This study investigates the role of convolutional layers in deep convolutional neural networks for scenarios involving interactions between the users and road-interaction environment. The user-driving behaviour and road environment exhibit unique features, and applications often require training-specific models for each user-environment pair. This leads to significant data collection and computational demands, including model training, thus necessitating efficient solutions to minimise these requirements. The aim is to determine whether the convolutional layers of deep convolutional autoencoders (DCAEs) are more specific to the user or the environment. The distinction might lead to optimising training strategies that reduce resource requirements. Case studies and data collection are performed on multiple bicyclists navigating various road segments. We evaluated the specificity of convolutional layers using metrics such as training epochs, execution time, model and parameter loading times, and total training loss. The results confirmed that the patterns learned by the outer convolutional layers are predominantly user-specific, emphasising individual behaviour over road-environment factors. This user-specific pattern recognition enhances model efficiency, reduces data requirements, and improves accuracy in predicting user behaviour across varying environments. Furthermore, after analysing training strategies, we found that complete refinement provided higher accuracy and stability at the cost of longer training and loading times. By contrast, freezing layers allowed faster initialisation but might necessitate extended training in complex cases. Finally, we examined the implications of these findings for improving safety and performance in driver-road interactions.

Oceans and seas are today mostly unexplored. In the aim of supporting their exploration, the vision of an Internet of Underwater Things (IoUT) emerged recently, indeed targeted at providing a degree of pervasiveness and connectivity in our seas, similarly to what happens in traditional terrestrial networks. This foreseen pervasiveness should however not be detrimental, from a sustainability point of view, to the environment. Accordingly, in this paper we present a semantic-based integrated sensing and communication solution specifically designed for the IoUT. We consider an acoustic underwater network where smart sensor nodes perform image collection and analysis to detect rare marine species. Based on the analysis of the collected data, the smart devices, equipped with a software radio, set physical layer parameters such as transmission gain, payload length, and modulation scheme, so that they communicate relevant data but minimize their impact on rare marine creatures identified in the area. This implies reduction in the sea noise level which could be dangerous for mammals, such as whales or dolphins. AI techniques are employed to classify images collected through sensors and accordingly tune transmission parameters. Performance analysis assess the effectiveness of the approach.

Next-generation networks aim to extend the Internet of Everything (IoE) vision to terrestrial, aerial, and underwater domains. However, when considering acoustic underwater sensing and communications, as traditionally done in the marine scenarios, challenges such as limited bandwidth, high latency, and energy constraints need to be faced. To address these limitations, this paper proposes a distributed AI-based framework for the realization of the Internet of Underwater Things (IoUT), enabling smart sensor nodes to perform localized data processing and adaptive communication. Our system integrates intelligent computing devices with underwater sensing capabilities, allowing cameraequipped nodes to classify marine species using lightweight AI models deployed directly on the nodes. Instead of transmitting raw data, nodes share only classification results, drastically reducing data volume. Software-defined radio (SDR) systems dynamically adapt transmission parameters (e.g., transmission power, modulation, etc.) to minimize energy consumption and environmental impact on marine ecosystems. This decentralized methodology enhances scalability, reduces latency, and saves resources while enabling real-time decision-making in dynamic environments. Performance evaluations using GNU Radio simulations prove reliable data delivery, measured by bit error rate (BER), throughput, and latency, while prioritizing marine ecosystem preservation. Results highlight the system's ability to balance efficiency, sustainability, and ecological conservation in next-generation underwater networks in view of realizing the vision of an Internet of Underwater Things.

In vehicular networks, decentralized cooperative learning strategies have gained significant attention due to the lower communication overhead they involve when compared to centralized cooperative learning approaches like Federated Learning. Decentralized solutions enable vehicles to collaboratively train Machine Learning (ML) models by exchanging parameters without relying on a central server. However, conventional model-sharing methods still suffer from high communication overhead and increased vulnerability to poisoning attacks. This paper presents SPARE , a gossip-based cooperative learning protocol that leverages Vehicle-to-Vehicle (V2V) communication to enhance communication efficiency by exchanging selected model parameters. SPARE selects vehicle nodes for model updates and transmits only the most significantly updated layers, reducing redundancy and improving efficiency. This selective exchange minimizes communication resource consumption and enhances privacy, as the complete model is never shared across the network. We assess the proposed approach using a real-world driving dataset, featuring data from multiple drivers along the same route. Experimental results prove that our method achieves efficient learning with significantly lower communication overhead, demonstrating its suitability for deployment in resource-constrained vehicular networks.

In this work i-WSN League, a comprehensive hardware/software framework for the support of distributed training and inference is introduced. For what concerns the hardware, in i-WSN League two types of nodes are considered, namely, head nodes and common nodes. Head nodes are resource rich nodes that have the capabilities for training artificial neural network. Common nodes collect data and can execute inference only. In i-WSN League, all nodes are grouped in Clusters, each with a Cluster Head (selected among the head nodes), which is the only node responsible for training. To this end, data coming from all nodes in the Cluster can be utilized. This, however, involves large exchange of data which might be unsustainable by common nodes. Thus, only part of the data collected by common nodes is sent to the Cluster Heads and a network of Cluster Heads will implement distributed learning in a peer-to-peer fashion. As compared to state of the art literature, the key contributions of our work are related to the combination of gossiping and clustering to adapt the operations executed by each node to its capabilities, with the aim of minimizing the energy consumption in resource limited nodes, while preserving accuracy. In this paper i-WSN League is assessed in a simple scenario in which a wireless sensor network monitors the air pollution in a large city. Performance results obtained by considering auto-encoders prove the effectiveness of the proposed scheme as well as its balanced energy consumption and fairness in resource consumption distribution.

The introduction of the Software Defined Networking (SDN) paradigm is radically changing the way in which networks are thought, designed, and managed. The reasons of such huge success are manifold; one of the most relevant is that SDN enables an agile management of the network that can quickly adapt its behavior to the dynamics of the user needs and context conditions. In this sense, SDN represents a fundamental step towards the vision of an autonomous network. Nevertheless, network adaptation still requires the intervention of the network manager that installs and configures the network applications executed by the network operating system. In this context, the application of the Digital Twin (DT) technology can trigger a significant leap forward. In fact, the DT of the network can interact with the other relevant DTs and, applying artificial intelligence techniques, interact with the network operating system and take care of the network application installation and configuration. In this paper we motivate and introduce a platform, implemented exploiting microservices, for the realization of such a vision. The proposed platform is applied in a simple use case to demonstrate the proposed workflow and the resulting impact on network operations.

In this paper, a software defined networking approach, named SDN-(UAV)ISE, is introduced for wireless sensor networks with data mules. In our scenario, sensor nodes are equipped with two wireless interfaces: one exploits a long range, low data rate wireless technology, such as LoRa or Sigfox, whereas the other uses a short range, wireless technology that provides higher data rate, examples include IEEE 802.15 or IEEE 802.11. Sensors can communicate directly to a control center through the long range wireless interface, or by utilizing the multihop paradigm realized with the aid of the short range wireless communication interface. In this context, a drone acts as a mobile sink (i.e., the mule) for the latter case. The movement of the data mule is forecast by the SDN controller and the forecast positions are considered to generate the flow table entries to be installed in the sensor nodes and schedule their applications. To this purpose, it is expected that the drone will move to the locations where abnormal conditions are observed by the sensors. In our work, a simple and efficient decision tree algorithm is implemented, which takes the values measured by the sensors as inputs, to forecast the route of the data mule. The proposed scheme is assessed through a large experimental campaign considering different operating conditions.

In this paper an analytical framework based on ordinary differential equations (ODE) is derived which models the propagation of worms injecting false traffic information in a Vehicular Sensor Networks (VSN) by exploiting V2V communications. This is a relevant problem because faulty traffic information can deviate traffic flows causing a decrease in the vehicle density in certain areas which results in a reduction of the sensing power of the VSN. Therefore, in this work the interactions between worm infection propagation and the mobility of infected vehicles are analyzed. The proposed framework is applied to an urban scenario in which mobility traces are generated by exploiting the urban mobility simulator SUMO.

In recent years identifier/locator splitting (ILS) has been proposed as a promising future Internet solution to the so-called “semantic overload of addresses” problem. It is currently under debate whether the ILS approach, which entails identifier-to-locator resolution procedures, could ensure scalability, session continuity, and mobility across heterogeneous multiaccess networks as demanded by Internet of Things (IoT). In this paper, it is proposed to exploit the Social IoT concept to address the above issues. More specifically, a scheme is introduced that browses the social graph of devices to find information about the locator of the intended destination. Results show that the proposed solution outperforms the alternative ILS approaches in terms of number of hops and latency incurred to accomplish the resolution procedure, at the cost of a slight increase in the storage demands to track social relationships.

The Identifier/Locator Splitting (ILS) paradigm has been proposed in the future Internet research arena to address the semantic overload of IP addresses. In this paper the integration of the Social Internet of Things (SIoT) concept into ILS solutions is investigated. Indeed, SIoT has been recently argued as a promising approach to improve the performance of identifier-to-locator mapping procedures. More specifically, we describe the general approach, propose an architecture and show some preliminary performance results obtained through simulations. The proposed SIoT-enabled ILS architecture relies on distributed repositories of virtual counterparts of entities that store Friendship Tables specifically introduced to enable the mapping information to be retrieved by surfing the social graph. Achieved results in a smart campus scenario show that the proposed approach achieves better performance, in terms of number of hops, than a mapping solution based on Distributed Hash Tables (DHT).

Wireless sensor networks (WSNs) are an integral part of an Internet of Things (IoT) ecosystem. In fact, a typical IoT service deployment considers an integrated network of switches and sensors (as well as actuators). In order to manage this heterogeneous network infrastructure, the use of software defined networking (SDN) technologies is anticipated. However, existing SDN-enabling technologies consider only isolated networks and there has been no concrete solution that treats the whole network in a unified way. In this paper, a network operating system is proposed as a way to address the above issue. Starting from the open network operating system, which currently supports only OpenFlow networks, the proposed solution leverages SDN-WISE to integrate WSNs and achieves unified system representation and treatment. The proposed system has been prototyped and is publicly available in open source. Experiments have been executed demonstrating that, by exploiting the proposed solution, it is also possible to improve efficiency of the overall network.

Flow-induced molecular communications are a promising communication paradigm based on the exchange of molecule concentrations in a continuous fluid, guided and directed through microfluidic pipes. An emerging approach to implement this type of communications is based on discrete (or droplet-based) microfluidics. It exploits the idea to represent binary information by encapsulating the signaling molecules inside droplets, which are dispersed in an immiscible fluid and delivered, through micro pipes to the destination. The objective of this paper is to study a binary droplet-based microfluidic system for flow-induced molecular communications from an information theoretical perspective. To this end, we first show that the binary discrete microfluidic channel is characterized by memory and anticipation. Accordingly, we provide a mathematical model based on a finite-state Markov chain. Finally, we evaluate the capacity of the binary droplet-based microfluidic channel.

Several approaches have been considered by research community as possible enablers for the Internet of Things (IoT) implementation. This paper presents the results obtained by testing and comparing three different solutions. In particular, we compare a centralized solution based on software defined network (SDN), called software defined wireless networking (SDWN), with two standard and distributed solutions, that are ZigBee and IPv6 over low-power wireless personal area networks (6LoWPAN). SDWN uses a centralized network layer protocol, where routing policies are defined by an external controller that can be positioned anywhere in the network. The other two solutions are actually the most common protocol stacks for wireless sensor networks, and they both use a distributed routing protocol. The comparison is achieved by experimentations performed on the European Laboratory of Wireless Communications for the Future Internet (EuWIn) platform developed within the network of excellence, NEWCOM#. Results show that SDWN is the best solution in static or quasi-static environments, while the performance degrades in highly dynamic conditions. However, ZigBee has a good reactivity to environmental changes. This paper reports the evaluation of several performance metrics, including packet loss rate, round-trip-time, and overhead generated in the network, under different conditions and considering different kinds of traffic.

In this paper, we propose a solution to support big data processing with MapReduce inside a wireless sensor network (WSN). The proposed framework provides a simple MapReduce interface, whose implementation can be dynamically loaded into the appropriate nodes. The execution of map and reduce functions inside the network is achieved by leveraging software defined networking principles and in particular by enhancing the SDN-WISE protocol on both the Controller and the sensor node sides. On the Controller side, the proposed framework introduces a functionality, which evaluates the optimal deployment of the processing functions in the network taking the typical WSN requirements into account and enforces it by instructing the flow tables to forward traffic from the mappers to the appropriate reducers. Then, on the node side, SDN-WISE is integrated with Contiki, a widely popular operating system for sensor nodes, which has the capability to load and execute new functions without service disruption, i.e., on the fly. The proposed framework is evaluated considering different network topologies and approaches about the data processing location.

This paper introduces μ-NET, a microfluidic LAN that supports the exchange of both digital information and biochemical information carried by droplets moving across molecular processors in a microfluidic chip. The μ-NET can be used to support molecular biology applications like DNA, RNA, and protein biosynthesis. The μ-NET is the first realization of a microfluidic networking paradigm that controls movements of droplets in microfluidic chips by exploiting hydrodynamic phenomena only and builds on recent solutions to achieve communications in the microfluidic domain. The μ-NET integrates techniques to represent addressing information, as well as switching and medium access control solutions. In fact, in μ-NET, the address of the molecular processor where a droplet should be sent to is encoded into the distance between droplets; switching is executed to steer the droplets inside the microfluidic device; medium access control is applied to avoid collisions between droplets that may result in their fusion and, thus, loss of the biochemical information. In this paper, the design of μ-NET is presented in detail, and simulation results validating μ-NET operations are shown.

Summary form only given. All market and technology studies forecast an explosive growth in the number of "things" that will be connected to the Internet. The resulting network is what is commonly known as the "Internet of Things" (IoT). When compared to the traditional Internet, the extremely high complexity of the IoT environments (usually characterized by a huge number of nodes, high heterogeneity of their resources and capabilities, uncertainty on their trustworthiness, etc.) poses new challenges that cannot be faced by even very smart objects singularly.Social behavior is the answer found by several creatures to face the complexity of the surrounding environment. Accordingly, the concept of Social Internet of Things (SIoT) has been recently introduced and is the subject of a rapidly increasing research effort.During the tutorial the introduction of social notions into the IoT will be motivated, the basic concepts of the SIoT paradigm explained, and the existing related research results and industrial experimentations surveyed. Besides, the architecture of a sample SIoT-based platform will be detailed together with some exemplary applications. Reference web site for this tutorial: http://www.social-iot.org.

In this paper SDN-WISE, a software defined networking (SDN) solution for wireless sensor networks, is introduced. Differently from the existing SDN solutions for wireless sensor networks, SDN-WISE is stateful and pursues two objectives: (i) to reduce the amount of information exchanged between sensor nodes and the SDN network controller, and (ii) to make sensor nodes programmable as finite state machines so enabling them to run operations that cannot be supported by stateless solutions. A detailed description of SDN-WISE is provided in this paper. SDN-WISE offers APIs that allow software developers to implement the SDN Controller using the programming language they prefer. This represents a major advantage of SDN-WISE as compared to existing solutions because it increases flexibility and simplicity in network programming. A prototype of SDN-WISE has been implemented and is described in this paper. Such implementation contains the modules that allow a real SDN Controller to manage an OMNeT++ simulated network. Finally, the paper illustrates the results obtained through an experimental testbed which has been developed to evaluate the performance of SDN-WISE in several operating conditions.

Existing social-aware routing protocols for packet switched networks make use of the information about the social structure of the network deduced by state information of nodes (e.g., history of past encounters) to optimize routing. Although these approaches are shown to have superior performance to social-oblivious, stateless routing protocols (BinarySW, Epidemic), the improvement comes at the cost of considerable storage overhead required on the nodes. In this paper we present SANE, the first routing mechanism that combines the advantages of both social-aware and stateless approaches. SANE is based on the observation - that we validate on a real-world trace - that individuals with similar interests tend to meet more often. In SANE, individuals (network members) are characterized by their interest profile, a compact representation of their interests. By implementing a simple routing rule based on interest profile similarity, SANE is free of network state information, thus overcoming the storage capacity problem with existing social-aware approaches. Through thorough experiments, we show the superiority of SANE over existing approaches, both stateful, social-aware and stateless, social-oblivious. We discuss the statelessness of our approach in the supplementary file, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TPDS.2014.2307857, of this manuscript. Our interest-based approach easily enables innovative networking services, such as interest-casting. An interest-casting protocol is also introduced in this paper, and evaluated through experiments based on both real-world and synthetic mobility traces.

The timing channel is a logical communication channel in which information is encoded in the timing between events. Recently, the use of the timing channel has been proposed as a countermeasure to reactive jamming attacks performed by an energy-constrained malicious node. In fact, while a jammer is able to disrupt the information contained in the attacked packets, timing information cannot be jammed, and therefore, timing channels can be exploited to deliver information to the receiver even on a jammed channel. Since the nodes under attack and the jammer have conflicting interests, their interactions can be modeled by means of game theory. Accordingly, in this paper, a game-theoretic model of the interactions between nodes exploiting the timing channel to achieve resilience to jamming attacks and a jammer is derived and analyzed. More specifically, the Nash equilibrium is studied in terms of existence, uniqueness, and convergence under best response dynamics. Furthermore, the case in which the communication nodes set their strategy and the jammer reacts accordingly is modeled and analyzed as a Stackelberg game, by considering both perfect and imperfect knowledge of the jammer's utility function. Extensive numerical results are presented, showing the impact of network parameters on the system performance.

Internet of Things (IoT) applications will be based on the interactions between smart objects. In many applications such interactions are possible (or meaningful) when objects are close to each others, i.e., there is a co-presence. Unfortunately, to date there are no data traces providing information about the copresence of smart objects. Indeed, several mobility traces reporting humans' movements are available, but none of them contains information about the interactions between their objects. Objective of the work reported in this paper is to fill this gap. To this purpose, we start from user mobility patterns available from several datasets. We associate to each user a set of objects, based on a survey we have carried out over around 450 users. Accordingly, we analyze the statistics about the co-presence of objects. We carry out our analysis by exploiting the tools developed for the analysis of complex networks. Our objective is to identify the objects which are likely to play a key role in the interactions between smart objects in the IoT.

A covert channel is a communication channel that creates a capability to transfer information between entities that are not supposed to communicate. A relevant instance of covert channels is represented by timing channels, where information is encoded in timing between events. Timing channels may result very critical in tactical scenarios where even malicious nodes can communicate in an undisclosed way. Jamming is commonly used to disrupt this kind of threatening wireless covert communications. However jamming, to be effective, should guarantee limited energy consumption. In this paper, an analysis of energy-constrained jamming systems used to attack malicious timing channels is presented. Continuous and reactive jamming systems are discussed in terms of their effect on the achievable covert channel capacity and jammer energy consumption. Also, a simple experimental set up is illustrated and used to identify proper operating points where jamming against malicious timing channels is effective while achieving limited energy consumption.

The feasibility of using microfluidic technologies for communication and networking among Labs-On-a-Chip (LoCs), in order to increase reusability, their effectiveness and flexibility, has been already demonstrated in recent works. LoCs are devices, in the size of few centimeters, characterized by μ-scale channels in which small volumes of fluids, either in the form of a continuous stream or of sequences of discrete droplets, move in order to deliver chemical or biological samples to a given destination entity in the microfluidic circuit. They are usually realized through monolithic devices. Samples are processed by passing them through a preset sequence of fixed microfluidic channels. We propose and assess a pure-hydrodynamic switching element in which the path followed by a sample can be controlled through a series of junctions simply modulating the distance between droplets flowing in the microfluidic channel.

Microfluidics deals with manipulation and control of fluids which flow in constrained sub-millimetric media. In this paper communication concepts and networking approaches, typical of telecommunications, are extended to the microfluidic domain. The work illustrated in this paper investigates on possible approaches to information encoding and evaluation of the corresponding channel capacity as well as design of switching solutions. Based on the results of this study, the Hydrodynamic Controlled Microfluidic Network (HCN) paradigm is proposed, which is based on a pure hydrodynamic microfluidic switching function. The HCN paradigm can be applied to interconnect Labs-on-a-Chip (LoCs) in a microfluidic network in which chemical/biological samples are routed between the LoCs by exploiting hydrodynamic effects only. The resulting LoCs are expected to be highly flexible and inexpensive, and thus to become extremely useful in chemical/biological analysis and synthesis.

Multicast is necessary in several wireless multihop communication scenarios. Accordingly, it has received a lot of attention in the past, and several multicast protocols have been proposed. Nevertheless, traditional solutions typically incur poor efficiency when there is a large number of nodes, topology changes occur frequently, and/or the traffic load is low. Geographic multicast has been recently exploited to solve the problems mentioned above. However, these solutions require exchange of topology information that, again, can lead to excessive overhead. In this paper, we propose a new geographic multicast protocol denoted as GEM, which is inspired by the Euclidean Steiner Tree (EST) theory and does not require any information exchange for routing purposes. Therefore, it is very efficient and scalable in wireless networking scenarios where other schemes achieve low performance, especially in terms of energy consumption. In this paper, we also derive some key properties of GEM that allow us to characterize the protocol performance. As a major contribution, we show that these properties are quite general and apply to a wide range of algorithms inspired by the EST. Simulation results assess the derived properties and confirm the effectiveness of the proposed GEM scheme.

In the recent past several network scenarios have emerged where transmit-only nodes - i.e., nodes without receiving capabilities - are deployed. Such nodes cannot perform carrier sensing and cannot be synchronized. Therefore, they have to apply an Aloha-like medium access control. However, it is well known that Aloha achieves low goodput due to the possibility to incur in collisions, and this results in poor energy efficiency too. In order to achieve better performance, in this paper a scheme called Timing-Channel Aloha (TC-Aloha) is introduced which exploits the timing channel. The timing channel is the logical communication channel established between a transmitter and a receiver in which the information is transferred by means of the timing of events. Another feature of TC-Aloha is that it enables multiple transmissions of the same information to improve the communication reliability. In this paper the TC-Aloha scheme is described in detail and an analytical framework is derived for the evaluation of its performance. The numerical results assess the advantages of TC-Aloha over traditional solutions.

Intra-body sensor networks can radically change the approach to personal health control and care. However, they still need several research issues to be solved. One major issue is related to the need for minimizing the transmitted energy in order to both increase battery duration and reduce heating of biological tissues which may raise health concerns. In this paper a scheme named Intra-Body Transmission Protocol (IB-TxP) is introduced which achieves reduction in the transmitted energy by exploiting the so-called timing channel approach. This is based on establishing a logical channel between a sender and a receiver in which information is transferred in the timing between transmissions. Accordingly, part of the information is encoded in the timing between events, so lowering energy consumption and tissues heating associated to the real bits transmission. An analytical framework is derived for the assessment of IB-TxP and its comparison to traditional transmission schemes. Numerical results show the effectiveness of IB-TxP.

Information-centric networking (ICN) is a new networking paradigm which is attracting increasing attention from the scientific community. ICN focuses on content handling and distribution rather than host-to-host communications. Satellite systems have always played a key role in content distribution and therefore, they are expected to be fundamental components of the information-centric networking. However, it is not obvious whether solutions that are being developed for terrestrial ICNs are effective in satellite scenarios as well. More specifically, focus of this paper is on in-network content caching, which is an important feature characterizing all ICN proposals but, as we will show, should be re-designed to address the specific characteristics of satellite networks. Indeed, in this paper a novel caching scheme named SatCache is proposed which exploits the broadcast nature of satellite communication media and creates a profile of the preferences of network users in order to estimate their potential interest in a given content. Simulation results given in the paper show the effectiveness of the proposed scheme.

Microfluidics refers to manipulation and control of little amount of fluids flowing into channels of micro-scale size and is the basic technology utilized by Labs-on-a-Chip (LoC) systems. In the recent past researchers have analyzed the possibility to support information exchange between different elements of a LoC. However, support of communication in microfluidic systems relies on the use of appropriate information coding strategies and deep knowledge of channel propagation characteristics. Accordingly, in this paper we compare two different schemes for information coding and evaluate the corresponding capacities depending on the characteristics of the fluids utilized. Furthermore, we discuss how such encoding schemes can be integrated in networking solutions for LoCs.

The Information-Centric Networking (ICN) paradigm is expected to be one of the major innovation of the Future Internet An ICN can be characterized by some key components like: (i) the content-centric request/reply paradigm for data distribution, (ii) route-by-name operations, and (iii) in-network caching. In this paper we focus on a framework for ICN called CONET (COntent NETwork) and in particular on a solution devised under this framework called coCONET. coCONET characteristics make it suitable for deployment in accordance to the Software Defined Networks (SDN) philosophy. In this paper, we will describe how coCONET can be implemented over an OpenFlow (the most popular SDN instantiation, to date) network and how OpenFlow should be modified to better suit the operations of coCONET and, more in general, of ICN solutions.

The integration of social networking concepts into the Internet of Things (IoT) has led to the so called Social Internet of Things (SIoT) paradigm, according to which the objects are capable of establishing social relationships in an autonomous way with respect to their owners. The benefits are those of improving scalability in information/service discovery when the SIoT is made of huge numbers of heterogeneous nodes, similarly to what happens with social networks among humans. In this paper we focus on the problem of understanding how the information provided by the other members of the SIoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define a subjective model for the management of trustworthiness which builds upon the solutions proposed for P2P networks. Each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the common friends with the potential service providers. We employ a feedback system and we combine the credibility and centrality of the nodes to evaluate the trust level. Preliminary simulations show the benefits of the proposed model towards the isolation of almost any malicious node in the network.

The network-centric warfare concept pursues information superiority as the key strategic advantage. However, information can have a different strategic value depending on its criticality and, thus, communication systems should provide higher priority to critical data. In this paper, performance of different approaches to achieve such differentiation in TDMA satellite-based tactical communication systems are provided. More specifically, we will evaluate the impact of the correlation between the criticality level of information sources that are in proximity to each other. To this purpose, a Markovian model of the process modeling the criticality level dynamics of information sources belonging to the same group is defined and implemented in the ns-2 simulation environment. Simulation results demonstrate that the correlation between the criticality level of information sources in proximity to each other significantly impact the performance of the communication system.

In this paper we describe SANE, the first forwarding mechanism that combines the advantages of both social-aware and stateless approaches in pocket switched network routing. SANE is based on the observation“that we validate on real-world traces”that individuals with similar interests tend to meet more often. In our approach, individuals (network members) are characterized by their interest profile, a compact representation of their interests. Through extensive experiments, we show the superiority of social-aware, stateless forwarding over existing stateful, social-aware and stateless, social-oblivious forwarding. An important byproduct of our interest-based approach is that it easily enables innovative routing primitives, such as interest-casting. An interest-casting protocol is also described, and extensively evaluated through experiments based on both real-world and synthetic mobility traces.

The incessant decrease in size, cost, and energy consumption of wireless devices is likely to boost the number of wireless devices dramatically. These will be deployed in several real world objects that we use in our daily life as envisioned by the Internet of Things (IoT) concept. Designing effective and efficient objects' location update and search mechanisms, is very important but is extremely difficult in the IoT scenarios. In fact, the number of mobile objects composing the IoT will be huge; this implies that signaling traffic generated for location update and discovery purposes can explode. Also, objects might currently be located where positioning solutions are not available or are not accurate enough to support most of the envisioned added value IoT applications. In this paper it is studied how object group mobility can be exploited to achieve accurate location update and search in the IoT, while reducing the signaling overhead. Object group mobility is a phenomenon that naturally emerges as usually moving objects are carried by a human or a vehicle together with several other objects. In this paper i) the concept of object group mobility is introduced and it is explained how and to which extent this can be used to reduce signaling overhead and improve accuracy in object location information; ii) the concept of collective-agent is introduced to further decrease signaling overhead in the IoT scenarios where object group mobility emerges, iii) an analytical framework is derived to assess the advantages of exploiting object group mobility in IoT scenarios.

The timing channel is the logical communication link established between a sender and a receiver in which flowing information is encoded in the timing between events. Accordingly, information can be transferred by means of the transmitted packets, but also through the time interval between such transmissions, and the size of the packets. In wired networks approaches using the timing channel can lead to a small increase in the overall communication capacity. In wireless networks with strict power constraints, instead, these can lead to significant energy efficiency improvements. In fact, part of the information (that encoded in the time interval between transmissions and in the size of the packets) is transferred without its actual transmission. In this paper a methodology is introduced which allows exploitation of the timing channel in wireless networks and an analytical framework is derived for its assessment in case of one-to-one, many-to-one, and one-to-many communications. Numerical results show that the proposed approach increases energy efficiency significantly, especially, when available energy is particularly scarce and precious.

Infostation communication is an innovative communication paradigm thought to provide connectivity in isolated areas. In infostation communications, wireless ports are deployed to act as gateways between the remote users and the communication infrastructure. However, users are allowed to exchange data with the infrastructure only when in the coverage area of one of them. In order to provide further connectivity to remote users far away from infostations, mobile nodes are assumed to be used to collect data at remote users not in the range of the infostations and, then, upload this data when they come into proximity of the infostation. In order for this process to be successful, the system stability conditions should be identified. More in depth, we denote collection process the process representing the data packets collected by the mobile node in the time between two consecutive visits of infostations and upload process the process representing the number of data packets delivered by the mobile node to the infostation. In this paper we derive conditions when the average of the upload process is higher than the average of the collection process. To this purpose a diffusion approach inherited from physics is presented and design guidelines for stable system design are identified.

In this paper an analytical framework is introduced for the optimization of TCP performance through joint channel coding and transmission power management in satellite communications, where both energy and bandwidth are scarce and costly resources. More specifically, the analysis takes into account the use of Low-Density Parity-Check (LDPC) codes as coding scheme for high data rate satellite communications. The analytical framework allows for the evaluation of the transmission power and coding rate that maximize the TCP throughput per unitary cost, which is a metric defined in terms of energy cost and bandwidth cost when related to throughput. Numerical examples demonstrate the usability of the proposed framework.

The five articles in this special section focus on multimedia applications in mobile/wireless context. Two papers focus on video transmission over 802.11a/b and WiMax, the next discusses a visual sensor network in wireless environments, and the last two propose supporting technologies for two mobile applications that rely on multimedia interactions.

We study routing for massively dense wireless networks, i.e., wireless networks that contain so many nodes that, in addition to their usual microscopic description, a novel macroscopic description becomes possible. The macroscopic description is not detailed, but nevertheless contains enough information to permit a meaningful study and performance optimization of the network. Within this context, we continue and significantly expand previous work on the analogy between optimal routing and the propagation of light according to the laws of Geometrical Optics. Firstly, we pose the analogy in a more general framework than previously, notably showing how the eikonal equation, which is the central equation of Geometrical Optics, also appears in the networking context. Secondly, we develop a methodology for calculating the cost function, which is the function describing the network at the macroscopic level. We apply this methodology for two important types of networks: bandwidth limited and energy limited.

The timing channel is the logical communication link established between a sender and a receiver in which the information flowing is encoded in the timing between events. Accordingly, information can be transferred by means of the transmitted packets, the time interval between such transmissions, and the size of the packets. In wired networks approaches using the timing channel can lead to a small increase in the overall communication capacity. In wireless networks with strict power constraints, instead, these can lead to significant performance improvements. In this paper attention is focused on power-constrained satellite networks where there is a large amount of bandwidth which cannot be used because the power required for operations executed on-board the satellite is much higher than what is available. In such scenarios the use of the timing channel can significantly improve the overall capacity of the system. In this paper a methodology is introduced which allows exploitation of the timing channel in power-constrained satellite networks and an analytical framework is derived for its assessment. Numerical results show that the proposed approach can achieve much higher capacity than what can be theoretically achieved without using the timing channel.

Recently trajectory based forwarding (TBF) has been proposed for dense wireless multihop networks. However, no strategies have been proposed so far for the minimization of the communication energy cost. In this paper a framework is proposed for the evaluation of the optimal route in wireless multihop networks which exploits analogies with geometrical optics. In the proposed framework a communication cost function is defined which represents the communication cost in each point of the deployment area. Such function has been calculated using the node density function. Accordingly, the proposed framework requires the density of nodes in the network to be known a priori. The proposed framework has been used in a relevant scenario. Finally, several ideas for future research are presented.

In a delay-tolerant sensor network where the sink is mobile, a node can conveniently hold an information packet until the sink comes closer. This allows to both decrease the number of wireless hops required to deliver the information to the sink and reduce energy consumption. Thus, mobility of nodes can be exploited to increase energy efficiency in sensor networks. However, a major drawback of the above policy is that it causes delay which may be not acceptable for the application. In this paper a trade-off between energy efficiency and delay is investigated. More specifically, an analytical framework which allows to evaluate the expected delivery cost with respect to the maximum delay acceptable for the application is derived and assessed by comparison with simulation results. Numerical results show that the analytical framework is very accurate and, as expected, accuracy increases as the density of nodes in the network increases.

TCP has serious performance problems when wireless links are involved in the end-to-end connection because of the high bit error rate typical of the wireless medium. Joint power management and error correction can improve the link reliability and increase the throughput performance. In this paper, the tradeoff between power management and error correction is investigated. To this end, an analytical framework aimed at maximizing the throughput per unitary cost, defined as the ratio between the TCP throughput and a cost function, is introduced. The proposed analytical framework is general and some significant results have been derived which do not depend on the specific wireless system and do not rely on any TCP throughput approximation formula. The benefits of joint power management and error control are demonstrated in several relevant case studies. The accuracy of the proposed analytical framework is assessed through ns-2 simulation

Sensor networks are characterized by limited battery supplies. Due to this feature, communication protocols specifically designed for these networks should be aimed at minimizing energy consumption. To this purpose, the sensor's capability of transmitting with different power levels can be exploited. With this in mind, in this paper an integrated MAC/routing protocol, called MACRO, which exploits the capability of sensor devices to tune their transmission power is introduced. The proposed protocol requires that each node only knows its own coordinates and the coordinates of the destination, but does not require any exchange of location information. In order to select the next relay node, a competition is triggered at each hop, so that the most energy efficient relay node is chosen. This is achieved through maximization of a newly introduced parameter, called weighted progress factor, which represents the progress towards the destination per unit of transmitted power. To this aim, an analytical framework which guarantees that MACRO performs the best choice is derived. MACRO performance is evaluated through ns-2 simulation and compared to other relevant routing schemes. Performance results show that the proposed protocol outperforms other solutions in terms of energy efficiency and boosts data aggregation.

Adaptive rate video encoding is required to maximize efficiency when wireless links are involved in the communication. In fact, wireless channels are characterized by high, time-varying bit error rates. To cope efficiently with this problem adaptive forward error correction schemes have been proposed. These schemes introduce an amount of redundancy dependent on the channel conditions. Accordingly, the bandwidth available at the application layer changes: it increases when channel conditions improve, and decreases when channel conditions worsen. Obviously, the encoding parameters must be tuned to adapt the video source transmission rate to the available bandwidth. This adaptation is achieved by means of appropriate feedback laws, which are relationships between the encoding parameters to be used and other variables representing the state of the system. An analytical framework is introduced which can be used for the design of the feedback laws. To this purpose both the channel and the video source are modeled by means of Markov models. The resulting model of the whole system is denoted as SBBP/SBBP/1/K. Analysis is derived which allows to evaluate the most significant performance measures and, therefore, to design optimal feedback laws.

Currently there is no control for real-time traffic sources in IP networks. This is a serious problem because real-time traffic can not only congest the network but can also cause unfairness and starvation of TCP traffic. However, it is not possible to apply current solutions for Internet to the networks with high bandwidth-delay products and high bit error rates. The channel errors may result in inaccurate congestion control decisions and unnecessary rate throttles leading to severe performance degradation. This problem is amplified in the links with high bandwidth-delay products, since the link is inefficiently utilized for a very long time until the unnecessary rate throttle is recovered. In this paper, a new Rate Control Scheme, RCS, is introduced for real-time interactive applications in networks with high bandwidth-delay products and high bit error rates. RCS is based on the concept of using dummy packets to probe the availability of network resources. Dummy packets are treated as low priority packets and consequently they do not affect the throughput of actual data traffic. Therefore, RCS requires all the routers in the connection path to support some priority policy. A new algorithm is also proposed to improve the robustness of the RCS to temporal signal loss conditions. The delay-bound considerations for real-time traffic sources using RCS rate control scheme are also investigated. Simulation experiments show that in environments with high bandwidth-delay products and high bit error rates, RCS achieves high throughput performance without penalizing TCP connections.

Wireless channels are characterized by high time-varying bit-error rates (BERs). To cope with this problem, several adaptive forward-error-correction (AFEC) schemes have been proposed in the literature. They work locally at the wireless link, adding a variable amount of redundancy to the transmitted data in order to maintain the packet error rate below an acceptable level. However, when such schemes are utilized, the bandwidth offered to the applications changes when channel conditions change. In this paper, the effects of these bandwidth variations are investigated in the case of real-time Motion Picture Experts Group (MPEG) video transmission. The MPEG encoder is controlled in order to adapt its emission rate to the current bandwidth offered by the wireless link. To this end, the encoding quality is diminished by the source rate controller when the transmission rate has to be decreased due to an increase in the channel BER, whereas it is improved when the transmission rate can be increased due to a decrease in the channel BER. A Markov-based model, denoted as SBBP/SBBP/1/K, has been introduced to model the scenario being considered. The analytical framework allows evaluation of the performance of the system and can be used to optimize the design of a video transmission system for wireless channels, providing the instruments to derive the tradeoff between information corruption in the wireless channel and MPEG video encoding quality.

It is well known that TCP is unfair when connections with different round trip times share the same bottleneck. In the literature TCP fairness in wired networks has been widely studied but little effort has been devoted to this issue in wireless networks where new problems arise. Objective of this paper is investigating on the possibility of achieving TCP fairness through power management in wireless CDMA networks. The basic idea is to allow long round trip time connections, which are usually the most disadvantaged, to have higher signal-to-interference ratio levels. An analytical framework is introduced to calculate, for each mobile terminal, the appropriate transmission power giving fairness. The impact of such power management scheme on fairness and overall throughput performance is evaluated by means of both analysis and simulation.

Ad hoc networking enables novel communication paradigms which require the definition of new frameworks and parameters for quality of service (QoS) support. The relevant QoS requirements are frequently antagonist and thus also appropriate tradeoff have to be determined and achieved to fit all of them. As an example, consider the spontaneous networking featured by self-organizing ad hoc networks. Spontaneous networking can happen only if neighboring communication nodes discover each other within a short period of time; however, velocity of discovery is paid in terms of energy consumption. In this paper we consider the tradeoff between energy efficiency and responsiveness in the discovery process. More specifically, our objective is to achieve the highest velocity in the discovery process, given that the energy consumption is lower than a certain threshold, or to minimize the energy consumption given that specific requirements in terms of the discovery velocity are satisfied.

Ad hoc networking enables novel communication paradigms which require the definition of new quality-of-service (QoS) parameters and frameworks for QoS support. The relevant QoS requirements are frequently antagonist and, consequently, an appropriate tradeoff has to be determined and achieved to fit all of them. As an example, the spontaneous networking featured by self-organizing ad hoc networks is possible only if neighboring communication nodes discover each other within a short period of time; however, velocity of discovery is paid in terms of energy consumption. In this paper, an analytical framework is derived which allows an evaluation of the tradeoff between energy efficiency and responsiveness in the discovery process. More specifically, the analytical framework allows either to achieve the highest velocity in the discovery process, given that the energy consumption is lower than a certain threshold, or to minimize the energy consumption given that specific requirements in terms of the discovery velocity are satisfied. The analytical framework is applied to significant case studies to derive design implications on neighbor discovery algorithms.

This paper presents a performance enhancing transport architecture for the satellite environment. This solution improves the network transport performance by overcoming the limits imposed by a transmission control protocol/Internet protocol (TCP/IP)-based stack suite, while maintaining the interfaces offered by it. This is an important issue since TCP/IP is widely used and most of the applications are based on it. The work starts from the state-of-the-art about the transport layer over satellite by distinguishing two alternative frameworks: the black box (BB) and the complete knowledge (CK) approaches. In the former, the network is considered as a "black box" and only modifications in the terminal tools are permitted. In the latter, the complete control of any network element is allowed so as a performance optimization procedure is possible. The proposed architecture [called Performance Enhancing Transport Architecture (PETRA)] is designed in all details using the second approach. PETRA uses network elements, called relay entities, to isolate the satellite portions in case of heterogeneous networks, while a transport layer protocol stack is used to optimize the transport of information over satellite links. A special satellite transport protocol, that is part of the transport layer protocol stack, is used over such links to perform error recovery. Simulation results show that the proposed framework significantly enhances throughput performance.

Given their broadcast nature, satellite communications are one natural engineering choice for multicast service deployment. In this paper, the throughput performance of transmission control protocol (TCP)-like multicast congestion control is analyzed in hybrid terrestrial/satellite networks. With this objective, an analytical framework based on Markov chains is introduced. The major advantage of the proposed analytical model is its scalability in that the number of states of the Markov chain modeling the system is independent of the number of receivers in the multicast session. This is a very important feature as simulation is unfeasible for large numbers of receivers. The framework is used to evaluate the impact of the long propagation delays, high bit-error rates, and channel asymmetry characterizing hybrid terrestrial/satellite communications. The performance results show that in certain cases, it is more convenient to divide the receivers in an appropriate number of groups and establish a different multicast session toward each of the above groups. Also, the convenience of an acknowledgment (ACK) flow reconstructor is shown.

In this paper, a hierarchical paradigm modeling both the intramedia and intermedia time relationships of multimedia sources is derived. Each multimedia source is considered as being made up of a master monomedia source, which is independent, and slave monomedia sources, which are dependent on the master. The paradigm takes different timescale statistics into account and is used to characterize intermedia relationships in terms of the second-order statistics of the multimedia source. Finally, the impact of intermedia relationships on the performance of each monomedia source making up a multimedia source is analyzed when a number of multimedia sources are multiplexed together. The error introduced in both loss and jitter performance analysis when intermedia relationships are not modeled is evaluated through a case study. Numerical results show that this error may be dramatically significant in many common scenarios.

This paper demonstrates that higher network resource efficiency can be achieved by using resource management protocols which consider service disciplines based on service curves together with statistical traffic modeling. To this end, an appropriate analytical framework is introduced which allows calculation of the performance statistically guaranteed to any flow out of an aggregate. This feature enables the analytical framework to be applied to the elements of the core network where aggregates of traffic are considered instead of single flows in order to avoid scalability problems. Given that flows are modeled in the analytical framework through switched batch Bernoulli processes (SBBPs), the whole queueing system is denoted as SBBP/Sc/1/K. The performance is calculated in terms of loss probability and delay distribution. The proposed framework is applied in a significant multinode case study.

To provide IP mobility for wireless users several micro-mobility protocols are currently available. These are capable for supporting this feature inside the scope of a LAN, by means of performing handovers between adjacent WiFi radio-access cells in order to follow users' movements. Also, it is possible to achieve wireless mobility in a larger extent, i.e. across whole network domains. But, in order to do it these protocols have to be used in conjunction with a macro-mobility protocol, like mobile IP. In this context, a problem arises if such domains are so far away from each other that wireless-access gaps exist between them. In fact, this prevents wireless IP users from experiencing access continuity while traveling across these domains. In this paper we describe a solution, which was designed and implemented to cope with the above problem. Starting from the cellular IP protocol, we developed a new mobility framework that extends it to seamlessly manage roaming into the GPRS access network, whenever the mobile host is out of range from any WiFi domain. Also, management of inter-domain macro-mobility is integrated in our framework, eliminating the need to externally rely on mobile IP.

It is well known that TCP has performance problems when wireless links are involved in the end-to-end connection. This is due to the high bit error rate characterizing wireless links. Appropriate power management and error correction can improve the link reliability observed by TCP and increase the throughput performance accordingly. In the literature, the effects of transmission power and error correction capability on TCP performance have been considered separately, so far. We study the tradeoff between power management and error correction. To this end, an analytical framework to maximize a user satisfaction function, defined as the ratio between the TCP throughput and a cost function, is introduced. The proposed analytical framework does not depend on the specific wireless system and does not rely on any TCP throughput approximation formula. The benefits of joint power management and error control are demonstrated in several relevant case studies.

Seamless mobility is a requirement whose importance for Internet users nowadays is growing faster than ever Thus many solutions to manage wireless IP mobile access and inter-working with the fixed Internet are already available and more are currently being studied and improved In this paper we described an actual wireless mobility framework we designed and implemented in our university campus, which is spread over a wide metropolitan area. The aim is to let a mobile host, that is a user equipped i.e. with a PDA device, experience real wireless IP mobility while moving on a large spatial scale, by means of a middleware that leverages from three main wireless access technologies: Bluetooth, WiFi and GPRS. In our framework, these are managed as a hierarch), of spatially overlapping access domains. While the user is on the move, the client-side of the middleware running on our mobile PDA device triggers smart switchings between the currently best available and more appropriate wireless access path, based on locally collected information. On the other hand, the network-side part of the middleware manages mobile host location paging and routing-update functions inside the whole campus area with an approach which extends from the Cellular IP micromobility protocol. We call this approach WiFi bridge since it also adds mobile hosts with the capability to seamlessly travel between disjunct WiFi access domains inside the campus by means of a temporary relay onto the GPRS access domain. We implemented and tested the system in a real testbed using IPaq devices running Linux, obtaining encouraging experimental results.

TCP-Peach has been proposed for IP network scenarios characterized by long round trip times and high bit error rates, such as satellite networks. In the TCP-Peach congestion control scheme, Slow Start and Fast Recovery are replaced with new algorithms called Sudden Start and Rapid Recovery. In this paper protocol refinements for TCP-Peach are proposed to allow it to be utilized in cooperation with FACK/SACK options. The modified protocol has been implemented in the Linux 2.2.17 kernel and its performance has been evaluated in an emulated satellite network environment. Performance results show that the modified TCP-Peach protocol outperforms other TCP implementations.

Currently there is no control for real-time traffic sources in IP networks. This is a serious problem because real-time traffic can not only congest the network but can also cause unfairness and starvation of TCP traffic. A new rate control scheme, RCS, is introduced for real-time traffic in networks with high bandwidth-delay products and high bit error rates. RCS is based on the concept of using dummy packets to probe the availability of network resources. Dummy packets are treated as low priority packets and consequently they do not affect the throughput of actual data traffic. Therefore, RCS requires all the routers in the connection path to support some priority policy. Simulation experiments show that in environments with high bandwidth-delay products and high bit error rates, RCS achieves good throughput performance without penalizing TCP connections.

Guarantees of quality-of-service (QoS) in the real-time transmission of stored video on the Internet is a challenging task for the success of many video on demand (VoD) applications. Two QoS classes have been specified by the IETF Integrated Services (intserv) Working Group: Guaranteed Services and Controlled-Load Services. For both of them, it is necessary to provide traffic sources with the capability of calculating the traffic characteristics to be declared to the network, Tspec, on the basis of a limited set of parameters statistically characterizing the traffic and the required level of QoS. The target of this paper is to develop an algorithm for the evaluation of the Tspec parameters which characterize the video stream when a given QoS is required. To this end an analytical framework modeling an MPEG stored-video server and the access network node is introduced. The video emission process is modeled with a switched batch Bernoulli process (SBBP), and performance in the video-server smoother is analytically evaluated. Then the token bucket at the network access point, loaded by the output traffic of the video-server smoother, is modeled to calculate the probability of marking nonconforming data packets.

Current TCP protocols have lower throughput performance in satellite networks mainly due to the effects of long propagation delays and high link error rates. In this paper, a new congestion control scheme called TCP-Peach is introduced for satellite networks. TCP-Peach is composed of two new algorithms, namely Sudden Start and Rapid Recovery, as well as the two traditional TCP algorithms, Congestion Avoidance and Fast Retransmit. The new algorithms are based on the novel concept of using dummy segments to probe the availability of network resources without carrying any new information to the sender. Dummy segments are treated as low-priority segments and accordingly they do not effect the delivery of actual data traffic. Simulation experiments show that TCP-Peach outperforms other TCP schemes for satellite networks in terms of goodput. It also provides a fair share of network resources.

Design of network devices requires accurate models for network traffic. The main difficulty lies in determination of the traffic statistics which effectively influence the network performance, and in construction of a tractable and easy analytical model capturing these statistics. This paper demonstrates that, in order to evaluate performance of a multiplexer in a discrete-time environment, it is necessary to define a model which is able to capture the probability density function, autocovariance function, and the overload probability of the input traffic, simultaneously. The paper also provide an algorithm for the construction of an SBBP model matching these statistics.

The "new Internet" will allow individual application sessions to request different QoS parameters to the network. Two QoS classes have been specified by the IETF: guaranteed services and controlled-load services. For both of them, it is necessary to provide users with the capability of calculating the traffic characteristics, Tspec, to be declared to the network, on the basis of a limited set of parameters statistically characterizing the data source and the required level of QoS. The target of this paper is to realize an analytical framework modeling the source and the access network nodes, with the purpose of calculating the Tspec parameters for MPEG video traffic. To this end the video source is modeled with a switched batch Bernoulli process (SBBP), and performance in the source smoother is analytically evaluated. Then the token bucket at the network access point, loaded by the output traffic of the smoother, is modeled to calculate the probability of marking nonconforming data packets.

The enormous increase in wireless communications has led to the need to configure wireless access networks with cellular structures based on the use of micro- and picocells. A key issue in connection with this is the rerouting of the data flow directed to a user making a handover. The paper considers one of the most widely-used connectionless protocols, the signaling network layer (SNL), which is based on a tree-structured routing architecture. Through an analytical model based on a queueing network, its performance is analyzed in terms of the distribution of the rerouting delay. The proposed model is then applied to a case study to demonstrate its versatility and manageability and to get important insights to the dimensioning of the routing architecture.

One of the most important quality-of-service parameters in a multimedia environment is skew, defined as the difference between the delays suffered by the monomedia flows belonging to the same multimedia stream. An analytical paradigm is proposed to evaluate the skew affecting a multimedia traffic stream in an asynchronous transfer mode multiplexer. For this purpose, the emission process of each multimedia source loading the multiplexer is defined as the superposition of heterogeneous correlated emission processes, each of which models one monomedia source as a switched batch Bernoulli process (SBBP). In order to model the intermedia relationships, the transition probabilities in the Markov chain underlying each SBBP are functions of the state of the other monomedia sources. The model is applied to a case study and the dependence of skew performance on some of the source characteristics, such as intermedia correlation, and some of the environment characteristics, such as buffer size, output capacity, and buffer utilization is analyzed and discussed.

Thanks to the ever growing diffusion of distributed multimedia applications, VBR compressed video traffic is expected to constitute the majority of the B-ISDN load in the immediate future. At the moment, the MPEG coding scheme is widely used for many types of applications. Therefore, it is crucial to obtain a model for the generation of sequences with the same statistical characteristics of real MPEG traces. In this paper, after demonstrating that intra-GoP (group of pictures) correlation has to be taken into account, an accurate model allowing the generation of an MPEG-like trace is proposed. Moreover, as the MPEG traffic has been demonstrated to be self-similar, the proposed algorithm allows one to generate a trace, fitting the short-range dependence (SRD) and long-range dependence (LRD) behavior and the probability density function of any given MPEG sequence.

Flow theory is a rich, effective theory introduced in order to study real-time network protocols. It is based on discrete mathematics in which a flow of data is represented by an infinite sequence of numbers and is characterized by its upper bounds. Unfortunately up to now flow theory has used a traffic characterization that in some cases can be too loose, thus causing an inefficient network utilization. In this paper we enhance flow theory by providing it with a more accurate traffic characterization and with all the tools necessary to deal with it. As we will see, this enhancement provide a more accurate performance evaluation and thus better network utilization.

An accurate and treatable Markov-based model for MPEG video traffic is proposed. Before reaching a definition of the model, a large number of MPEG video sequences are analyzed and their statistical characteristics are highlighted. Besides the well-known autocorrelation function, testifying the pseudo-periodicity of the sequence in the short term, and the gamma-shaped probability density function the correlation between different frames belonging to the same group of pictures (GOP) is also accurately studied. Then a structured model is proposed. Thanks to its two-level structure it is able to capture both the inter-GOP and the intra-GOP correlation. In order to obtain the first level of the model, the well-known inverse eigenvalue problem is solved in the discrete-time domain. Finally, the model is used to evaluate the loss probability in an ATM multiplexer loaded by an MPEG video source and an aggregate of external traffic. The accuracy of the model is evaluated by comparing the analytically obtained loss probability with the loss probability calculated by simulating the system using real traffic sequences as driven traces.