefore introduce a new performance metric, the failure probability, defined as the probability that the mining output cannot guarantee the desired level of accuracy. We then discuss the attractive tradeoffs between privacy, accuracy and communication overhead that each scheme exhibits.

New pervasive technologies often reveal many sensitive information about users' habits, seriously compromising the privacy and sometimes even the personal security of people. To cope with this problem, researchers have developed the idea of privacy-preserving data mining which refers to the possibility of releasing aggregate information about the data provided by multiple users, without any information leakage about individual data. These techniques have different privacy levels and communication costs, but all of them can suffer when some users' data becomes inaccessible during the operation of the privacy preserving protocols. It is thus interesting to validate the applicability of such architectures in real-world scenarios. In this paper we experimentally evaluate two promising privac-preserving techniques on PlanetLab, analyzing the execution time and the failure rate that each scheme exhibits.

Recent years have witnessed the increasing adoption of heterogeneous wireless networks working in unlicensed ISM bands, thus creating serious problems of spectrum overcrowding. Although ZigBee, Bluetooth and WiFi networks have been natively designed for working in presence of interference, it has been observed that several performance impairments may occur because of heterogeneous sensitivity to detect or react to the presence of other technologies. In this paper we focus on the WiFi capability to detect interfering ZigBee links. Despite of the narrowband transmissions performed by ZigBee, in emerging scenarios ZigBee interference can have a significant impact on WiFi performance. Therefore, interference detection is essential for improving coexistence strategies in heterogeneous networks. In our work we show how such a detection can be performed on commodity cards working on time and frequency domain and also analysing data in the error domain. Errors are monitored and classified into error patterns observed in the network in terms of occurrence probability and temporal clustering of different error events. Through statistical analysis we are able to detect the presence of ZigBee transmissions measuring the errors raised by the WiFi card.

Wireless Body Area Networks (WBANs) have received much attention due to the possibility to be used in healthcare applications. For these applications, energy saving is a critical issue, as in many cases, batteries cannot be easily replaced. A transmit power control scheme, able to adapt to the variations of the wireless body channel, will allow consistent energy saving and longer battery life. In this paper we propose a transmit power control scheme suitable for IEEE 802.15.6 narrowband scheduled access networks, in which the transmission power is modulated frame by frame according to a run-time estimation of the channel propagation conditions. A simple and effective line search algorithm is proposed to estimate the channel quality based on the signal power received from the hub; in addition, an adaptive fade margin estimator is presented to determine an optimum margin based on the channel conditions. The approach allows tracking the highly variable propagation conditions due to the body mobility and the deployment of the sensors close to the human body. An experimental study in different test cases proves the effectiveness of the scheme in comparison with alternative solutions in the literature.

We introduce MAClets, software programs uploaded and executed on-demand over wireless cards, and devised to change the card's real-time medium access control operation. MAClets permit seamless reconfiguration of the MAC stack, so as to adapt it to mutated context and spectrum conditions and perform tailored performance optimizations hardly accountable by an once-for-all protocol stack design. Following traditional active networking principles, MAClets can be directly conveyed within data packets and executed on hard-coded devices acting as virtual MAC machines. Indeed, rather than executing a pre-defined protocol, we envision a new architecture for wireless cards based on a protocol interpreter (enabling code portability) and a powerful API. Experiments involving the distribution of MAClets within data packets, and their execution over commodity WLAN cards, show the flexibility and viability of the proposed concept.

Programmable wireless platforms aim at responding to the quest for wireless access flexibility and adaptability. This paper introduces the notion of wireless MAC processors. Instead of implementing a specific MAC protocol stack, Wireless MAC processors do support a set of Medium Access Control “commands” which can be run-time composed (programmed) through software-defined state machines, thus providing the desired MAC protocol operation. We clearly distinguish from related work in this area as, unlike other works which rely on dedicated DSPs or programmable hardware platforms, we experimentally prove the feasibility of the wireless MAC processor concept over ultra-cheap commodity WLAN hardware cards. Specifically, we reflash the firmware of the commercial Broadcom AirForce54G off-the-shelf chipset, replacing its 802.11 WLAN MAC protocol implementation with our proposed extended state machine execution engine. We prove the flexibility of the proposed approach through three use-case implementation examples.

The problem of resource allocation in cellular networks has been traditionally faced at two different levels: at the network level, in terms of frequency planning and reuse pattern design, and at the cell level, in terms of cell capacity optimizations based on channel-dependent scheduling, link adaptation, power control, and so on. While this second aspect has been deeply investigated in literature, the first aspect has been mainly faced with static or semi-dynamic reuse utilization solutions. In this paper we deal with the problem of multi-cellular resource allocation in heterogeneous OFDMA environments with reuse factor equal to 1, where base stations with different power constraints coexist. In particular, we analyze the effects of different allocation schemes, independently performed in each cell, on the aggregated network-level performance. By means of simulation results, we enlighten the network scenarios in which network planning and mobile station feedbacks are (or not are) advantageous.

In WiFi networks, mobile nodes compete for accessing a shared channel by means of a random access protocol called Distributed Coordination Function (DCF). Although this protocol is in principle fair, since all the stations have the same probability to transmit on the channel, it has been shown that unfair behaviors may emerge in actual networking scenarios because of non-standard configurations of the nodes. Due to the proliferation of open source drivers and programmable cards, enabling an easy customization of the channel access policies, we propose a game-theoretic analysis of random access schemes. We show that even when stations are selfish, efficient equilibria conditions can be reached when they are interested in both uploading and downloading traffic. We explore the utilization of the Access Point as an arbitrator for improving the global network performance. Finally, we propose and evaluate some simple DCF extensions for practically implementing our theoretical findings.

In this paper we propose a game-theoretic approach for characterizing WiFi network performance in presence of intelligent nodes employing cognitive functionalities. We assume that a cognitive WiFi node is aware of its application requirements and is able to dynamically estimate the network status, in order to dynamically change its access strategy by tuning the contention window settings. We prove that, for infrastructure networks with bidirectional traffic and homogeneous application requirements, selfish access strategies are able to reach equilibrium conditions, which are also Pareto optimal. Indeed, we show that the station strategies converge toward values which maximize a per-node utility function, while maintaining performance fairness.

Wireless multi-hop networks often rely on the use of IEEE 802.11 technology. Despite of the robustness of the IEEE 802.11 Distributed Coordination Function (DCF) for working in various network scenarios, it has been proven that critical inefficiencies can arise in the case of multi-hop packet forwarding. In this paper, we propose a MAC scheme, based on the visualization of the Point Coordination Function, optimized for working on chain topologies with bidirectional traffic flows. Our scheme is based on a token-like access mechanism coupled with network coding. The basic idea is the use of multiple Point Coordinators (PCs) along the node chain, which are elected by passing special token frames. Since traffic sources are located at the edge of the chain and intermediate nodes act as relays, we also exploit network coding for merging uplink and downlink traffic. Analytical and simulation results prove that our scheme can provide an aggregated uplink and downlink throughput comparable with bidirectional point-to-point transmissions.

A very common conclusion of many experimental studies about IEEE 802.11 outdoor network deployments is that their poor performance results derive from the unfavorable interference and multi-path signals in which the WLAN-cards are required to operate. Goal of this paper is to show that this condition does not always hold, and unexpected and inaccurated PHY layer implementations can be a primary cause of packet losses. With the support of extensive measurement campaigns led in our campus, we provide the performance evidence that IEEE 802.11 outdoor performance impairments are strongly affected by proprietary interference mitigation techniques that adaptively adjust the WLAN-card receiver sensitivity thresholds on the basis of the perceived noise levels. Because of the immediate relationship between these receiver sensitivity parameters with the carrier sense functions, we show how, in highly interfered outdoor scenarios, interference mitigation algorithms may cause tremendous amplifications of either the hidden or the exposed terminal phenomena, thus determining dramatic wireless link failures. Surprisingly, deactivating such mechanisms allows to achieve high link quality performance.

In the last years, several strategies for maximizing the throughput performance of IEEE 802.11 networks have been proposed in literature. Specifically, it has been shown that optimizations are possible both at the medium access control (MAC) layer, and at the physical (PHY) layer. In fact, at the MAC layer, it is possible to minimize the channel waste due to collisions and backoff expiration times, by tuning the minimum contention window as a function of the network congestion level. At the PHY layer, it is possible to improve the transmission robustness, by selecting a suitable modulation/coding scheme as a function of the channel quality perceived by the stations. However, the feasibility of these optimizations rely on the availability of MAC/PHY measurements, which are often impracticable or very rough. In this paper, we propose a joint MAC/PHY estimator based on a bi-dimensional extended Kalman filter, devised to separately track the collision probability and the channel error probability suffered by each station. To this purpose, we derive a relationship between the unobservable system state and measurements which are performed in a distributed way by all the competing stations.

This paper provides experimental evidence that "weird'/poor outdoor link-level performance measurements may be caused by driver/card-specific antenna diversity algorithms unexpectedly supported/activated at the WLAN transmitter side. We focus our analysis on the Atheros/MADWiFi card/driver case, and we observe that the transmit antenna diversity mechanisms remain by default enabled when the available antennas are not homogeneous in terms of gain or, even worse, when only a single antenna is connected. This may cause considerable performance impairments (large frame loss ratio), in conditions frequently encountered in outdoor link deployments. The negative impact of transmit antenna diversity is not limited to the transmission of broadcast frames (where a cyclic shift between the "two" assumed antennas is performed), but under certain circumstances it can severely affect the delivery of unicast frames as well, and despite the fact that in this case the ACK receptions may provide a feedback about the best receiving antenna. While, as obvious, driver developers are expectedly fully aware of the existence of such mechanisms, we believe that the scientific research community has very limited awareness of the implications these mechanisms have on the measured link-level performance. Indeed, to the best of our knowledge, ours is the first research paper which explicitly raises this issue.

Recently, the impressive success of the IEEE 802.11 WLAN technology has dramatically changed the role of the wireless connectivity provisioning. Born as a wireless extension of small office or home networks, todays the WLANs are getting more and more popular as a large, even metropolitan, area networks. The deployment of large-scale WLANs has some critical issues, because of the lack of coordinated management functionalities among the network nodes. In this paper we briefly describe the CAPWAP architectural solution, for centralizing some control and maintenance functionalities in large scale WLAN, by guaranteeing the interoperability between network nodes provided by different vendors. We also investigate on a simple and efficient application for optimizing the wireless network resources, which is possible thanks to the centralization of some control operations. In particular, we propose an automatic frequency planning algorithm, not requiring any network administrator aids, which we tested via simulation and we implemented in an actual testbed.

It has been observed that different IEEE 802.11 commercial cards produced by different vendors experience different performance, either when accessing alone the channel, as well as when competing against each other. These differences persist also when thorough measurement methodologies (such as RF shielding, laptop rotation, etc) are applied, and alignment of the environmental factors (same laptop models, traffic generators, etc) is carried out. This paper provides an extensive experimental characterization of the backoff operation of six commercial NIC cards. It suggests a relevant methodological approach, namely a repeatable, well defined, set of experiments, for such a characterization. Low level backoff distribution measurements are taken through a custom equipment developed in our laboratory. Our work allows to detect both a non-standard backoff behavior of some commercial cards (in terms of minimum contention window size and neglection of EIFS times), as well as potential implementation limits (in either the card hardware/firmware and/or the software driver) which appear to severely alter the card performance in challenging conditions.

Recently, the impressive success of the IEEE 802.11 WLAN technology has dramatically changed the role of the wireless connectivity provisioning. Born as a wireless extension of small office or home networks, todays the WLANs are getting more and more popular as a large, even metropolitan, area networks. The deployment of large-scale WLANs has some critical issues, because of the lack of coordinated management functionalities among the network nodes. In this paper we briefly describe the CAPWAP architectural solution, for centralizing some control and maintenance functionalities in large scale WLAN, by guaranteeing the interoperability between network nodes provided by different vendors. We also investigate on a simple application for optimizing the wireless network resources, which is possible thanks to the centralization of some control operations. In particular, we propose an automatic frequency planning algorithm, not requiring any network administrator aids, which we tested via simulation and we implemented in an actual testbed.

In recent years, the physical layer data rate provided by 802.11 Wireless LANs has dramatically increased thanks to significant advances in the modulation and coding techniques employed. However, previous studies show that the 802.11 MAC operation, namely the distributed coordination function (DCF), represents a limiting factor: the throughput efficiency drops as the channel bit rate increases, and a throughput upper limit does indeed exist when the channel bit rate goes to infinite high. These findings indicate that the performance of the DCF protocol will not be efficiently improved by merely increasing the channel bit rate. This paper shows that the DCF performance may significantly benefit from the adoption of two separate physical carriers: one devised to manage the channel access contention, and another devised to deliver information data. We propose a scheme, referred to as out-of-band signaling (OBS), designed to reuse (and remain backward compatible with) the existing 802.11 medium access control (MAC) specification. Performance evaluation of OBS is carried out through analytical techniques validated via extensive simulation, for both saturation and statistical traffic conditions. Numerical results show that OBS improves the throughput/delay performance, and provides better bandwidth usage compared with the in-band signaling technique employed by DCF.

Quality of service support in wireless LAN is a theme of current interest. Several solutions have been proposed in literature in order to protect time-sensitive traffic from best-effort traffic. According to the EDCA proposal, which is a completely distributed solution, the service differentiation is provided by giving probabilistically higher number of channel accesses to stations involved in real-time applications. To this purpose, the MAC parameter settings of each contending stations can be tuned dynamically. In this paper, we face the problem of tuning the EDCA MAC parameters in common scenarios in which a given number of low-rate delay-sensitive traffic flows share the channel with some stations involved in data transfer. Our contribution is threefold. First, we show that, whenever possible, the delay constraints of the high priority class can be satisfied in both the cases of contention windows differentiation and inter-frame space differentiation. However, these mechanisms have different side effects in terms of bandwidth availability for the best effort stations. Second, we propose to exploit the MAC parameter dynamic settings of EDCA in order to probabilistically guarantee the delay requirements and to jointly maximize the aggregated throughput of the network. Finally, we suggest a very simple solution to automate these parameter settings in a real scenario, where traffic flows can be activated/deactivated dynamically, by simply monitoring the channel activity. The proposed solution is very robust, since it does not require any a priori traffic model or any network load estimator.

Many models have been proposed to analyze the performance of the IEEE 802.11 distributed coordination function (DCF) and the IEEE 802.11e enhanced distributed coordination function (EDCA) under saturation condition. To analyze DCF under statistical traffic, Foh and Zukerman introduce a model that uses Markovian Framework to compute the throughput and delay performance. In this paper, we analyze the protocol service time of EDCA mechanism and introduce a model to analyze EDCA under statistical traffic using Markovian Framework. Using this model, we analyze the throughput and delay performance of EDCA mechanism under statistical traffic.

It has been observed that IEEE 802.11 commercial cards produced by different vendors show a different behavior in terms of perceived throughput or access delay. Performance differences are evident both when the cards contend alone to the channel, and when heterogeneous cards contend together. Since the performance misalignment does not disappear by averaging the environmental factors (such as propagation conditions, laptop models, traffic generators, etc), it is evident that the well known throughput-fairness property of the DCF protocol is not guaranteed in actual networks. In this paper we propose a methodological approach devised to experimentally characterize the IEEE 802.11 commercial cards thus understanding and predicting their performances in different network scenarios. We set up some specific experiments using a custom test equipment, able to classify the card behavior not only in terms of figures which are evident to the user perspective (such as the throughput), but also in terms of low-level channel access operations and delays. Our approach is able to detect potential hardware limits or not-standard MAC implementations, which severely affect the contending card performance.

Directional antennas may dramatically increase the capacity of a wireless LAN by allowing several stations to simultaneously communicate. Since deployment of directive/smart antennas on the customer's terminals is awkward (for technological, cost, robustness, and convenience reasons) it is of interest to deploy advanced antenna solutions only at the access point. When omnidirectional transmissions are used at the mobile stations, the asynchronous nature of the 802.11 MAC handshake structurally limits the possibility to exploit spatial reuse. Significant throughput enhancements can be achieved only at the expense of redesigning (part of) the 802.11 MAC protocol: mainly a form of synchronization is required. This paper addresses this problem and proposes a novel solution, devised to operate in the above scenario. The system operation is based on the joint usage of space division and time division multiple access techniques. A synchronous time-division structure avoids unwanted interference among different antenna coverage regions. Backward compatibility with legacy IEEE 802.11 terminals is also accounted for.

The channel utilization efficiency of the standard 802.11 networks is severely compromised when high data transmission rates are employed, since physical layer headers and control frames are transmitted at low rate, thus wasting more channel time, proportionally. The extensions defined in the emerging 802.11e for quality-of-service (QoS) provisioning include some new mechanisms developed in order to improve the efficiency. Those include data transmission bursting (referred to as TXOP operation) and acknowledgment aggregation (referred to as block ACK). These two features allow it to offer new data transmission services, in which the data delivery and acknowledgment unit is not a single frame, but a block of frames. In this paper, we evaluate the performance of these operations for both basic and RTS/CTS access cases. We quantify how the data bursting and block ACK mechanisms can affect the system efficiency for different environments, and derive the maximum achievable throughput. We also discuss the operating conditions at which the switch from one channel utilization method to another is desired.

The IEEE 802.11e extensions for QoS support in WLAN define the transmission opportunity (TXOP) concept, in order to limit the channel holding times of the contending stations in the presence of delay-sensitive traffic. We evaluate the use of TXOP for a different purpose: "temporal fairness" provisioning among stations employing different data rates. We show that the equalization of the channel access times allows each station to obtain its throughput basically (1) proportional to its transmission rate, and (2) independent of the transmitted frame length. This also improves the aggregate throughput of the overall WLAN. For a given TXOP limit, i.e., a granted channel access time, a station is required to fragment its pending frame if the TXOP limit is too short, and is allowed to transmit multiple frames back-to-back in a burst if the TXOP limit is long enough, while different fragmentation and bursting rules are possible. Based on the analytical and simulation results, we demonstrate the advantages of TXOP operations over the legacy 802.11 DCF, and compare different TXOP managing policies to find the optimal one.

IEEE 802.11 medium access control (MAC), called distributed coordination function (DCF), provides two different access modes, namely, 2-way (basic access) and 4-way (RTS/CTS) handshaking. The 4-way handshaking has been introduced in order to combat the hidden terminal phenomenon. It has been also proved that such a mechanism can be beneficial even in the absence of hidden terminals, because of the collision time reduction. We analyze the effectiveness of the RTS/CTS access mode, in current 802.11b and 802.11a networks. Since the rates employed for control frame transmissions can be much lower than the rate employed for data frames, the assumption on the basis of the 4-way handshaking introduction, i.e., a short transmission time for the RTS control frame, is no longer valid. As a consequence, the basic access mode results in the optimal access solution in most cases, even in heavy load conditions with hidden nodes. We compare the 2-way and 4-way access performances through both analytical and simulation tools. We also discuss the operating conditions at which the switch from one access mode to another is desired for the cases of uniform and heterogeneous data rates among the stations. We conclude that, for the heterogeneous data rate environments, the RTS/CTS threshold should be redefined as a frame transmission time rather than as a frame size.

In this paper, we study the performance of our earlier proposed out-of-band signaling (OBS) scheme for high speed wireless local area networks (WLANs). We employ the system approximation technique for modeling of the OBS scheme. An equivalent state dependent single server queue, that describes the OBS scheme, is constructed for the analysis of the throughput and delay performances. Moreover, we study the throughput optimization of the OBS scheme, which provides a means for optimizing the performance of the OBS scheme, given a particular network environment. Finally, we conduct several simulation experiments to validate our analytical results.

The IEEE 802.11e draft specification aims to extend the original 802.11 MAC protocol by introducing priority mechanisms able to manage bandwidth and resource allocation according to the QoS needs of real-time applications. Different strategies based on MAC parameter diversifications, such as contention window limits, contention window updating factor and silence monitoring time, can be pursued in order to provide service differentiation, also in the case of distributed access. In this paper, we investigate on the behaviour of each differentiation possibility under different load conditions and traffic requirements. Our results show that the most powerful mechanisms which provide service differentiation are based on inter frame space (IFS) and minimum contention window (CW/sub min/) diversification. We conclude that the best differentiation policy should be based on a joined use of IFS and CW/sub min/ differentiation, using the first parameter to adjust access probabilities, and the second parameter to optimize the resource utilization in the network.

Abstract This paper refers to a wireless cellular packet network scenario where fast retransmission of corrupted packets is used to improve the packet error ratio. Since the ‘gross’ packet transmission rate (including retransmission) depends on the channel quality perceived, admitted calls weight unevenly in terms of effective resource consumption. In this paper, we suggest using channel quality information to drive load balancing mechanisms. We propose two novel metrics to determine the best cell to attach to, during handover or new call origination. Extensive simulation results prove the superiority of our proposed schemes with respect to traditional load balancing, which base their operation on the number of admitted calls per cell. Copyright © 2004 John Wiley & Sons, Ltd.

Throughput performance of the IEEE 802.11 distributed coordination function (DCF) is very sensitive to the number n of competing stations. The contribute of this paper is threefold. First, we show that n can be expressed as function of the collision probability encountered on the channel; hence, it can be estimated based on run-time measurements. Second, we show that the estimation of n, based on exponential smoothing of the measured collision probability (specifically, an ARMA filter), results to be a biased estimation, with poor performance in terms of accuracy/tracking trade-offs. Third, we propose a methodology to estimate n, based on an extended Kalman filter coupled with a change detection mechanism. This approach shows both high accuracy as well as prompt reactivity to changes in the network occupancy status. Numerical results show that, although devised in the assumption of saturated terminals, our proposed approach results effective also in non-saturated conditions, and specifically in tracking the average number of competing terminals.

This paper provides a comparative performance evaluation of various load balancing schemes in cellular packet networks. With respect to circuit switched networks, wireless packet technology adds the further issue of quality of service of accepted connections. In fact, with packet technology, transmission error performance does not uniquely depend on the perceived channel quality, but it can be improved by adopting a scheduling mechanism enforcing fast retransmission of corrupted packets. The result is that throughput can be traded off with QoS experienced by an admitted flow. This paper proposes new packet-level load balancing mechanisms. In addition to the number of calls admitted in a cell, our schemes use supplementary packet level information, expressed in terms of effective resource consumption of each individual call when retransmission mechanisms are employed. Simulation results prove the superiority of our proposed schemes with respect to traditional load balancing schemes.

This paper provides a comparative performance evaluation of various load balancing schemes in cellular packet networks. With respect to traditional schemes, that measure each cell load in terms of number of admitted calls, our schemes use supplementary packet level information, expressed in terms of effective resource consumption of each individual call when retransmission mechanisms are employed. The simulation model adopted is based on a toroidal cellular network topology, to avoid border effects affecting the numerical results.

The algorithm which selects the best candidate base station to connect to is a key component in handover and admission control schemes for wireless cellular networks. This paper shows that, in wireless packet networks based on dynamic channel slot assignment, this algorithm can exploit additional packet-level information. The idea is that connections consume a different amount of resources even if they have the same nominal rate. In fact, corrupted packets can be retransmitted, and the retransmission overhead reflects the time varying channel quality perceived by each connection. We propose two novel load balancing metrics that effectively account for the uneven "weight" of each connection in terms of its up-to-date resource consumption. The performance of the proposed metrics are then evaluated for a particular (i.e. static) scenario. Although supplementary investigation is required in dynamic scenarios, our preliminary results provide new insights in the field of handover and admission control, and appear to open a new promising research area.