Trusting autonomous, connected vehicles is necessary to build Cooperative Driving applications and enhance Smart Mobility. A necessary step is full confidence in communications beyond identification, pseudonyms and certificates: Message validity must be unquestionable to enable cooperation, even when messages originate from trusted entities affected by faults or malfunctions. Extreme reliability requires multiple evaluation tools, as independent as they can be, to fuse estimation into a dependable decision. This work proposes to combine two methods of evaluating messages, one based on Artificial Intelligence (AI) analysis and one on physical coherence of message content, achieving extremely good performance both on the VeReMi dataset, and in run-time execution in a highway scenario simulated with Plexe . Moreover, the paper proposes a simple protocol demonstrating how to safely dismantle a platoon of Cooperative Driving vehicles returning to autonomous (or human) driving when misbehaving messages are received.

Wi-Fi sensing based on Channel State Information (CSI) has witnessed considerable research activity in recent years. However, a critical literature analysis reveals that only a limited amount of proposals are potentially reproducible, with many works lacking essential experimental details, publicly available datasets, or accessible analysis code. This may impede the research progress and the subsequent transition of promising findings into practical applications. The objective of this work is to identify CSI-based sensing proposals that are potentially reproducible based on the published information. Our goal is to provide a focused review of resources that can serve as a concrete starting point for researchers and practitioners seeking to experiment with and advance the field of Wi-Fi sensing. We perform a comprehensive analysis of publicly available datasets (encompassing both the collection methodologies and the environmental characteristics) and existing sensing models, accompanied by their code, pre-processing steps, and evaluation procedures. Finally, we discuss what are the minimum requirements for truly verifiable contributions in this field, and outline the best practices for creating and sharing reproducible CSI-based sensing datasets and models.

Channel state information (CSI) is widely used for joint communication and sensing in sub-6 GHz wireless networks, but its application at mmWave frequencies remains under-explored. This work applies a quantized amplitude-based CSI similarity metric to data from a 28 GHz indoor testbed, showing the feasibility of CSI-based ambient sensing in next-generation wireless networks.

Wireless sensing based on Channel State Information (CSI) is rapidly spreading with the advent of 6G and newer Wi-Fi versions. Today, the CSI is regarded as one of the most promising elements for boosting service innovation on indoor device-free sensing. In addition, the wide adoption of the latest IEEE 802.11be standard, commonly known as Wi-Fi 7, might open up new possibilities for Wi-Fi sensing applications with even larger bandwidths, up to 320 MHz, and 4096 sub-carriers per spatial stream. However, researchers have still limited access to CSI extraction tools for such systems. In this work, we devise a framework based on software-defined radios to investigate the potential implications of the new Wi-Fi features, namely the wider channels and the higher number of sub-carriers, on a device-free positioning system based on position fingerprinting. In particular, we analyze the impact and the performance variations of this new technology across different bands in a position classification system, which has proven to be very accurate with previous versions of Wi-Fi. Our preliminary findings set some clear guidelines to direct future research efforts towards a better usage of newer Wi-Fi channels for sensing purposes. Furthermore, we publicly release our framework to the community of researchers and engineers for developing better Wi-Fi sensing solutions for smart homes, health care, and Internet-of- Things applications in general.

Channel State Information (CSI) sensing is now an established element of Integrated Sensing and Communication (ISAC) operations, but what is its real potential, and what are its limits? The literature focused more on sophisticated AI systems to exploit CSI variations imposed by different propagation scenarios, indeed achieving amazing results, but few, if any works tackled the topic of characterizing the long-term CSI behavior, its stability, and its stochastic properties to achieve insight in the potential and limits of CSI sensing. This work presents a first attempt in this direction, providing a framework that allows the comparison of CSIs quantifying the difference between CSI collected in different scenarios and showing that a quantitative analysis of the CSI is possible, and it can also help to explain the accuracy difference observed between distinct experiments with a CNN-based localization method taken from the literature.

Cooperative Driving requires ultra-reliable communications, and it is now clear that no single technology will ever be able to satisfy such stringent requirements, if only because active jamming can kill (almost) any wireless technology. Cooperative driving with multiple communication technologies which complement each other opens new spaces for research and development, but also poses several challenges. The work we present tackles the fallback and recovery mechanisms that the longitudinal controlling system of a platoon of vehicles can implement as a distributed system with multiple communication interfaces. We present a protocol and procedure to correctly compute the safe transition between different controlling algorithms, down to autonomous (or manual) driving when no communication is possible. To empower the study, we also develop a new version ofPlexe, which is an integral part of this contribution as the only Open Source, free simulation tool that enables the study of such systems with a modular approach, and that we deem offers the community the possibility of boosting research in this field. The results we present demonstrate the feasibility of safe fallback, but also highlight that such complex systems require careful design choices, as naïve approaches can lead to instabilities or even collisions, and that such design can only be done with appropriate in-silico experiments.

The use of ultra high frequencies in 5G and future networks to improve transmission speeds and capacity requires that users’ equipment remain in Line of Sight with the access antennas most of the service time. This requirement implies a change in perspective to plan the coverage: Antennas cannot be placed on roofs or remote antenna sites, and a robust coverage is based on multi-antenna visibility from any point. This paper tackles the problem of public street coverage in urban areas with a data-driven methodology. Starting from 3D digital maps, we formalize the problem of antenna placement as a set coverage problem and leverage powerful heuristics to implement a general algorithm that allows the exploration of different policies, returning the detailed coverage, the antenna placement, and the cost of the coverage. Results on 15 areas in 3 Italian cities show the properties of different policies and confirm for the first time on large scale real data the feasibility of Line of Sight communications with a sustainable number of antennas per km2.

Mesh backhauls are getting attention for 5G networks, but not only. A backhaul mesh is attractive due to its multiple potential paths that grants redundancy and robustness. The real topology and its properties, however, is heavily influenced by the characteristics of the place where it is deployed, a fact that is rarely taken into account by scientific literature, mainly due to the lack of detailed topographic data. This WIP analyzes the impact of true topography on small backhaul meshes in nine different locations in Italy. Initial results stress how true data influence results and can help designing better networks and better services.

Many optimization techniques for networking protocols take advantage of topological information to improve performance. Often, the topological information at the core of these techniques is a centrality metric such as the Betweenness Centrality (BC) index. BC is, in fact, a centrality metric with many well-known successful applications documented in the literature, from resource allocation to routing. To compute BC, however, each node must run a centralized algorithm and needs to have the global topological knowledge; such requirements limit the feasibility of optimization procedures based on BC. To overcome restrictions of this kind, we present a novel distributed algorithm that requires only local information to compute an alternative similar metric, called Load Centrality (LC). We present the new algorithm together with a proof of its convergence and the analysis of its time complexity. The proposed algorithm is general enough to be integrated with any distance vector (DV) routing protocol. In support of this claim, we provide an implementation on top of Babel, a real-world DV protocol. We use this implementation in an emulation framework to show how LC can be exploited to reduce Babel's convergence time upon node failure, without increasing control overhead. As a key step towards the adoption of centrality-based optimization for routing, we study how the algorithm can be incrementally introduced in a network running a DV routing protocol. We show that even when only a small fraction of nodes participate in the protocol, the algorithm accurately ranks nodes according to their centrality.

The trend toward autonomous driving and the recent advances in vehicular networking led to a number of very successful proposals in cooperative driving. Maneuvers can be coordinated among participating vehicles and controlled by means of wireless communications. One of the most challenging scenarios or applications in this context is cooperative adaptive cruise control (CACC) or platooning. When it comes to realizing safety gaps between the cars of less than 5 m, very strong requirements on the communication system need to be satisfied. The underlying distributed control system needs regular updates of sensor information from the other cars in the order of about 10 Hz. This leads to message rates in the order of up to 10 kHz for large networks, which, given the possibly unreliable wireless communication and the critical network congestion, is beyond the capabilities of current vehicular networking concepts. In this paper, we summarize the concepts of networked control systems and revisit the capabilities of current vehicular networking approaches. We then present opportunities of Tactile Internet concepts that integrate interdisciplinary approaches from control theory, mechanical engineering, and communication protocol design. This way, it becomes possible to solve the high reliability and latency issues in this context.

Wireless Mesh Networks are subject to frequent node and link failures, and routing protocols currently used, such as Optimized Link State Routing (OLSR) or Babel, suffer from relatively long recovery times characterized by broken and looped routes due to long management timeouts that can not be shortened to keep the overhead at an acceptable level. This paper experiments a novel timer management technique named Pop-Routing on top of OLSR. Pop-Routing exploits the notion of betweenness centrality to tune timers depending on the node position in the network, so that failures that lead to larger traffic losses can be recovered faster. Pop-Routing maintains the overhead constant, but favors the most central nodes, whose failure is devastating from the performance point of view, and penalizes peripheral ones, whose failure has a very little impact on the entire network. Pop-Routing has been implemented as a plug-in in the OLSR daemon, coupled with an external process, named Prince, that computes centrality and timer values without interfering with the routing daemon. Experiments are run on the WiSHFUL showing the benefit of Pop-tuning OLSR Hello and Traffic Control timers.

Centrality metrics are a key instrument for graph analysis and play a central role in many problems related to networking such as service placement, robustness analysis and network optimization. Betweenness centrality is one of the most popular and well-studied metric. While distributed algorithms to compute this metric exist, they are either approximated or limited to certain topologies (directed acyclic graphs or trees). Exact distributed algorithms for betweenness centrality are computationally complex, because its calculation requires the knowledge of all possible shortest paths within the graph. In this paper we consider load centrality, a metric that usually converges to betweenness, and we present the first distributed and exact algorithm to compute it. We prove its convergence, we estimate its complexity and we show it is directly applicable-with minimal modifications-to any distance-vector routing protocol based on Bellman-Ford. We finally implement it on top of the Babel routing protocol and we show that, exploiting centrality, we can significantly reduce Babel's convergence time upon node failure without increasing signalling overhead. Our contribution is relevant in the realm of wireless distributed networks, but the algorithm can be adopted in any distributed system where it is not possible, or computationally impractical, to reconstruct the whole network graph at each node and compute betweenness centrality with the classical approach based on Dijkstra's algorithm.

Summary Modern computing hardware has a very good task parallelism, but resource contention between tasks remains high. This renders large fractions of CPU time wasted and leads to application interference. Even tasks running on dedicated CPU cores can still incur interference from other tasks, most notably because of the caches and other hardware components shared by more than one core. The level of interference depends on the nature of executed tasks and is difficult to predict. A customer who has been granted that his task will run as if it were alone (e.g., a CPU core dedicated to a virtual machine), indeed suffers from significant performance degradation due to the time spent waiting for resources occupied by other tasks. Measuring actual performance of a task or a virtual machine can be difficult. However, even more challenging is estimating what the performance of the task should be if it were running completely in isolation. In this paper, we present a measurement techniqueFreeze'nSense. It is based on the hardware performance counters and allows measuring actual performance of a task and estimating performance as if the task were in isolation, all during runtime. To estimate performance in isolation, the proposed technique performs a short‐time freezing of the potentially interfering tasks.Freeze'nSenseintroduces lower than 1% overhead and is confirmed to provide accurate and reliable measurements. In practice,Freeze'nSensebecomes a valuable tool helping to automatically identify tasks that suffer the most in a shared environment and move them to a distant core. The observed performance improvement can be as large as 80–100% for individual tasks, and scale up to 15–20% for the computing node. Copyright © 2016 John Wiley & Sons, Ltd.

Betweenness centrality is a popular metric in social science, and recently it was adopted also in computer science. Betweenness identifies the node, or the nodes, that are most suitable to perform critical network functions, such as firewalling and intrusion detection. However, computing centrality is resource-demanding, we can not give for granted that it can be computed in real time at every change in the network topology. This is especially true in mesh networks that generally use devices with few computation resources. This paper shows that using the fastest state-of-the-art heuristic algorithm it is indeed possible to compute network centrality even in real, low-power networking hardware in a network made of up to 1000 nodes. Not only, observing the behavior of a real mesh network it shows that centrality does not need to be updated at every topology change, but it can be safely re-computed with an interval in the order of the tens of minutes. Our findings confirms that centrality can be effectively and successfully used as a building block for security functions in mesh networks.

Fast and efficient recovery from node failure, with minimal disruption of routes and the consequent traffic loss is of the utmost importance for any routing protocol. Link-state protocols, albeit preferred to distance vector ones because of faster convergence, still suffer from a trade-off between control message overhead and performance. This work formalizes the routes' disruption following a node failure as an optimization problem depending on the nodes' centrality in the topology, constrained to a constant signaling overhead. Next, it shows that the solution can be found using Lagrange Multipliers. The solution complexity is low enough to be computed on-line on the network routers, thus obtaining the optimal setting of control message timers that minimize the traffic loss following a node failure. The gain obtained is quantified in power-law synthetic topologies, and it is also tested on real network topologies extending the OLSR protocol to use the modified timers, showing that the inevitable approximations introduced in the analysis do not hamper the very good results achievable through this novel approach. The technique can be applied to any link state protocol, including OSPF, and improves route convergence not only upon failures but on every topology modification.

An Intersection Assistance System aim to assist road users in avoiding collisions at intersections, either by warning the driver or by triggering automated actions. Such a system can be realized based on passive scanning only (e.g., using LiDAR) or supported by active Inter-Vehicle Communication (IVC). The main reason to use Inter-Vehicle Communication (IVC) is its ability to provide situation awareness even when a possible crash candidate is not yet in visual range. The IVC research community has identified beaconing, i.e., one-hop broadcast, as the primary communication primitive for vehicular safety applications. Recently, adaptive beaconing approaches have been studied and different congestion control mechanisms have been proposed to cope with the diverse demands of vehicular networks. In this paper, we show that current state-of-the-art congestion control mechanisms are not able to support IAS adequately. Specifically, current approaches fail due to their inherent fairness postulation, i.e., they lack fine grained prioritization. We propose a solution that extends congestion control mechanisms by allowing temporary exceptions for vehicles in dangerous situations, that is, situation-based rate adaptation. We show the applicability for two state-of-the-art congestion control mechanisms, namely Transmit Rate Control (TRC) and Dynamic Beaconing (DynB), in two different vehicular environments, rural and downtown.

Automated and coordinated vehicles' driving (platooning) is gaining more and more attention today and it represents a challenging scenario heavily relying on wireless Inter-Vehicular Communication (IVC). In this paper, we propose a novel controller for vehicle platooning based on consensus. Opposed to current approaches where the logical control topology is fixed a priori and the control law designed consequently, we design a system whose control topology can be reconfigured depending on the actual network status. Moreover, the controller does not require the vehicles to be radar equipped and automatically compensates outdated information caused by network delays. We define the control law and analyze it in both analytical and simulative way, showing its robustness in different network scenarios. We consider three different wireless network settings: uncorrelated Bernoullian losses, correlated losses using a Gilbert-Elliott channel, and a realistic traffic scenario with interferences caused by other vehicles. Finally, we compare our strategy with another state of the art controller. The results show the ability of the proposed approach to maintain a stable string of vehicles even in the presence of strong interference, delays, and fading conditions, providing higher comfort and safety for platoon drivers.

We study the effect of radio signal shadowing dynamics, caused by vehicles and by buildings, on the performance of beaconing protocols in Inter-Vehicular Communication (IVC). Recent research indicates that beaconing, i.e., one hop message broadcast, shows excellent characteristics and can outperform other communication approaches for both safety and efficiency applications, which require low latency and wide area information dissemination, respectively. To mitigate the broadcast storm problem, adaptive beaconing solutions have been proposed and designed. We show how shadowing dynamics of moving obstacles hurt IVC, reducing the performance of beaconing protocols. To the best of our knowledge, this is one of the first studies on identifying the problem and the underlying challenges and proposing the opportunities presented by such challenges. Shadowing also limits the risk of overloading the wireless channel. We demonstrate how these challenges and opportunities can be taken into account and outline a novel approach to dynamic beaconing. It provides low-latency communication (i.e., very short beaconing intervals), while ensuring not to overload the wireless channel. The presented simulation results substantiate our theoretical considerations.

Peer-to-peer live-streaming (P2P-TV) systems' goal is disseminating real-time video content using peer-to-peer technology. Their performance is driven by the overlay topology, i.e., the virtual topology that peers use to exchange video chunks. Several proposals have been made in the past to optimize it, yet few experimental studies have corroborated results. The aim of this paper is to provide a comprehensive experimental comparison based on PeerStreamer in order to benchmark different strategies for the construction and maintenance of the overlay topology in P2P-TV systems. We present only experimental results in which fully distributed strategies are evaluated in both controlled experiments and the Internet using thousands of peers. Results confirm that the topological properties of the overlay have a deep impact on both user quality of experience and network load. Strategies based solely on random peer selection are greatly outperformed by smart yet simple and actually implementable strategies. The most performing strategy we devise guarantees to deliver almost all chunks to all peers with a playout delay as low as 6 s even when system load approaches 1, and in almost adversarial network scenarios. PeerStreamer is open-source to make results reproducible and allow further research by the community.

We study the ability of Inter-Vehicle Communication (IVC) solutions to handle real-time requirements in safety scenarios using beaconing as a communication primitive. One of the envisioned safety applications is intersection assistance. The objective of such applications is to either warn the driver or even to act autonomously if other approaching vehicles endanger the vehicle. Fairness, combined with aggressive channel access for low-latency safety messages, has been one of the main research line according to which state of the art congestion control mechanisms have been developed. We show that these solutions are not able to sufficiently support intersection assistance applications. Specifically, we show that current approaches fail exactly due to their fairness postulation. We propose a new situation-aware solution to this fairness dilemma by allowing temporary exceptions for vehicles in dangerous situations. We show the applicability for two state of the art congestion control mechanisms, namely ETSI Transmit Rate Control (TRC) and Dynamic Beaconing (DynB). Our investigation also reveals important research objectives for future IVC protocols, namely how much reactivity and situation-awareness is needed in the highly dynamic environment of vehicular networks.

Distributing live streaming in Wireless Community Networks (WCNs) is a service with a high added value; however, cloud-based streaming, as commonly used in the Internet, does not fit well the architecture of WCNs, which often have restricted access to the Internet. Modern WCNs, instead, can have a good internal connectivity with high bandwidth. A P2P approach is thus well matched for streaming in WCNs. This paper presents experimental results obtained with PeerStreamer running on top of Community-Lab, a test-bed realized by the CONFINE EU Project for the experimentation of novel protocols in community networks. The experiments highlight relevant differences between a WCN and the Internet, and we propose strategies that can be implemented on all the peers or even only locally on the source to improve the streaming quality. These strategies are based on simple heuristics and can be activated dynamically when the streaming quality degrades below a given threshold.

We study the effect of radio signal shadowing dynamics, caused by vehicles and by buildings, on the performance of beaconing protocols in Inter-Vehicular Communication (IVC). Recent research indicates that beaconing, i.e., one hop message broadcast, shows excellent characteristics and can outperform other communication approaches for both safety and efficiency applications, which require low latency and wide area information dissemination, respectively. We show how shadowing dynamics of moving obstacles hurt IVC, reducing the performance of beaconing protocols. At the same time, shadowing also limits the risk of overloading the wireless channel. To the best of our knowledge, this is the first study identifying the problems and resulting possibilities of such dynamic radio shadowing. We demonstrate how these challenges and opportunities can be taken into account and outline a novel approach to dynamic beaconing. It provides low-latency communication (i.e., very short beaconing intervals), while ensuring not to overload the wireless channel. The presented simulation results substantiate our theoretical considerations.

Thin-client based solutions allow users to connect to remote servers and access content that is running on these servers within a virtual PC. With the advent of cloud based solutions, thin-client deployments running on remote Data-centers are increasingly popular. Unfortunately, since the traffic has to traverse through the Internet, issues such as latency, packet drops, and potentially congestion are introduced, which in turn affect the Quality of Experience (QoE) for the user. Our objective is to provide preferential treatment to certain thin-client flows over the rest of the thin-client flows traversing the same intermediate node, based on the application that the user is using at a given point in time. This is not straightforward, as it is not easy to identify what actual application is running inside a given thin client session, given that thin client protocols essentially only send bitmaps of the desktop to the client and in addition are often encrypting traffic. Assuming that some statistical mechanisms for application identification for thin client connections exists, the challenge we address is how to exploit this information for QoE-driven scheduling. We present a scheme that allows the prioritization of thin client flows that are serving delay-sensitive applications, i.e., prioritizing flows based on the specific QoE requirements of the dynamically changing individual applications running within persistent thin client traffic flows. Our solution is essentially a hybrid scheduling scheme that takes into account the dynamically changing delay and bandwidth requirements of inner (i.e., tunneled in the thin client protocol) applications to prioritize flows that are close to an application-dependent QoE threshold. Our evaluation based on a prototype implementation reveals that our algorithm is indeed effective in dynamically prioritizing persistent thin-client flows based on the dynamically changing inner applications running within the flows.

P2P13 was held in Trento, Italy September 9–11 2013. Peer-to-Peer Computing is a small, single track, focussed conference on Peer-to-Peer technologies that is today recognized as one of the most relevant venues for the publication and dissemination of results on Peer-to-Peer technologies, applications, systems, and networks.

The Session Initiation Protocol (SIP) is at the root of many sessions-based applications such as VoIP and media streaming that are used by a growing number of users and organizations. The increase of the availability and use of such applications calls for careful attention to the possibility of transferring malformed, incorrect, or malicious SIP messages as they can cause problems ranging from relatively innocuous disturbances to full blown attacks and frauds. To this end, SIP messages are analyzed to be classified as “good” or “bad” depending on whether this structure and content are deemed acceptable or not. This paper presents a classifier of SIP messages based on a two stage filter. The first stage uses a straightforward lexical analyzer to detect and remove all messages that are lexically incorrect with reference to the grammar that is defined by the protocol standard. The second stage uses a machine learning approach based on a Support Vector Machine (SVM) to analyze the structure of the remaining syntactically correct messages in order to detect semantic anomalies which are deemed a strong indication of a possibly malicious message. The SVM “learns” the structure of the “good” and “bad” SIP messages through an initial training phase and the SVM thus configured correctly classifies messages produced by a synthetic generator and also “real” SIP messages that have been collected from the communication network at our institution. The preliminary results of such classification look very promising and are presented in the final section of this paper.

Voice and multimedia communications are rapidly migrating from traditional networks to TCP/IP networks (Internet), where services are provisioned by SIP (Session Initiation Protocol). This paper proposes an on-line filter that examines the stream of incoming SIP messages and classifies them as good or bad. The classification is carried out in two stages: first a lexical analysis is performed to weed out those messages that do not belong to the language generated by the grammar defined by the SIP standard. After this first stage, a second filtering occurs which identifies messages that somehow differ - in structure or contents - from messages that were previously classified as good. While the first filter stage is straightforward, as the classification is crisp (either a messages belongs to the language or it does not), the second stage requires a more delicate handling, as it is not a sharp decision whether a message is semantically meaningful or not. The approach we followed for this step is based on using past experience on previously classified messages, i.e. a "learn-by-example" approach, which led to a classifier based on Support-Vector-Machines (SVM) to perform the required analysis of each incoming SIP message. The paper describes the overall architecture of the two-stage filter and then explores several points of the configuration-space for the SVM to determine a good configuration setting that will perform well when used to classify a large sample of SIP messages obtained from real traffic collected on a VoIP installation at our institution. Finally, the performance of the classification on additional messages collected from the same source is presented.

Automated platooning is one of the most challenging fields in the domain of ITS. Conceptually, platooning means creating clusters of vehicles which closely follow each other autonomously without action of the driver, neither for accelerating, nor for braking.

P2P-TV systems performance are driven by the overlay topology that peers form. Several proposals have been made in the past to optimize it, yet little experimental studies have corroborated results. The aim of this work is to provide a comprehensive experimental comparison of different strategies for the construction and maintenance of the overlay topology in P2P-TV systems. To this goal, we have implemented different fully-distributed strategies in a P2P-TV application, called Peer-Streamer, that we use to run extensive experimental campaigns in a completely controlled set-up which involves thousands of peers, spanning very different networking scenarios. Results show that the topological properties of the overlay have a deep impact on both user quality of experience and network load. Strategies based solely on random peer selection are greatly outperformed by smart, yet simple strategies that can be implemented with negligible overhead. Even with different and complex scenarios, the neighborhood filtering strategy we devised as most performing guarantees to deliver almost all chunks to all peers with a play-out delay as low as only 6s even with system loads close to 1.0. Results are confirmed by running experiments on PlanetLab. PeerStreamer is open-source to make results reproducible and allow further research by the community.

MPR selection is one of the most important and critical functions of OLSR. The OLSR standard specifies an algorithm that has good local properties in terms of number of MPR selected but does not use available information in order to reduce the global number of MPR nodes. MPR selection affects many network properties, from the actual logical topology, to the routing efficiency, to the protocol overhead and the broadcast/multicast delivery. This paper proposes and evaluates two simple modifications to the MPR selection strategy, which are oriented to global properties rather than local `optimality'. The results presented show that even marginal modifications of the heuristic lead to a performance improvement, with, for instance, a reduction of up to 15% in the number of control messages required to maintain the topology, a relevant gain specially when obtained without introducing any overhead in control messages.

Research in Wireless Mesh Networking has been very active in the past years, with the birth of several new ideas and the protocols that implement them. Most common implementations rely on Layer-3 addressing and routing; however 802.11s and other successful protocols suggest that Mesh Networking on Layer-2 address space is more efficient, does not mingle with the global IP routing, and provides easier ways to support micro-mobility as well as client management. This paper focuses on the client announcement protocol, i.e., the functionality, somewhat embedded between Layer-2 and Layer-3, that allows routers in a mesh network to announce the clients they are serving and that in practice makes the entire routing protocol work correctly. In particular, it focuses on B.A.T.M.A.N.-Advanced, analyses the shortcomings of the simple implementation of this functionality present until v.2011.2.0 and defines the new protocol and algorithms that we have implemented and are part of the distribution starting from v.2011.3.0. Experiments in controlled scenarios show how performance increases dramatically even in scenarios designed specifically to stress the new protocol. The new mechanism and improved performance make it possible to design new features for B.A.T.M.A.N.-Advanced, most notably the support for fast and seamless handover, which is currently under testing.

SUMMARY Grid applications move large amounts of data between distributed resources, and the efficiency of a Grid depends on their timely delivery within given bounds (deadlines). In most cases, the data volume and deadline are known in advance, allowing for both network planning and connection admission control (textrmCAC). We formally define the problem and, based on this formalization, describe the operation of a feasible procedure for network reservations of deadline‐constrained bulk data transfer requests. The procedure guarantees a minimum bandwidth to meet the deadlines and allows for opportunistic utilization of residual network capacity. We propose a novel analytical model based on the solution of anM/M(nc)/1/k(s)−RPSqueue. The analytical model is validated againstns−2 simulations taking into account network level details (IP and TCP protocols), showing remarkably good coherence even under heavy loads. The model is orders of magnitude faster than simulation, which enables its application to plan the capacity of Grid networks, and to enforce CAC under the hypothesis of a dominating bottleneck on the transfer route. Copyright © 2011 John Wiley & Sons, Ltd.

SUMMARY This paper presents an evaluation of the impact of the so‐called operating system (OS) latencies on the performance of a synchronous network based on global time coordination. The concept of end‐to‐end latency was first defined by extending the concept of latency used to evaluate the performance of real‐time systems and the end‐to‐end latency provided by a general‐purpose OS was measured as a benchmark. Finally, real‐time techniques were used to reduce the worst‐case values of such a latency, showing how a gateway between synchronous and asynchronous networks can be implemented by using commercial‐off‐the‐shelf hardware and a proper software stack (based on a real‐time version of Linux). The use of a real‐time OS is still a nontrivial task, which requires experience and the analysis of the specific application to devise the proper techniques to be applied. This work dissects the problem of OS‐to‐network data transfer (and vice versa) identifying the key sources of latencies and delay jitter, and solving each problem with the application of a proper technique. Copyright © 2011 John Wiley & Sons, Ltd.

Splitting a P2P video distribution in multiple media flows with different priorities is an interesting approach for developing flexible and adaptive streaming systems, ranging from VoD to TV. Such an approach can both yield satisfactory quality to all end users and be light in network resources usage, because low-priority flows can be discarded a-priori when target peers do not have enough resources to receive them. This paper focuses on chunk-based video distribution in unstructured meshes, adopting a push strategy (the sender takes the scheduling decision) based on buffer map exchange to avoid sending duplicated chunks. A deadline-based scheduling algorithm is proposed, where different flows of chunks are prioritized using different deadline postponing parameters for each flow. Some experimental results show good differentiation properties and streaming performance much better than with strict priority enforcement. Also, PSNR measures on real video streams show improvements compared to both strict priority and single stream distribution.

P2P TV and video streaming are among the most bandwidth-hungry applications running over the Internet. One of the main reasons is that the scheduling of information transfer between peers is extremely aggressive and does not take network characteristics into account. Moreover, schedulers are not designed to be robust and configurable, so that their performance is greatly affected by networking conditions. This work first analyzes the impact of network heterogeneity on the streaming performance and then proposes a novel, robust, configurable, network-aware scheduler that outperforms the other schedulers in all networking scenarios.

Botnets have become the most sophisticated and dangerous way of spreading malware. Their damaging actions can range from massive dispatching of e-mail messages, to denial of service attacks, to collection of private and sensitive information. Unlike standard computer viruses or worms, botnets spread silently without actively operating their damaging activity, and then are activated in a coordinated way to maximize the ``benefit'' of the malware. In this paper we propose two models based on compartmental differential equations derived from ``standard'' models in biological disease preading. These models offer insight into the general behavior of botnets, allowing both the optimal tuning of botnets' characteristics, and possible countermeasures to prevent them.

P2P TV distribution is going commercial, and the video quality delivered to users becomes of the utmost importance. However, the impact of P2P distribution on the video quality is not completely understood yet, especially in live streaming situations. This work addresses the impact of P2P distribution when the delay of the playout is limited, as it must be in any true live TV service. A methodology for the evaluation (using standard objective video quality metrics) is proposed, showing that different ways of grouping frames in chunks for the distribution can lead to very different quality when the system is overloaded.

P2P video streaming is receiving enormous attention, and when video is involved, the efficient use of the network becomes a very important issue, specially if live applications are addressed. In this work we study properties of Push/Pull protocols for the exchange of video chunks in non-structured systems. Push/Pull protocols are a broad class of chunk exchange mechanisms where peers alternate phases where they actively send chunks to other peers, with phases where they seek for missing chunks from other peers. We focus on the properties of the protocol, trying to gain insight on the distributed exchange mechanism itself. Then, we explore how performances can be improved if peers, in selecting the peers to exchange information with, also consider network level parameters, namely the round trip delay.

P2P-TV systems have become part of the Internet landscape (See for instance http://www.pplive.com, http://www.soapcast.com, http://www.tvants.com, and many others). The architecture of these (normally proprietary) applications is generally receiver-driven, in that receivers actively search for suitable peers to download from, trying to maximize their performance. This results in very aggressive applications that generate huge and non optimized traffic loads. The demo summarized in this short paper shows the impact of various P2P streaming options and the efficiency of the Napa-Wine approach (compared to more traditional approaches) by running real streaming clients in realistic conditions. To make this comparison possible, the software developed in Napa-Wine is highly modular and configurable, allowing the user to test different topology management and chunk trading techniques developed within the Napa-Wine project, as well as to configure it to mimic other chunk/peer selection strategies known from literature.

Protecting users' privacy is becoming one of the rising issues for the success of future communications. The Internet in particular, with its open architecture, presents several threats to the right of protecting personal and sensitive data. One fundamental building block of privacy-respectful communications is protecting the communication parties identities, or, as it is commonly called within the research community anonymous networks (ANs). An AN prevents external observers as well as the network to have access to communicating partners identities and addresses. In this paper we propose a novel architecture to realize ANs, as an extension to IPsec. After explaining the rationale and discussing possible alternatives, we present a working prototype implementation and its experimental performance comparison with application level solutions.

A future where Internet telephony will constitute a target valuable to attack is not so unrealistic. E-mail spam botnets software can be updated to send voice spam (commonly referred to as SPIT, spam over Internet telephony) constituting a huge threat to VoIP-based applications and business. This paper tries to learn from one of the biggest lessons learnt from the e-mail world, i.e. "do not wait until is too late", and proposes a quantitative study, based on a simulation campaign, of SPIT filtering based on the analysis of the call setup protocols. After discussing attack scenarios based on dichotomic choices by the attacker, it presents how the SPIT filtering system can be optimized in order to self-tune parameters achieving high SPIT detection ratio and low false rates at the same time.

Are P2P systems and applications here to stay? Or are they a bright meteor whose destiny is to disappear soon? In this paper we try to give a positive answer to the first question, highlighting reasons why the P2P paradigm should become an integral part of computing and communication services and not only oddities for Cyber-geeks.

Fractional lambda switching (FlambdaS) is a novel approach for traffic management over all-optical networks with sub-wavelength provisioning capability. The unique characteristic of FlambdaS is the utilization of UTC (coordinated universal time) for switching with minimum or no buffers. Several central research issues are still open in FlambdaS and need to be formally defined and analyzed. In this paper, we introduce three novel switch designs that are based on the use of tunable lasers (which can be replaced in the future with wavelength converters). First, the paper presents analytical results of scheduling feasibility, which measures the total number of possible different schedules for each switch design. Then it is shown that the architecture with the highest scheduling feasibility is strictly non blocking in the space domain. Next, the paper provides a closed form analysis of the blocking probability in the time domain, which is applicable for any strictly non-space blocking switch, using combinatorics. In addition, the paper provides measures of the switching hardware complexity, which, for the strictly non-blocking architecture, has the same switching complexity as Clos interconnection network, i.e., O(N'radic(N')) where N' is the number of optical channels.

This paper proposes a new methodology to model the distribution of finite size content to a group of users connected through an overlay network.Our methodology describes the distribution process as a constrained stochastic graph process (CSGP), where the constraints dictated by the content distribution protocol and the characteristics of the overlay network define the interaction among nodes. A CSGP is a semi-Markov process whose state is described by the graph itself. CSGPs offer a powerful description technique that can be exploited by Monte Carlo integration methods to compute in a very efficient way not only the mean but also the full distribution of metrics such as the file download times or number of hops from the source to the receiving nodes.We model several distribution architectures based on trees and meshes as CSGPs and solve them numerically. We are able to study scenarios with a very large number of nodes and we can precisely quantify the performance differences between the treeand mesh-based distribution architectures.

This paper tackles the problem of traffic and packet scheduling in HCCA, the contention-free portion of the 802.11e MAC protocol. Scheduling traffic belonging to different categories or priorities on a shared channel, as in wireless LANs, is a multi-class complex optimization problem. We consider two different scheduling techniques, one based on an extremely simple positional controller and one based on the optimal solution of the linearized control problem based on a fluid approximation. Simulation results are presented discussing pros and cons of the two solutions both in terms of performances (resource exploitation and traffic differentiation properties) and in terms of implementation complexity and fairness.

This paper studies fundamental properties of stream-based content distribution services. We assume the presence of an overlay network (such as those built by P2P systems) with limited degree of connectivity, and we develop a mathematical model that captures the essential features of overlay-based streaming protocols and systems. The methodology is based on stochastic graph theory, and models the streaming system as a stochastic process, whose characteristics are related to the streaming protocol. The model captures the elementary properties of the streaming system such as the number of active connections, the different play-out delay of nodes, and the probability of not receiving the stream due to node failures/misbehavior. Besides the static properties, the model is able to capture the transient behavior of the distribution graphs, i.e., the evolution of the structure over time, for instance in the initial phase of the distribution process. Contributions of this paper include a detailed definition of the methodology, its comparison with other analytical approaches and with simulative results, and a discussion of the additional insights enabled by this methodology. Results show that mesh based architectures are able to provide bounds on the receiving delay and maintain rate fluctuations due to system dynamics very low. Additionally, given the tight relationship between the stochastic process and the properties of the distribution protocol, this methodology gives basic guidelines for the design of such protocols and systems.

We consider the problem of distributing a content of finite size to a group of users connected through an overlay network that is built by a peer-to-peer application. The goal is the fastest possible diffusion of the content until it reaches all the peers. Applications like Bit-Torrent or SplitStream are examples where the problem we study is of great interest. In order to represent the content diffusion process, we model the system as a stochastic graph process and define the constraints the graph evolution is subject to. The evolution of the graph is a semi-Markov process where the sojourn times are the rewards of interest for the computation of the time needed to complete the file distribution. We discuss the general properties of the constrained stochastic graphs and we show preliminary results obtained with an ad-hoc Monte-Carlo technique.

In this paper we investigate which is the most efficient architecture and protocol that can be used for file distribution. The focus of the analysis is to understand not only the parameters that influence the distribution process (constraints on the number of neighbors, bandwidth heterogeneity, etc.), but also the impact of the peer behavior, such as selfishness or neighbor selection strategies. The analysis also compares different tree- and mesh-based distribution architectures. We developed an ad-hoc Monte-Carlo technique that is able to analyze scenarios with millions of peers, a network size that traditional discrete- event simulators are not able to treat. The results give an accurate view of the fundamental protocol parameters and policies that impact on the final performance and allow designers to devise improved protocols.

Fractional Lambda Switching (FλS) is a novel proposal for the management of all-optical networks with sub-wavelength provisioning capability. The unique characteristic of FλS is the utilization of the UTC (coordinated universal time) for alignment and switching. Several central research issues are still open in FλS and need to be formally defined and analyzed. Within the scope of this paper, we introduce three novel switch architecture designs that are based on the use of tunable lasers. As an important goal, we introduce the notion “scheduling feasibility” that measure the number of possible different scheduling between an input and output time-frames.

Traffic grooming in IP over WDM networks introduces a coupling between the optical and the IP layer. Grooming algorithms are normally studied with a very simple traffic model that completely ignores this interaction. This paper compares the performance of two simple grooming algorithms with a traditional Poisson based traffic model and a more complex one that takes into account the IP traffic elasticity and the inherent interaction between IP and the optical layer. Simulation results, supported by heuristic considerations highlighting the interaction effects, show that ignoring the two layer interaction may lead to wrong conclusions and waste of resources.

In this paper, we propose a MMPP (Markov modulated Poisson process) traffic model that accurately approximates the LRU (long range dependence) characteristics of Internet traffic traces. Using the notion of sessions and flows, the proposed MMPP model mimics the real hierarchical behavior of the packet generation process by Internet users. Thanks to its hierarchical structure, the proposed model is both simple and intuitive: it allows the generation of traffic with the desired characteristics by easily setting a few input parameters which have a clear physical meaning. Results prove that the queuing behavior of the traffic generated by the MMPP model is coherent with the one produced by the real traces collected at our institution edge router under different networking scenarios and loads. Due to its characteristics, the proposed MMPP traffic model can be used as a simple and manageable tool for IP network performance analysis, as well as for network planning and dimensioning.

This paper presents a new analytical model for the estimation of the performance of TCP connections. The model is based on the description of the behavior of TCP in terms of a closed queueing network. The model is very accurate, deriving directly from the finite state machine description of the protocol. The assessment of the accuracy of the analytical model is based on comparisons against detailed simulation experiments developed with the ns-2 package. The protocol model interacts with an IP network model that can take into account meshed topologies with several bottlenecks. Numerical results indicate that the proposed closed queueing network model provides accurate performance estimates in all situations. A novel and interesting property of the model is the possibility of deriving ensemble distributions of relevant parameters, such as, for instance, the transmission window size or the timeout probability, which provide useful insight into the protocol behavior and properties.

Analytical approaches for the performance investigation of portions of the Internet often consider the behavior of TCP over congested (or bottleneck) links. In several cases, the analysis is based on an iterative fixed point approximation (FPA) to compute the equilibrium point, in terms of packet loss rate and offered load, that represents the operating point of the network. Almost invariably, the FPA is conjectured to converge, but no proof of convergence is provided. This paper proves that a general model of a reliable protocol (such as TCP) over congested links converges to a unique stable solution under mild regularity conditions. This provides a justification of the convergence observed in the literature and a solid base for the further development of analytical approaches based on FPAs.

Tstat is a new tool for the collection and statistical analysis of TCP/IP traffic, able to infer TCP connection status from traces. Discussing its use, we present some of the performance figures that can be obtained and the insight that such figures can give on TCP/IP protocols and the Internet. While standard performance measure, such as flow dimensions, traffic distribution, etc., remain at the base of traffic evaluation, more sophisticated indices, like the out-of-order probability and gap dimension in TCP connections, obtained through data correlation between the incoming and outgoing traffic, give reliable estimates of the network performance also from the user perspective. Several of these indices are discussed on traffic measures performed for more than 2 months on the access link of our institution.

This paper discusses a new approach to QoS routing, introducing the notion of algorithm resilience (i.e., its capability to adapt to network and load modifications) as the performance index of the algorithm itself, for a given network topology, load and traffic pattern. The new approach can be summarized as network graph reduction, i.e., a modification of the graph describing the network before the routing path is computed, in order to exclude from the path selection over-congested portions of the network. This solution leads to a class of two-step routing algorithms, where both steps are simple, hence allowing efficient implementation. Simulation experiments, run on randomly-generated topologies and traffic patterns, show that these routing algorithms outperform both the standard minimum hop algorithm and those QoS-based algorithms based on the same metrics but not using the notion of network graph reduction.

Research on congestion-control algorithms has traditionally focused more on performance than on robustness of the closed-loop system to changes in network conditions. As the performance of the control loop is strictly connected with the quality of service, these systems are natural candidates to be approached by the optimal control theory. Unfortunately, this approach may fail in the presence of transmission delay variations, which are unavoidable in telecommunication systems. In this paper, we first show the fragility of optimal controllers and demonstrate their instability when the control delay is not known exactly. Then we propose a robust control algorithm based on a classical proportional integral derivative scheme which does not suffer from this fragility phenomenon. Its stability versus the control delay variations, as well as versus sources that transmit less than their computed share, is studied with Nyquist analysis. The control algorithm is implemented within a simulator in the framework of the asynchronous transfer mode (ATM) ABR transfer capability. The final part of the paper shows some selected results assessing the performance of the control algorithm in a realistic network environment. ABR was chosen as an example, but the control studied here can be applied in any data network to obtain a robust and reliable congestion-control scheme.

The first part of this paper presents a novel scheme for handover provisioning in wireless asynchronous transfer mode (W-ATM) networks based on in-band signaling. First, the network architecture and principles of in-band signaling are described, discussing advantages and interaction with other procedures and signaling techniques. Then, loss-free protocols for the handover procedures are presented and compared with existing proposals. The second part of the paper is devoted to performance analysis of the handover procedures. A general methodology for evaluating handover delays and required buffer capacity is introduced and exemplified for one of the protocols introduced before. Numerical results give insight into the handover procedure characteristics and are compared with estimates provided by detailed discrete event simulations for validation purposes. Finally, additional simulation results are presented for parallel, concurrent handovers, evaluating the requirements posed to the network by different handover procedures.

In this paper we extend a previously proposed approach for the performance analysis of short-lived TCP connections, so as to allow the investigation of multiple-bottleneck networks loaded with the traffic resulting from a mixture of TCP-Tahoe and TCP-NewReno connections. The modeling approach is based on the separate development of three submodels, the first describing the dynamics of TCP Tahoe, the second describing the dynamics of TCP NewReno, and the third describing the behavior of the multi-bottleneck network. The first two models describe the dynamics of the two considered TCP versions using open multiclass queuing networks; the third describes the behavior of the multi-bottleneck network using M/sup [D]//M/1/B queues. The solution of the analytical model allows the computation of a number of interesting performance parameters, among which the most important is the average time necessary for the transfer of a file of a given size.

This paper addresses the problem of evaluating routing algorithms via simulation in packet-switched networks when elastic traffic is involved. It highlights some deficiencies of classical approaches that fail to capture both the complex interactions of connections traversing multiple bottlenecks and common user behaviors. The paper describes an approach devised to overcome these limitations which is particularly suited for the evaluation of routing algorithms in presence of best-effort traffic. The simulation results presented offer a deeper insight into well-known routing algorithms. Through this analysis it is clear that quantitative and also qualitative behaviors of dynamic routing algorithms based on traffic measurements may be fairly different depending on the nature of the traffic loading the network, as well as depending on its interactions with the network parameters and behavior.

This paper presents a new analytical model for the estimation of the performance of TCP connections. The model is based on the description of the behavior of TCP-Tahoe in terms of a closed queueing network, whose solution can be obtained with very low cost, even when the number of TCP connections that interact over the underlying IP network is huge. The protocol model can be very accurate, deriving directly from the finite state machine description of the protocol. The assessment of the accuracy of the analytical model is based on comparisons against detailed simulation experiments developed with the ns-2 package. Numerical results indicate that the proposed closed queueing network model provides extremely accurate performance estimates, not only for average values, but even for distributions, in the case of the classical single-bottleneck configuration, as well as in more complex networking setups.

A novel approximate technique is proposed for the estimation of call blocking probabilities in cellular mobile telephony networks where call blocking triggers customer retrials. The approximate analysis technique is based on Markovian models with state spaces whose cardinalities are proportional to the maximum number of calls that can be simultaneously in progress within cells. The accuracy of the approximate technique is assessed by comparison against results of detailed simulation experiments, results of a previously proposed Markovian analysis approach, and upper and lower bounds to the call blocking probability. Numerical results show that the proposed approximate technique is very accurate, in spite of the remarkably small state spaces of the Markovian models.

This paper proposes a feedback based algorithm for congestion control and bandwidth allocation in the presence of either TCP traffic or both TCP and real time traffic. In this proposal, the network layer conveys bandwidth and propagation delay measurements to data sources, for instance using IPv6 optional fields. TCP sources use this bandwidth delay product to control their congestion window, while video sources use the available bandwidth feedback to adjust their data sending rate. The experiments show that with this approach, the network achieves stable equilibrium, and users, either transmitting TCP traffic or real-time traffic, can share network resources fairly. Furthermore, since TCP sources learn about the available bandwidth independent of packet loss, there is no need to reduce the congestion window following a packet loss. This provides a way to improve the TCP performance in wireless networks where it is difficult to distinguish between congestion loss and radio channel interference loss.

A novel approximate technique is proposed for the estimation of call blocking probabilities in cellular mobile telephone networks where call blocking triggers customer retrials. The approximate analysis technique is based on Markovian models with state spaces whose cardinalities are proportional to the maximum number of calls that can be simultaneously in progress within cells. The accuracy of the approximate technique is assessed by comparison against results of detailed simulation experiments. Numerical results show that the proposed approximate technique is very accurate, in spite of the remarkably small state spaces of the Markovian models.

This paper presents a load-balancing method to improve network utilization when static routing algorithms are employed. Static routing algorithms can generally be reduced to a path assignment problem with the aim of minimizing a cost function: i.e., maximizing network revenues. Unfortunately the problem, when multiple constraints such as different QoS traffic classes are present, is computationally intractable. Load-balancing methods are heuristics that allow the identification of local minima of the cost function that hopefully are close to the real optimum. The load-balancing method we propose is based only on static information about the average traffic load of each traffic relation: a piece of information which can easily be attained in telecommunication networks. The path-selection strategy is defined in terms of set theory and its performance is evaluated via simulation by comparison against standard minimum-hop path selections. Simulation results show that low priority traffic benefits significantly from the more balanced load obtained with our solution.

In the presence of satellite channels, one of the most challenging problems for TCP is to achieve fair bandwidth sharing among several competing connections with round-trip propagation delays that may differ by more than two orders of magnitude. The bandwidth-aware TCP (BA-TCP) provides a fair solution while maintaining the end-to-end semantics of transport protocols. At the same time, it allows backward compatibility and it does not require substantial changes to the existing TCP. In BA-TCP, the network layer is assumed to be able to convey propagation delay and available bandwidth measurements to end users, for instance using IPv6 optional fields. TCP receivers employ this information to compute a generalized advertised window, which, in turn, controls the amount of data the source injects into the network. Experimental results show that a satellite connection can fairly share a bottleneck with wired connections. Furthermore, since BA-TCP exploits the bandwidth-delay product to control the source congestion window, the queuing delay at the bottleneck link tends to zero at steady state and buffer overflow is negligible in most situations.

Fairness in the Internet is becoming a major obstacle for the introduction of commercial services. In this paper we address the problem of fairness with a slightly non-standard approach: we show that, in order to achieve fairness in the Internet, it is enough to provide good congestion control, without the need for explicit computation of fairness indexes. We first introduce a TCP-based congestion scheme that takes into account available bandwidth resources on links, describing how this scheme can be easily introduced as a TCP option in end-systems; it requires neither a centralized approach in routers, nor a per-flow management of traffic. Then several scenarios are analyzed via simulation, showing how and to what degree fairness is achieved. Results are compared with a traditional TCP-Reno implementation with RED routers. Finally, the coexistence of the new TCP version with traditional implementations is discussed.