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Given the importance of line-of-sight in mmWave communications, a strategic adversary can harm a transmission by obstructing the receiver, which in turn can react by trying to move around this hurdle. To expand on this point, we study one such scenario from the perspective of game theory, considering a mobile mmWave receiver and an adversary interacting strategically as players in a zero-sum game, where they want to maximize, or respectively minimize, the spectral efficiency of the communication. To do so, the adversary attempts at screening the receiver's line of sight as an obstacle, while the receiver can move around so as to avoid the blockage. We consider preset distances and the choices available to the players are to change their angular coordinates to go around each other. This is framed as a static game of complete information, for which we numerically find the Nash equilibrium in mixed strategies, drawing some interesting conclusions such as connecting it with the beamforming pattern of the transmitter., Comment: 8 pages, 6 figures. Published on MedComNet 2022

Dynamic time-division duplexing (TDD) enables independent uplink/downlink mode scheduling at each cell, based on the local traffic. However, this creates cross-interference among cells. Thus, the joint power allocation and scheduling problem becomes mixed-integer non-convex and turns out to be NP-hard. We propose a low-complexity and decentralized solution, where power allocation and scheduling are decoupled. First, power is allocated in a decentralized fashion, and then modes are scheduled by a non-cooperative game to achieve the mixed-strategy Nash equilibrium. We consider two possible approaches to compute the payoffs in the game, according to the cross-interference power model and the entailed communication overhead among cells. Simulation results are presented for an outdoor dense small-cell scenario, showing that our approaches outperform static TDD significantly.

Age of information (AoI) is one of the key performance metrics for Internet of things (IoT) systems. Timely status updates are essential for many IoT applications; however, they are subject to strict constraints related on the available energy and unreliability of underlying information sources. Hence, the scheduling of status updates must be carefully planned to preserve energy, but at the same time, it may happen that when a status update is needed, there is no reliable up-to-date information content to refresh. As a solution to overcome these unpredictabilities, one can employ multiple sources that track the same signal of interest, but with different energy costs and reliabilities, which we call information source diversity. We consider an energy-harvesting monitoring node equipped with a finite-size battery and collecting status updates from multiple heterogeneous information sources. We investigate the policies that minimize the average AoI, and evaluate the role of information source diversity on the system performance. To do so, we formulate the problem as a Markov decision process (MDP). The optimal policy represents the scheduling of actions, such as an update from one of the sources or remaining idle, based on the current energy level and the AoI at the monitoring node. We analyze the structure of the optimal solution for different cost/AoI distribution combinations, and compare the performance of the optimal policy with an aggressive strategy that transmits whenever possible.

Data collected and transmitted by Internet of things (IoT) devices are typically used for control and monitoring purposes; and hence, their timely delivery is of utmost importance for the underlying applications. However, IoT devices operate with very limited energy sources, severely reducing their ability for timely collection and processing of status updates. IoT systems make up for these limitations by employing multiple low-power low-complexity devices that can monitor the same signal, possibly with different quality observations and different energy costs, to create diversity against the limitations of individual nodes. We investigate policies to minimize the average age of information (AoI) in a monitoring system that collects data from two sources of information denoted as primary and backup sources, respectively. We assume that each source offers a different trade-off between the AoI and the energy cost. The monitoring node is equipped with a finite size battery and harvests ambient energy. For this setup, we formulate the scheduling of status updates from the two sources as a Markov decision process (MDP), and obtain a policy that decides on the optimal action to take (i.e., which source to query or remain idle) depending on the current energy level and AoI. The performance of the obtained policy is compared with an aggressive policy for different system parameters. We identify few types of optimal solution structures and discuss the benefits of having a backup source of information in the system.

This article explores the implementation of different sampling strategies for a practical energy‐harvesting wireless device (sensor node) powered by a rechargeable battery. We look for a realistic yet effective sampling strategy that prevents packet delivery failures, which is simple enough to be implemented in low‐complexity hardware. The article proposes methods that balance erratic energy arrivals and include advantages of dynamic data‐driven approaches based on historical data. Due to the industrial requirements in terms of minimum acceptable sampling frequency, we also integrate sampling rate limits and verify the proposed methods. To do so, we simulated the operation of an industrial data logger powered with a solar panel relying on the enhanced state of the model for battery charging. Finally, the proposed methods are compared based on energy consumption over a year and the amount of packet delivery failures, thus showing how some modifications of available strategies achieve satisfactory performance in this sense. &nbsp

We present a game-theoretic analysis of the interaction between a malicious node, attempting to perform unauthorized radio transmission, and friendly jammers trying to disrupt the malicious communications. We investigate the strategic behavior of the jammers against a rational malicious node and highlight counterintuitive results for this conflict. We also analyze the impact of multiple friendly jammers sharing the same goal but acting without coordination; we find out that this scenario offers a better payoff for the jammers, which has some strong implications on how to implement friendly jamming.

The definition of “energy topologies” based on energetic cooperation (exploitation and exchange) between interconnected objects is an important feature that can be implemented in Smart Cities. Based on the presence of energy harvesting devices, it is aimed at providing system-wide sustainability by allowing exchange of stored and supplied energy in a similar fashion to communication of data. In this paper, we investigate the possibility of integrating energy cooperation within the design of the energy topology, or, in other words, by establishing energy links between objects, in particular wireless smart nodes powered by harvesting renewable energy sources. To do so, we construct an optimization model, where it is guaranteed that wireless nodes during operation will not be depleted and the optimal energy transfer does not exceed the energy demands of other communication nodes. We analyze how the system conditions can affect the energy topology, in particular, energy harvesting capabilities, energy levels, and energy thresholds. We also identify some theoretical limits for the system to guarantee complete sustainability, that is, nodes do not go out of charge. Also we demonstrated the effectiveness of the model comparing it with the system operation without applied optimization.

In this paper, we consider energy cooperation in an Internet of Things (IoT) smart city scenario. We assume the presence of interconnecting energy harvesting IoT gateways (GWs), that are endowed with energy harvesting capabilities and whose role is to collect and aggregate data from field sensing devices. Energy cooperation complements and balances the energetic needs to those devices that are neither connected to the power grid, nor satisfactorily served by energy harvesting due to the instability of ambient energy arrivals. The proposed solution entail energy transfers from energy rich gateways to energy scarce ones, i.e., those which are not connected to the power grid. To identify the optimal energy transfer/allocation scheme, we formulate a convex optimization problem that finds the optimal solution for heterogeneous smart systems. With this energy allocation technique, the gateways are unlikely to run out of energy during operation and the gap between energy offer and demand among interconnected gateways is kept to a minimum. We also quantify the performance of the proposed energy transfer policies as a function of network parameters, including: the amount of traffic generated by sensing devices, the number of smart services in the system, and the number of gateways that are connected to the power grid.

Interactions between pedestrians, bikers, and human-driven vehicles have been a major concern in traffic safety over the years. The upcoming age of autonomous vehicles will further raise major problems on whether self-driving cars can accurately avoid accidents; on the other hand, usability issues arise on whether human-driven cars and pedestrians can dominate the road at the expense of the autonomous vehicles which will be programmed to avoid accidents. This paper proposes some game theoretical models applied to related traffic scenarios. In the first two games the reciprocal influence between a pedestrian and a vehicle (either autonomous or not) is analyzed, while the third game investigates the intersection of two vehicles, possibly autonomous. The games have been simulated in order to demonstrate the theoretical analysis and the predicted behaviors. These investigations can shed new lights on how novel urban traffic regulations could be required to allow for a better interaction of vehicles and a general improved management of traffic and communication vehicular networks., Accepted at 'IEEE International Symposium on Personal, Indoor and Mobile Radio Communications' 9-12 September 2018 - Bologna, Italy. Special Session on 'Wireless Technologies for Connected and Autonomous Vehicles'. 7 pages, 5 figures

This work presents an innovative application of the well-known concept of cortico-muscular coherence for the classification of various motor tasks, i.e., grasps of different kinds of objects. Our approach can classify objects with different weights (motor-related features) and different surface frictions (haptics-related features) with high accuracy (over 0.8). The outcomes presented here provide information about the synchronization existing between the brain and the muscles during specific activities; thus, this may represent a new effective way to perform activity recognition.

Underwater acoustic networks make it possible to wirelessly convey information, e.g., coming from measurements and sensing applications from under water to the surface. However, underwater communications are characterized by long delays, small available bandwidths and high error rates. These aspects may significantly affect the design of a reliable data-link layer for such systems. In this paper, we assess the performance of hybrid automatic repeat request error control schemes and we evaluate their application to improve the reliability of time-varying underwater acoustic links. We employ a parametric Markov model, which has been trained over channel traces collected during at-sea experiments. The results, based on both experimental data and analysis, suggest that parametric probabilistic representations, such as the considered Markov model, are good candidates for describing the correlated underwater acoustic channel dynamics, and may be employed to achieve a realistic evaluation of the data-link layer performance for underwater acoustic scenarios. Analytical and simulation results confirm that incremental redundancy improves the throughput of underwater acoustic links, even when real channel conditions, such as those encountered in the considered experiments, have wide dynamics over time. Finally, this kind of evaluations, beyond the data-link design, can also be employed at the network level for routing and network deployment considerations.

We consider the management of an energy harvesting wireless sensor network, inspired by game theory so as to obtain a distributed multi-agent operation. In particular, we focus on asymmetries in the nodes energetic capabilities, and how do they impact on the resulting performance. We frame the problem as a repeated Bayesian game with asymmetric players and incomplete information, where also the private information available at each node is asymmetric. We find out that instead of a proportionally fair resource utilization, such a situation ends up in an even more unbalanced situation, which leads to an inefficient management where certain nodes are utilized beyond their fair share. Future research directions are identified so as to recover information about asymmetries from the strategic gameplay of the sensors and thus enable a better management.

Energy harvesting is an important feature that can be implemented in mobile devices to provide them with extended autonomy, yet it poses several challenges in terms of optimal battery usage. In this paper, we highlight that some non-ideal effects, especially the so-called "charge recovery," can have a dramatic impact on the operation policy of autonomous devices. To do so, we construct a Markov model, where we introduce a bidimensional battery value, including the apparent energy level, which is what available at the electrodes to power the device, and the actual energy level stored in the battery. When power is not drained by the device, these levels tend to equalize due to charge recovery, but, in the case of intense battery usage, they can be significantly different. We show that this non- ideality leads to considerably different estimates of undesirable events such as battery outages, and may cause a general underutilization of the devices if not properly accounted for.

The article describes the potential gain by spectrum sharing between cellular operators in terms of network efficiency. The focus of the study is on a specific resource sharing scenario: spectrum sharing between two operators in cellular downlink transmission. If frequency bands are allocated dynamically and exclusively to one operator - a case called orthogonal spectrum sharing - significant gains in terms of achievable throughput (spectrum sharing gains between 50 percent and 100 percent) and user satisfaction are reported for asymmetric scenarios at link and system level as well as from two hardware demonstrators. Additionally, if frequency bands are allocated simultaneously to two operators - a case called non-orthogonal spectrum sharing - further gains are reported. In order to achieve these, different enablers from hardware technologies and base station capabilities are required. However, we argue that all requirements are fulfilled in 3GPP and newer mobile standards. Therefore, the results and conclusions of this overview article encourage to seriously consider the inter-operator spectrum sharing technologies.

We present a framework, based on Markov models, for the analysis of error control techniques in video transmission over wireless channels. We focus on retransmission-based techniques, which require a feedback channel but also enable to perform adaptive error control. Traditional studies of these methodologies usually consider a uniform stream of data packets. Instead, video transmission poses the non-trivial challenge that the packets have different sizes, and, even more importantly, are incrementally encoded; thus, a carefully tailored model is required. We therefore proceed on two different sides. First, we consider a low-level description of the system, where two main inputs are combined, namely, a video packet generation process and a wireless channel model, both described by Markov Chains with a tunable number of states. Secondly, from a high-level perspective, we represent the whole system evolution with another Markov Chain describing the error control process, which can feed the packet generation process back with retransmissions. The framework is able to evaluate hybrid automatic repeat request with selective retransmission, but can also be adapted to study pure automatic repeat request or forward error correction schemes. In this way, we are able to comparatively evaluate different solutions for video transmission, as well as to quantitatively assess their performance trends in a variety of scenarios. Thus, our framework can be used as an effective tool to understand the behavior of error control techniques applied to video transmission over wireless, and eventually identify design guidelines for such systems.

In this paper, we present a methodology to obtain a channel description tailored on performance evaluation for incremental redundancy hybrid automatic repeat request schemes. Such techniques counteract channel errors by using data coding and transmitting parts of the codeword over different channel realizations. We focus on coding performance models where the error probability is asymptotically zero if the channel parameters of these realizations fall within a given region. To map this region in a compact but still precise manner, we adopt a finite-state channel model. This approach is quite common in the literature; however, differently from existing work, we propose a novel method to derive efficient channel partitioning rules, i.e., a code-matched quantization of the channel state. Such a representation enables the use of accurate Markov models to study the system performance. Compared to existing channel representation methods, our proposed technique leads to a more accurate evaluation of higher layer statistics while at the same time keeping the computational complexity low.

Wireless mesh networks are an attractive technology for providing broadband connectivity to mobile clients who are just on the edge of wired networks, and also for building self-organized networks in places where wired infrastructures are not available or not deemed to be worth deploying. This paper investigates the joint link scheduling and routing issues involved in the delivery of a given backlog from any node of a wireless mesh network towards a specific node (which acts as a gateway), within a given deadline. Scheduling and routing are assumed to be aware of the physical interference among nodes, which is modeled in the paper by means of a signal-to-interference ratio. Firstly, we present a theoretical model which allows us to formulate the task of deriving joint routing and scheduling as an integer linear programming problem. Secondly, since the problem cannot be dealt with using exact methods, we propose and use a technique based on genetic algorithms. To the best of our knowledge, these algorithms have never been used before for working out these kinds of optimization problems in a wireless mesh environment. We show that our technique is suitable for this purpose as it provides a good trade-off between fast computation and the overall goodness of the solution found. Our experience has in fact shown that genetic algorithms would seem to be quite promising for solving more complex models than the one dealt with in this paper, such as those including multiple flows and multi-radio multi-channels.

This paper presents an analytical model for the study of hybrid ARQ techniques on discrete time Markov channels by means of an appropriate Markov chain, which tracks the transmission outcome and can be used to evaluate several performance metrics, including throughput, loss probability, number of retransmissions, and delay. The analysis is carried out with the assumptions that the information frame is encoded by the source with a linear block code and hard decoding is used at the receiver side. We finally present numerical evaluations for the performance of a truncated type II hybrid ARQ technique based on Reed Solomon erasure codes.

In this letter we discuss the exploitation of aggregated mobility patterns in mobile networks including heterogeneous multiple access techniques. We advocate the use of knowledge about neighboring devices to create routing groups (RGs) of adjacent nodes in order to optimize radio resource management. Basically, RGs consist of aggregated logical structures which are built and maintained at the application layer. Their use allows decreased signaling overhead between groups of nodes and access points (AP) and, at the same time, improved connectivity, which is achieved through the exploitation of technology diversity and relaying schemes. We illustrate a simple yet effective analytical model, and validate it through accurate simulation results. Finally, we show the effectiveness of the RG approach in terms of resource efficiency, throughput and multiple access performance.

This article reviews routing algorithms in heterogeneous wireless networks with the goal of including QoS awareness. After a general overview of the issues and challenges of QoS provisioning over heterogeneous networks, classic routing strategies are revisited, and how they can be exploited to achieve QoS efficiency is discussed. In particular, for the considered scenarios our proposal is to account for some proactivity in the routing algorithms, as well as a QoS-driven control selection, which are shown to improve throughput, delay, and energy consumption. Finally, we introduce a general backward utility formulation for user satisfaction as a tool to capture complex and dynamic QoS variations

The use of a larger bandwith in the millimeter wave (mmWave) spectrum is one of the key components of next generation cellular networks. Currently, part of this band is allocated on a co-primary basis to a number of other applications, such as the fixed satellite services (FSSs). In this paper, we investigate the coexistence between a cellular network and FSSs in a mmWave scenario. In light of the parameters recommended by the standard and the recent results presented in the literature on the mmWave channel model, we analyze different BSs deployments and different antenna configurations at the transmitters. Finally, we show how, exploiting the features of a mmWave scenario, the coexistence between cellular and satellite services is feasible and the interference at the FSS antenna can be kept below recommended levels.

The increasing demand for higher data rates has accelerated research on the next generation of mobile cellular networks (5G). One of the key factors of 5G is the use of a larger bandwidth allocated in the millimeter wave (mmWave) frequency spectrum. In particular, one of the candidate bands is the portion of spectrum between 17 and 30 GHz that is currently used by other technologies such as fixed satellite services (FSS) and the cellular network backhaul. In this paper, we analyze the coexistence between mobile services and FSS considering the main characteristics of the mmWave spectrum recently investigated in the literature. Moreover, we present a novel cooperative scheduling algorithm based on a game theoretic framework that exploits the use of analog beamforming at the base stations (BS). Finally, we show that adopting this algorithm ensure that the system meets the regulatory recommendation concerning the interference level at the FSS and at the same time provides a good user spectral efficiency.

In this letter we investigate the packet delay statistics of a fully reliable selective repeat ARQ scheme by considering a discrete time Markov channel with non-instantaneous feedback and assigned round-trip delay m. Our focus is on studying the impact of the arrival process on the delay experienced by a packet. An exact model is introduced to represent the system constituted by the transmitter buffer, the m round-trip slots, and the channel state. By means of this model, we evaluate and discuss the delay statistics and we analyze the impact of the system parameters, in particular the packet arrival rate, on the delay statistics

In this paper the packet delay statistics of a fully reliable selective repeat ARQ (SR ARQ) scheme is investigated. An N-state discrete time Markov channel model is used to describe the packet error process and the channel round trip delay is considered to be non zero, i.e., ACK/NACK messages are received at the transmitter m channel slots after the packet transmission started. The ARQ packet delay statistics is evaluated by means of an exact analysis by jointly tracking packet errors and channel state evolution. Furthermore, procedures to derive a Markov channel description of a Rayleigh fading process are discussed and the delay statistics obtained from the Markov analysis is compared with that estimated by simulation of the SR ARQ protocol over the actual fading process. The accuracy of the delay statistics obtained from the Markov Channel representation of the actual fading process is investigated by explicitly addressing the effect of the number of states considered in the Markov channel model and the impact of the Doppler frequency. Finally, besides giving a new analysis to obtain link layer statistics over N-state Markov channels, the paper provides important considerations on the adequacy of the widely used Markov modeling approach for the characterization of higher layer performance

In the context of dynamic spectrum access, spectrum sharing among multiple operators has recently emerged as a promising paradigm to improve the efficiency of resource usage. Several theoretical evaluations have proven the benefits offered by pooling the available frequencies so as to tune the capacity offered by the operators according to their different needs, especially the service demands from their users. However, practical aspects concerning the application of sharing techniques are rarely studied, and deserve more detailed investigations. This paper aims at tackling this problem, in particular investigating the impact of asymmetries and dynamics of the user demands on the implementation of spectrum sharing techniques and the resulting performance, especially in terms of fairness among the users, which seems to be often neglected by many studies. We show that in variable traffic conditions, a constantly monitored and updated sharing of frequency bands performs much better than a static allocation simply based on average traffic loads. However, it is possible to choose the update rate of the spectrum allocation so that it does not represent a heavy computational and signaling burden, while retaining most of the improvements brought by the spectrum sharing paradigm.

Data-bundling is a useful technique that decreases the delivery delay of packet streams when they are transmitted over noisy channels and are subject to retransmission-based error control. In this paper, we investigate the packet delay statistics for a fully reliable selective repeat automatic repeat request (SR ARQ) where a data-bundling mechanism is employed. In more detail, we discuss a model for data-bundling to analyze the SR ARQ mechanism over wireless channels based on Markov chains. We evaluate various channel error distributions and analyze the buffer occupancy to check if the data-bundling mechanism provides efficient results. We further analyze the queueing, delivery and overall delay statistics at link layer. We found that using data-bundling can improve the delay performance of the SR ARQ mechanism, especially when bursty channels with heavily correlated errors are considered. Thus, this technique can bring useful improvements for real-time services, multimedia, and other delay-sensitive applications over wireless networks.

Several techniques for wireless networking, such as opportunistic spectrum access, or self-healing networks, may be seen as using a form of cognition, meaning that they mimic reasoning processes of intelligent beings. We propose to expand this cognition-based process by exploiting the parallel processing power of the infrastructure, so as to go beyond cognition as is meant by these approaches. We leverage novel approaches, taken from cognitive science and artificial intelligence, involving not only supervised but also unsupervised learning, and we envision their application to systems for video over wireless. The transmission of multimedia content, and its adaptation to the condition of the communication infrastructure, i.e., the wireless channel or the content delivery network, are envisioned as particularly critical steps for the development of latest generation mobile networks. For this scenario, we propose and evaluate a video classifier based on a Restricted Boltzmann Machine that tries to extract abstract features of videos from the analysis of the sizes of a few coded frames. These features can then be exploited by the communication network itself to optimize video transmission based on its content.

Smart grids are a novel paradigm for energy distribution, where instead of the traditional directed flow from a producer to the consumers, several micro-generators are spread throughout the network. We focus on the problem of coordinating the injection of active power into the grid by the micro-generators. Each of them aims at injecting the maximum amount of power, satisfying some operative constraints such as voltage boundaries; a tradeoff must be found among these conflicting objectives. First, we characterize the active power increment region, i.e., the set of all the increments of injected power that, depending on the grid state, satisfy the voltage boundary. Based on this finding, we frame the problem within game theory and propose a distributed approach that achieves a fair share of the active power injection, while at the same time satisfying the voltage boundary.

Users of video multicast groups are highly heterogeneous in terms of individual channel conditions and requirements for video transmission. Their experienced quality may vary, making it a challenging task for the network to optimally configure the resource management. In this paper, we consider mathematical model to represent layered video content delivery in a multicast group. We compare various network policies to choose the optimum number of transmit opportunities and we investigate the role of feedback, which, if present, dynamically tunes the resource management. We analyze the actual perceived quality of the users as well as how their satisfaction levels vary in the multicast session. Simulation results show that the presence of feedback generally enhances the overall users quality; however, this improvement is heavily related to the resource allocation policy of the operator.

In this paper, we focus on next-generation cellular networks and discuss physical resources sharing among the operators. This implies cooperative usage of the available radio frequencies and also infrastructure sharing. In particular, we analyze the spectrum sharing gain achievable at different time scales and the main factors impacting on it. Then, we move towards a wider idea of resource sharing and consider a joint spectrum and infrastructure sharing (full sharing). We describe a two-layer resource management architecture that enables operators to reduce costs while still guaranteeing a good service level. The main findings of our investigations are to quantify the effectiveness of resource sharing and open up new perspectives for the operators of next-generation networks. © 2012 IEEE.

ISSN: 1530-1346, ISBN: 978-1-4244-7754-8 (Print) Video transmission is expected to be the next big thing in personal communication systems. While text messaging applications have already experienced an explosive growth, the exchange of multimedia content is still lacking architectural solutions which enable it to become the next killer application. The EU project MEDIEVAL (MultimEDia transport for mobIlE Video AppLications) [1] aims at filling this gap. In this paper we describe the approaches envisioned by the project for what concerns the data link layer, with special emphasis on wireless access and its related cross-layer issues. After presenting some general project aspects, we will review the state of the art and enumerate several open issues, concerning the identification of the most suitable radio technologies for video support, as well as their integration and required enhancements to enable efficient video transport. TRUE pub

This paper proposes a novel approach, based on game theory, for radio resource allocation in the downlink of cellular networks using Orthogonal Frequency Division Multiple Access. The reference technology is the Long Term Evolution of the 3GPP UTRAN. The main contribution is to identify a model for the allocation objectives, and how to approach them in a tunable manner. The resource management issue is framed in the context of spectrum sharing, where multiple entities agree on utilizing the radio access channel simultaneously. A trade-off between sum-rate throughput and fairness among the users is identified and addressed through game theory, i.e., moving the operation of the system towards a stable Pareto efficient point. Such a methodology can be implemented with low complexity while ensuring logical modularity of the overall system. Numerical results are also shown, to exemplify the validity of the proposed approach.

Multimedia real-time traffic is deemed to be dominant in future communication systems. One of the reference applications to support real-time traffic is the Real-time Trans port Protocol (RTP), which can be used to transmit multimedia contents on real-time basis. At the same time, Real-time Transmission Control Protocol (RTCP) is used for receiving feedback and getting information about the network. This paper proposes and evaluates a traffic management implementation in such an RTP/RTCP environment for congestion control. Deficit Round Robin queue discipline is used as the traffic management strategy instead of Random Early Detection and Drop Tail queue disciplines. A simulation campaign was performed to analyze the effects of implemented traffic strategies in RTP/RTCP environment and compare it with previous solutions. The obtained results highlight a significant difference in terms of jitter delay and packet losses and improvement the bandwidth utilization for real-time flows. Thus, we are able to provide quantitative evidence of the importance of the queue discipline to efficiently manage multimedia content

This paper proposes a variation to the classic implementation of Automatic Repeat reQuest (ARQ) which is particularly suitable for the long delay channels, as can be found, for example, in the underwater environment. The proposed technique, called Selective Repeat with a Second Replica ARQ, (SR)^2 ARQ, follows the same rationale as Selective Repeat ARQ, but, upon NACK reception, schedules two retransmissions, one taking place immediately, and the other put in a special queue to be released after further retransmissions, but before new packet transmissions. We propose an exact analysis of this technique, proving its ability of trading throughput for shorter delivery delay; thus, it is suitable for scenarios where the required data rate is not high, but a timely data delivery is very important, as is the case, for example, for underwater monitoring applications.

Traditional analog video surveillance systems technology has recently become inadequate to face the massive demand of security systems consisting of hundreds and sometimes thousands of cameras often deployed in hostile environments miles away from the control room. During the last few years, the rapid growth of the digital technology has produced sophisticated cameras which can directly record highdefinition digital videos. The packetized video stream can be straightforwardly conveyed to the control room, relaying on common IP network infrastructures. This solution result is extremely flexible as the network infrastructure can be built over a wide variety of heterogeneous network technologies from the traditional Ethernet-based Local Area Networks (LANs) to the recently proposed Wireless Mesh Networks (WMNs). However, the widespread adoption of IP-based solutions for video surveillance poses serious problems in terms of required bandwidth, processing power, network security, and system dependability. In this chapter, we first investigate the advantages of the IP-based video surveillance systems over the traditional analog ones. Then, we describe the technical challenges and the open research issues which still lack an ultimate solution which permits to completely abandon the traditional analog technology. Finally, we propose and verify, by means of a case study, a methodology to address the design of video surveillance systems in real deployment.

Joint design and optimization of traditionally independent problems such as routing and link scheduling have recently become one of the leading research trends in wireless mesh networks. Although technically challenging, cross-layering is, in fact, expected to bring significant benefits from the network resource exploitation standpoint to achieve high system utilization. In this article we propose a versatile framework for joint design of routing and link scheduling, introducing the notion of link activation constraints, which are related to the transceiver capability and the broadcast nature of the wireless medium. To this end, we introduce a taxonomy of wireless interference models to harmonize existing approaches presented in the literature. Finally, we evaluate the impact on network capacity of the various interference models when optimal joint routing and link scheduling are employed.

This paper addresses feedback design issues in ad hoc networks with simultaneous access of multiple users, when type II HARQ exploits a constrained capacity reverse channel. In such networks, communications performance is limited by interference and nodes operate in a distributed fashion; thus, efficient resource allocation relies on proper feedback signaling, which on the other hand can use only a limited amount of network resources. For this reason, we investigate how to determine a finite set of feedback messages, which accounts for the underlying type II HARQ error control and jointly regulates power allocation and medium access in an optimal manner.

This paper investigates routing strategies for mobile and heterogeneous multi-hop wireless networks. We leverage the knowledge about users mobility to improve the efficiency of route discovery and of the following data forwarding phase. In particular, we exploit group mobility behaviors, which allow us to apply a distributed on-line algorithm for the recognition of aggregated mobility patterns. Hence, we adopt a novel routing strategy that uses the aggregate structure formed within this algorithm to simplify the exchange of signaling and data messages. Finally, we demonstrate and quantify the benefits obtained with the proposed technique by means of a simulator for heterogeneous wireless networks.

In this paper we discuss the exploitation of aggregated mobility patterns and physical proximity of nodes in a so-called ambient network, i.e., a wireless network with heterogeneous nodes and access techniques. We advocate to use the knowledge about node movements and geographical positions to create routing groups of adjacent nodes, which might be beneficial in order to decrease signaling overhead and increase transmission efficiency. Basically, routing groups (RGs) consist of aggregated logical structures which are built and maintained at the application layer. Their aim is to decrease the signaling overhead between group of nodes and access points and, at the same time, to improve connectivity by exploiting technology diversity and relaying techniques. On this matter, we describe a validation through simulation of a previously developed analytical work which is useful to evaluate the effectiveness of RG structures. Finally, we show the validity of the RG approach in terms of throughput and connectivity performance.

This paper is a sequel of previous work, in which we proposed a model and computational technique to calculate the Erlang capacity of a single CDMA cell that supports elastic services. The present paper extends that base model by taking into account two important features of CDMA. First, we capture the impact of soft blocking by modeling the neighbor cell interference as a lognormally distributed random variable. Secondly, we model the impact of the outage by taking into account that in-progress sessions can be dropped with a probability that depends on the current load in the system. We then consider a system with elastic and rigid service classes and analyze the trade-off between the total (soft and hard) blocking probabilities on the one hand and the throughput and the session drop probabilities on the other.

Underwater sensor networks are a very interesting case of wireless communication in extreme conditions. They exploit acoustic communication in the water and are nowadays used in surveillance and monitoring applications. These networks present very challenging aspects, such as low data rates and large delays, as well as the special propagation characteristics of the underwater medium. We propose an integer-linear programming approach to jointly optimize routing, link-scheduling and node placement in such a scenario. Accounting for these special aspects of underwater wireless communications leads to re-thinking traditional approaches; this results in original solutions, which highlight novel directions for further research in this area.

In this paper we investigate new features of future generation networks, where the availability of several different access technique is integrated by means of common radio resource management interfaces and, at the same time, information about the mobility context and the physical proximity of some nodes is exploited. In particular, we advocate utilizing this knowledge in order to create routing groups of adjacent nodes, which might be beneficial in order to improve connectivity, decrease signalling overhead and increase transmission efficiency. An analytical framework is proposed, which allows the performance evaluation of device aggregation algorithms, by measuring several connectivity metrics (routing hierarchy, amount of information to be exchanged, energy consumption) under the cases where either routing groups are established or not. In this way, many detailed insights for the network connectivity performance are obtained, which can be adapted to any context due to the analytical formulation. Therefore, it might be useful for the evaluation of the grouping effectiveness and its application to real cases.