Edge cloud technologies enable faster and more energy-efficient processing of user requests on servers located at the network’s edge. However, when compared to the cloud, edge resources are significantly more limited, prompting a critical question: as user requests arrive, how to determine which ones to allocate to the edge and which ones to the cloud. Additionally, to ensure a quality of service that considers task priorities, it is essential to reserve available resources for potential high-priority requests. This introduces a fundamental trade-off: reserving excessive computing resources at the edge, in anticipation of high-priority requests, is incompatible with reducing energy consumption. Conversely, allocating all edge resources may push higher-priority, potentially more delay-sensitive tasks into the cloud.To tackle this intricate problem, we present a multi-objective reinforcement learning approach utilizing a modified Q-learning process. This approach facilitates intelligent resource allocation, striking a careful balance between fulfilling high-priority requests and minimizing unused processing capacity. While the multi-objective agent ensures the satisfaction of high-priority services, it optimally utilizes the edge resources. Additionally, we introduce a framework for adapting the two cost components to specific requirements, favoring one objective over the other, and examining their impact on relevant metrics. Results demonstrate that this specialized strategy outperforms a conventional First Come First Served baseline, as well as a myopic strategy, which represents the unmodified Q-learning process, across these metrics.

We propose ColorUAV, a genetic algorithm for UAV path planning under multiple constraints. Our solution enables drones to travel towards a destination point while avoiding obstacles and navigating as close as possible to base stations in order to maximize communication opportunities. ColorUAV learning phase creates UAVs able to interact with their environment and compute paths whose weight is within 17% of the optimal. More interestingly, our trained UAVs are capable of adapting to moderate changes in the environment without re-training and while remaining efficient in terms of the path quality.

Efficient bot detection is a crucial security matter and has been widely explored in the past years. Recent approaches supplant flow-based detection techniques and exploit graph-based features, incurring however in scalability issues in terms of time and space complexity. Bots exhibit specific communication patterns: they use particular protocols, contact specific domains, hence can be identified by analyzing their communication with the outside. To simplify the communication graph, we look at frequency distributions of protocol attributes capturing the specificity of botnets behaviour. In this paper, we propose a bot detection technique named BotFP, for BotFinger-Printing, which acts by (i) characterizing hosts behaviour with at-tribute frequency distribution signatures, (ii) learning behaviour of benign hosts and bots through a clustering technique, and (iii) classifying new hosts based on distances to labelled clusters. We validate our solution on the CTU-13 dataset, which contains 13 scenarios of bot infections, connecting to a Command-and-Control (C&C) channel and launching malicious actions such as port scanning or Denial-of-Service (DDoS) attacks. Our approach applies to various bot activities and network topologies. The approach is lightweight, can handle large amounts of data, and shows better accuracy than state-of-the-art techniques.

Mobile edge computing (MEC) allows for the execution of delay-sensitive and context-aware applications close to the end-users while alleviating backhaul utilization and computation at the core network. A recent trend is to extend the capabilities of the MEC using the available resources of end-user devices beyond the edge, such as vehicles. Because of the highly mobile nature of such devices, the beyond-the-edge computing resources available at the time the MEC offloads a task decays over time. In this paper, we propose and investigate the persistence of groups of computational nodes in a vehicular-augmented MEC scenario. The groups are formed according to the time of arrival of vehicles and their co-location within a cell. Through the analyses of two real-world vehicular scenarios in the cities of Rome and Rio de Janeiro. On the one hand, our results show that the persistence is highly heterogeneous, depending on the vehicular traffic density and the time of day. On the other hand, we are able to identify periods during which the persistence is short and periods that show stronger stability - it becomes then possible to schedule tasks to specific time slots depending on the requirements and the expected persistence.

Efficient bot detection is a crucial security matter and widely explored in the past years. Recent approaches supplant flow-based detection techniques and exploit graph-based features, incurring however in scalability issues, with high time and space complexity. Bots exhibit specific communication patterns: they use particular protocols, contact specific domains, hence can be identified by analyzing their communication with the outside. A way we follow to simplify the communication graph and avoid scalability issues is looking at frequency distributions of protocol attributes capturing the specificity of botnets behaviour. We propose a bot detection technique named BotFP, for BotFingerPrinting, which acts by (i) characterizing hosts behaviour with attribute frequency distribution signatures, (ii) learning benign hosts and bots behaviours through either clustering or supervised Machine Learning (ML), and (iii) classifying new hosts either as bots or benign ones, using distances to labelled clusters or relying on a ML algorithm. We validate BotFP on the CTU-13 dataset, which contains 13 scenarios of bot infections, connecting to a Command-and-Control (C&C) channel and launching malicious actions such as port scanning or Denial-of-Service (DDoS) attacks. Compared to state-of-the-art techniques, we show that BotFP is more lightweight, can handle large amounts of data, and shows better accuracy.

Although D2D communications have been extensively investigated in the literature, relatively few works have focused on understanding the capacity of direct links in a real setup. In this paper, we propose an empirical characterization of the currently available high-speed D2D technologies in Android, namelyWi-Fi P2P andGoogle Nearby. To this end, we developed a custom Android application calledOcat which interacts with the available D2D APIs and measures the link's goodput. From the experimental campaign, we derive several useful observations. Concerning communication capacity, the goodput between Android devices ranges between 320~Mbits/s when nodes are within 20 meters of each other and 0.1~Mbits/s when the distance grows to 300 meters. Based on the experimental measurements, we propose a model of the upper-bound goodput as a function of the distance between two devices. Using the wireless signal strength as a link measurement, we combine it with the two-ray ground-reflection model to infer the goodput and obtain a good fit for the characterization of D2D links between Android devices. Our findings provide a reality check in regards to actual direct data-exchange capabilities of Android devices and can help assess system performance of D2D applications.

In this work, we present COLiDeR, the first practical system for two-path relaying using off-the-shelf half-duplex radios. While two-path relaying has been mostly studied from a theoretical perspective in the literature, our solution addresses the challenges of making it practical by introducing two key contributions. First, using a measurement-driven approach, we identify the best approach for a radio to handle two overlapping signals. Just as important, we carefully quantify its limits and introduce the concept of the decoding areas. Second, we introduce a cross-layer protocol that seamlessly navigates the decoding areas with the objective of maximizing throughput while minimizing decoding failures. Experiments on a 4-USRP testbed show that COLiDeR delivers between 80-95% of the relaying performance of an ideal full-duplex radio while incurring negligible decoding failures.

Ever since Network Functions Virtualization has replaced dedicated appliances, ISPs have been able to add a degree of flexibility in their traffic engineering. However, it also has increased the complexity of the optimization problem, because it is now necessary to place virtual functions and route traffic jointly. Insofar, a logically centralized approach has been taken, where a so-called orchestrator, having full knowledge of the network, the virtual functions, and the traffic, run complex algorithms to find a suitable solution to the problem. The outcome of the algorithms are then translated to network configurations to be pushed to all of the appliances. We argue that there is no need to fully centralize every decision, rather we can leverage existing network intelligence to achieve the same goal. In particular we propose to augment the routing layer with the notion of services, so to rely on the robustness and scalability of Interior Gateway Protocols (IGP). Our solution leverages on existing distributed routing protocols where, in addition, autonomous nodes announce information about the virtual services they provide. Our design is modular and incrementally deployable and has been implemented in what we call a NFV Router. In our evaluation, we show that (i) NFV Routers distributed chaining decisions are close to optimal centrally-computed paths, (ii) on a large scale testbed deployment, NFV Routers efficiently steer traffic through chains and only add a small overhead to control traffic and (iii) our distributed system, because of its local control loop, has a faster reaction to network events than centralized solutions.

Assessing the performance of opportunistic networks requires a subtle understanding of both contact and intercontact patterns. While the analysis of intercontacts has attracted significant attention from the research community, surprisingly only a few works have focused on explaining what happens during a contact. In this paper, we perform an in-depth analysis of contacts using both empirical measurements and reference models. We make several observations that allow us to better capture the adaptive nature of device-to-device (D2D)links. In particular, in the case of Wi-Fi 5, we show that a slight modification of the nominal modulation scheme is enough to achieve an accurate characterization of opportunistic contacts for some categories of propagation models. As a consequence, we confirm previous observations that the evaluation of protocols and algorithms for D2D networks based on links of fixed rate may lead to inaccurate results. We finally propose a tool that extends mobility traces with plausible values of per-link capacity.

Physical-Layer Network Coding (PLNC) was first introduced as a solution to increase the throughput of a two-way relay channel communication. Unlike most wireless communication techniques which try to avoid collisions, PLNC allows two simultaneous transmissions to a common receiver. In basic topologies, this technique has been shown to significantly enhance the throughput performance compared to classical interference-free communications. However, quantifying the impact of PLNC in large multi-hop networks remains an open question. In this work, we introduce the first theoretical framework that, given a particular network topology and traffic matrix, can evaluate the optimal network throughput subject to a fairness constraint relative to the initial demand of each flow, when PLNC is adopted. Based on linear programming, our solution ensures to respect the particularities imposed by PLNC. We use this framework to evaluate three state-of-the-art PLNC schemes across a variety of topologies and traffic matrices. Our numerical analysis reveals that while in simple toy topologies PLNC can significantly increase the network throughput, in large topologies the verdict is mixed. For certain topologies and traffic patterns adopting PLNC can double the throughput while in others, depending on the scheme used for implementing PLNC, the gain can be as high as 60 percent or as low as 0 percent when compared to traditional interference-free transmissions.

Ever since Network Functions Virtualization has replaced dedicated appliances, ISPs have been able to add a degree of flexibility in their traffic engineering. Now traffic is steered through virtual functions before reaching its destination, which, nonetheless, hardens network operation. Insofar, a logically centralized approach has been proposed to compute and install the correct forwarding behavior on every network devices. However, this flexibility comes at the cost of increased fragility compared to current Interior Gateway Protocols (IGP) and of a whole new infrastructure. Instead, we propose to augment the routing layer with the notion of services. Our solution leverages on existing distributed routing protocols where, in addition, autonomous nodes announce information about the virtual services they provide. Our design is modular, incrementally deployable and has been implemented in what we call an NFV Router. In our evaluation, we show that (i) NFV Routers distributed chaining decisions are close to optimal centrally-computed paths, (ii) on a large scale testbed deployment, NFV Routers efficiently steer traffic through chains and only add a small overhead to control traffic, and (iii) our distributed system, because of its local control loop, has a faster reaction to network events than centralized solutions.

We revisit Physical-Layer Network Coding (PLNC) and the reasons preventing it from becoming a staple in wireless networks. We identify its strong coupling to the Two-Way Relay Channel (TWRC) as key among them due to its requiring crossing traffic flows and two-hop node coordination. We introduce SE-PLNC, a Source-Encoded PLNC scheme that is traffic pattern independent and involves coordination only among one-hop neighbors, making it significantly more practical to adopt PLNC in multi-hop wireless networks. To accomplish this, SE-PLNC introduces three innovations: it combines bit-level with physical-level network coding, it shifts most of the coding burden from the relay to the source of the PLNC scheme, and it leverages multi-path relaying opportunities available to a particular traffic flow. We evaluate SE-PLNC using theoretical analysis, proof-of-concept implementation on a Universal Software Radio Peripherals (USRP) testbed, and simulations. The theoretical analysis shows the scalability of SE-PLNC and its efficiency in large ad-hoc networks while the testbed experiments its real-life feasibility. Large-scale simulations show that TWRC PLNC barely boosts network throughput while SE-PLNC improves it by over 30%.

Mobile edge computing (MEC) is an emerging technology that aims at pushing applications and content close to the users (e.g., at base stations, access points, and aggregation networks) to reduce latency, improve quality of experience, and ensure highly efficient network operation and service delivery. It principally relies on virtualization-enabled MEC servers with limited capacity at the edge of the network. One key issue is to dimension such systems in terms of server size, server number, and server operation area to meet MEC goals. In this paper, we formulate this problem as a mixed integer linear program. We then propose a graph-based algorithm that, taking into account a maximum MEC server capacity, provides a partition of MEC clusters, which consolidates as many communications as possible at the edge. We use a dataset of mobile communications to extensively evaluate them with real world spatio-temporal human dynamics. In addition to quantifying macroscopic MEC benefits, the evaluation shows that our algorithm provides MEC area partitions that largely offload the core, thus pushing the load at the edge (e.g., with 10 small MEC servers between 55% and 64% of the traffic stay at the edge), and that are well balanced through time.

We investigate the potential gains of Physical-Layer Network Coding (PLNC) in multi-hop wireless networks. Physical-Layer Network Coding was first introduced as a solution to increase the throughput of a two-way relay channel communication. Unlike most wireless communications techniques which try to avoid collisions, PLNC allows two simultaneous transmissions to a common receiver. Such transmitted messages are summed at signal level and then decoded at packet level. In basic topologies, Physical-Layer Network Coding has been shown to significantly enhance the throughput performance compared to classical communications. However, the impact of PLNC in large multi-hop networks remains an open question. We therefore exploit Linear Programming to evaluate the impact of this paradigm in large realistic radio deployments. Our numerical results show that PLNC can increase the throughput in large multi-hop topologies by 30%. Such gains set theoretical benchmarks for designing new access methods and routing protocols to efficiently exploit the Physical-Layer Network Coding concept.

Physical-Layer Network Coding (PLNC) was first introduced as a solution to increase the throughput in simple bidirectional communication schemes. Unlike most wireless communication techniques which try to avoid collisions, PLNC allows two simultaneous transmissions to a common receiver. In this work, we propose a MAC layer distributed and realistic scheduling policy targeting PLNC based networks. In order to easily operate in large ad-hoc networks, our solution is completely decentralized and runs in constant time. By basing the transmission priority of every node on the queue sizes of its local neighbors and PLNC opportunities, our solution ensures high throughput when compared to classical interference-free scheduling. Both our theoretical analysis corroborated by our simulation results highlight that the proposed algorithm outperforms existing scheduling policies with throughput gains of around 35%.

Software-Defined Networking (SDN) allows for fast reactions to security threats by dynamically enforcing simple forwarding rules as counter-measures. However, in classic SDN all the intelligence resides at the controller, with the switches only capable of performing stateless forwarding as ruled by the controller. It follows that the controller, in addition to network management and control duties, must collect and process any piece of information required to take advanced (stateful) forwarding decisions. This threatens both to overload the controller and to congest the control channel. On the other hand, stateful SDN represents a new concept, developed both to improve reactivity and to offload the controller and the control channel by delegating local treatments to the switches. In this paper, we adopt this stateful paradigm to protect end-hosts from Distributed Denial of Service (DDoS). We propose StateSec, a novel approach based on in-switch processing capabilities to detect and mitigate DDoS attacks. StateSec monitors packets matching configurable traffic features (e.g., IP src/dst, port src/dst) without resorting to the controller. By feeding an entropy-based algorithm with such monitoring features, StateSec detects and mitigates several threats such as (D)DoS and port scans with high accuracy. We implemented StateSec and compared it with a state-of-the-art approach to monitor traffic in SDN. We show that StateSec is more efficient: it achieves very accurate detection levels, limiting at the same time the control plane overhead.

We propose to showcase the benefits of stateful SDN in the context of DDoS detection and mitigation. By delegating some local tasks to the switch rather than relying always on the controller, it is possible to monitor data-plane traffic efficiently and to detect malicious network behaviours with high accuracy. Stateful SDN concepts are employed both to improve reactivity and to offload the controller and the control channel by delegating local treatments down to the switches. The demo illustrates how to protect end-hosts from Distributed Denial of Service (DDoS) attacks. Our approach, named StateSec, is built on advanced in-switch processing capabilities to detect and mitigate threats swiftly. StateSec relies on a detection loop to: 1) match and count a configurable set of traffic features (e.g., IP source and destination, port source and destination) without resorting to the controller; 2) use an entropy-based detection algorithm with such monitored features, 3) detect several threats such as (D)DoS and port scans with high accuracy, and 4) take countermeasures by installing OpenFlow rules at the switch.

An isolated base station is a base station having no connection to a traditional core network. To provide services to users, an isolated base station is colocated with an entity providing the same functionalities as the traditional core network, referred to as Local EPC. In order to cover wider areas, several base stations are interconnected, forming a network that should be served by a single Local EPC. In this work, we tackle the Local EPC placement problem in the network, to determine with which of the base stations the Local EPC must be co-located. We propose a novel centrality metric, flow centrality, which measures the capacity of a node to receive the total amount of flows in the network. We show that co-locating the Local EPC with the base station having the maximum flow centrality maximizes the total amount of traffic the Local EPC can receive from all base stations, under certain capacity and load distribution constraints. We compare the flow centrality to other state of the art centrality metrics, and emphasize its advantages.

Traffic offloading using opportunistic device-to-device (D2D) communications is a new and exciting opportunity for cellular operators to cope with the unprecedented mobile data growth. A limitation of existing proposals is that they assume that all terminals are, by default, involved in the D2D forwarding process. In particular, they do not capture the need to reward seed users. For this reason, we include a rewarding cost in the design of the opportunistic offloading strategy. In our solution, we make the difference between nodes that receive content through the cellular channel only (leechers) and nodes that take part in the forwarding process (seeders). The key point for an operator is to design a global strategy to select which nodes act as seeders and which ones as leechers, in order to reduce the total dissemination cost. We formulate this question as a stochastic control problem that we solve using an application of Pontryagin's Maximum Principle. We provide a mathematical framework to devise the optimal strategy for opportunistic offloading under a generic cost model. First, we show that an optimal solution exists; then, from this policy, we extract some insights to develop heuristics. Finally, we discuss the advantages of the proposed model compared to the classic seeder-only model. We demonstrate that separating seeders/leechers leads to better incentive strategies in the most demanding cases of content with a large span of delivery delays.

This paper introduces Rest, a reliable streaming protocol for lossy networks. Rest ensures full reliability while recovering losses as soon as possible thanks to the proactive injection of redundancy packets encoded following an on-the-fly scheme. It dynamically adapts the sending of codes depending on the estimation of the packet error rate with periodic acknowledgments to limit feedback dependency and protocol overhead. Results show that data are smoothly delivered to the receiving application with minimum overhead when errors are uniform. For systems with limited processing capacity, we propose to use a bounded encoding window to deliver data more uniformly while limiting decoding matrices size. We study the performance of Rest under different network conditions and highlight the underlying trade-offs behind each system parameter. We show that an optimal acknowledgement frequency can be estimated to minimize overhead while meeting system requirements in terms of delivery delay and computational power.

In this paper, we propose a new MAC protocol targeting bidirectional full duplex wireless networks. Our solution reserves resources and adapts frame sizes based on the handshake between communicating nodes. Most importantly, our protocol requires minor changes for backward compatibility with IEEE 802.11 protocol. We have implemented and simulated our solution in OMNET++. Our results show up to 93% gains in terms of throughput can be achieved. Moreover, our contribution highlights the need for specific routing solutions in the area of full duplex wireless systems.

Mobile data traffic is set to triple in three years from now according to Cisco. This trend is a real challenge for operators since wireless capacity is bounded.

Network Functions Virtualization (NFV) is transforming how networks are architected and network services delivered. The network is more flexible and adaptable, it can scale with traffic demands. To manage video traffic in the network, or get protection from cyber-attacks, Deep Packet Inspection is increasingly deployed at specific locations in the network. The virtual Deep Packet Inspection (vDPI) engines can be dynamically deployed as software on commodity servers within emerging NFV infrastructures. For a network operator, deploying a set of vDPIs over the network is a matter of finding the appropriate placement that meets the traffic management or cyber-security targets (such as the number of inspected flows) and operational cost constraints (license fees, network efficiency or power consumption). In this work, we formulate the vDPI placement problem as a cost minimization problem. The cost captures the different objectives the operator is pursuing. A placement of vDPIs on the network nodes realizes a trade-off between these possibly conflicting goals. We cast the problem as a multi-commodity flow problem and solve it as an Integer Linear Program (ILP). We then devise a centrality-based greedy algorithm and assess its validity by comparing it with the ILP optimal solution on a real data set (GEANT network with 22 nodes and real traffic matrix). We further analyze the scalability of the heuristic by applying it to larger random networks of up to 100 nodes. The results show the network structure and the costs strongly influence time performance. They also show that after a size limit (between 40 to 80 nodes in our case), the execution time increases exponentially due to combinatorial issues. Finally, they demonstrate that the heuristic well approximate the optimal on smaller problem instances.

Cellular operators count on the potentials of offloading techniques to relieve their overloaded data channels. Beyond standard access point-based offloading strategies, a promising alternative is to exploit opportunistic direct communication links between mobile devices. Nevertheless, achieving efficient device-to-device offloading is challenging, as communication opportunities are, by nature, dependent on individual mobility patterns. We propose, design, and evaluate DROiD (Derivative Re-injection to Offload Data), an original method to finely control the distribution of popular contents throughout a mobile network. The idea is to use the infrastructure resources as seldom as possible. To this end, DROiD injects copies through the infrastructure only when needed: (i) at the beginning, in order to trigger the dissemination, (ii) if the evolution of the opportunistic dissemination is below some expected pace, and (iii) when the delivery delay is about to expire, in order to guarantee 100% diffusion. Our strategy is particularly effective in highly dynamic scenarios, where sudden creation and dissolution of clusters of mobile nodes prevent contents to diffuse properly. We assess the performance of DROiD by simulating a traffic information service on a realistic large-scale vehicular dataset composed of more than 10,000 nodes. DROiD substantially outperforms other offloading strategies, saving more than 50% of the infrastructure traffic even in the case of tight delivery delay constraints. DROiD allows terminal-to-terminal offloading of data with very short maximum reception delay, in the order of minutes, which is a realistic bound for cellular user acceptance.

Routing in overlay networks typically involves engineering an overlay topology on top of the Internet to balance traffic along overlay paths so that quality and/or resilience of delivered services are improved. It can be used to reduce latency for delay-sensitive applications. It then consists in selecting, for any pair of nodes, an intermediate overlay node which reduces the latency on this one-hop overlay path against the latency on the direct overlay path between them. In this paper, we propose to optimize the overhead generated by the overlay route computation mechanism by introducing a differentiation between the nodes that are highly used as relay and those that are not. Our approach relies on disseminating at a high frequency the link states with the identified sub-set of nodes and at a lower frequency all the link states. We conduct large experimentations on PlanetLab to evaluate the trade-off between the performances in terms of RTT gain and the reduction of the control overhead compared to the state of the art.

Most disruption-tolerant networking protocols focus on mere contact and intercontact characteristics to make forwarding decisions. We propose to relax such a simplistic approach and include multi-hop opportunities by annexing a node's vicinity to its network vision. We investigate how the vicinity of a node evolves through time and whether such knowledge is useful when routing data. By analyzing a modified version of the pure WAIT forwarding strategy, we observe a clear tradeoff between routing performance and cost for monitoring the neighborhood. By observing a vicinity-aware WAIT strategy, we emphasize how the pure WAIT misses interesting end-to-end transmission opportunities through nearby nodes. For the datasets we consider, our analyses also suggest that limiting a node's neighborhood view to four hops is enough to improve forwarding efficiency while keeping control overhead low.

We propose a transport protocol capable of dynamically adapting to network and receiver properties in multi-destination, multi-channel wireless networks. The key feature of our solution resides in its ability to convey common traffic to a group of users, while at the same time distributing information to each user as quickly as possible. This is achieved by clustering receivers in groups, each group being served at a suitable throughput. We emphasize in this study on the two groups of receivers case. We show analytically and through OMNet++ simulations that groups formation is decided by the wireless link performance and the proportion of receivers constituting each group. Our solution captures dynamically these effects. Indeed, our transport is capable to cope transparently with wireless links changes (i.e specturm handoff) by adapting dynamically its transmission rate and groups composition. It is therefore adapted for point-to-multipoint cognitive radio networks.

Cooperative ITS systems are expected to highly improve the efficiency of road mobility. Wireless communications are used by these systems to disseminate centralized real-time traffic information to radio-equipped vehicles. Current proposals for traffic information dissemination either exploit dedicated cellular transmissions to interested vehicles, or cooperatively relay the information through vehicular ad-hoc networks. However, dedicated cellular transmissions may pose energy cost and traffic scalability issues to network operators. On the contrary, purely ad-hoc solutions may suffer from network disconnections and not always ensure adequate service reliability. To overcome these limitations, this paper introduces RoAHD, a hybrid approach in which a few messages injected through the cellular system are followed by a cooperative multi-hop dissemination in the vehicular network. RoAHD exploits multi-hop road connectivity information obtained at a low channel cost. Thanks to this knowledge, it is capable to operate smart injection decisions to ensure good levels of message delivery.

While a natural fit for modeling and understanding mobile networks, time-varying graphs remain poorly understood. Indeed, many of the usual concepts of static graphs have no obvious counterpart in time-varying ones. In this paper, we introduce the notion of temporal reachability graphs. A (tau,delta)-reachability graph is a time-varying directed graph derived from an existing connectivity graph. An edge exists from one node to another in the reachability graph at time t if there exists a journey (i.e., a spatiotemporal path) in the connectivity graph from the first node to the second, leaving after t, with a positive edge traversal time tau, and arriving within a maximum delay delta. We make three contributions. First, we develop the theoretical framework around temporal reachability graphs. Second, we harness our theoretical findings to propose an algorithm for their efficient computation. Finally, we demonstrate the analytic power of the temporal reachability graph concept by applying it to synthetic and real-life datasets. On top of defining clear upper bounds on communication capabilities, reachability graphs highlight asymmetric communication opportunities and offloading potential.

Wireless Mesh Networks have been traditionally deployed to offer Internet access. Following the general trend of convergence, they must increasingly provide customers with communication services whose quality constraints are heterogeneous. For large scale deployments, access to the Internet is provided by multiple gateways installed at different points in the network. Each gateway may be connected to the Internet with different technologies (ADSL, Ethernet, satellite, HF link) offering several alternatives to get out of the network with heterogeneous and dynamic performances. Routing QoS-constrained flows so that they always benefit from the best quality available is a challenging task. In addition to an intelligent gateway selection, it requires a forwarding system able to dynamically balance each flow towards the most suitable gateway. Existing candidates generate unnecessary complexity and overhead. In this paper, we propose a distributed and lightweight tag-based forwarding scheme that brings the flexibility required to work at the flow level, and supports dynamic traffic balancing among gateways with various bandwidth, delay or jitter characteristics. We implemented our forwarding scheme on an experimental testbed and applied it to the enforcement of simple gateway selection strategies. Results demonstrate the interest of our approach and its efficiency to dynamically forward specific flows among competing gateways.

So far, efforts attempting to characterize the spatiotemporal nature of disruption-tolerant networks (DTN) have relied on the dual notion of contacts and intercontacts. A contact happens when two nodes are within communication range of each other. An intercontact is simply defined as the dual of a contact, i.e., when two nodes are not in communication range of each other. We refer to this model as “binary”. Although the binary characterization allows understanding the main interaction properties of the network, it is not sufficient to capture a plethora of situations beyond the binary hypothesis. In this paper, we investigate the structural properties of the network when nodes are not in contact but do have a contemporaneous path connecting them. We first introduce the notion of n-ary intercontact and, to defend its adoption, we quantify the proportion of nodes bearing this new intercontact notion in well-known datasets available to the community. Surprisingly, we observe that most pairs of nodes are nearby (within a few hops) for significant amounts of time when not directly in contact. Finally, we compare the impact of our proposal with the classic intercontact definition and give incentives toward using the n-ary characterization to leverage new communication opportunities.

A Public Safety Network (PSN) is a particular kind of wireless ad hoc network which provides a communication support for Public Safety Users. Use-cases are numerous in terms of both deployment scenarios (e.g. mobile or fixed, small or large scale) and services (Push To Talk, Mail reporting, video streaming). Extreme conditions encountered after an earth quake or floodings may impede the use of any communication infrastructure. Maintaining robust and efficient communications is such harsh conditions is a major challenge. QoS requirements lead previous studies towards TDMA based radio resource management combined with clustering techniques for scalability purposes. In this paper we investigate how both Push To-Talk and Mail Reporting services can be supported in such networks. The key contributions are threefold: i) identification of remaining issues within TDMA/Clustered networks ; ii) proposition of a novel radio resource management protocol ; iii) evaluation of performance gains of the novel solution. We show that both services (Push-To-Talk and Mail reporting) can be supported in a Public Safety Network and that our solution outperforms the previous ones. Finally, we present further identified targeted works to improve our solutions.

One of the challenging features of the TVWS for public safety operation is its variation across space and time. More specifically the available channels are not contiguous and vary from one location to another. In addition the white space available in a given location can vary with time if one or more of the TV band primary users start/stop operation. Public Safety Situation Aware services are a main concern when one strives to provide a standard overview of an incident. This standard overview aims at providing intervention information as refreshed as possible to facilitate Incident Commander/Unified Command (e.g. in the case of an European cooperative intervention that involves different Operations Center). Within this study, we propose to investigate how this service can be supported in a Cognitive Radio Network context by considering the unpredictable availability of spectrum resources. We present a Random Network Coding based technique and evaluate the performance assessment of this technique under Cognitive Radio Network assumptions. We show that even for a very restrictive radio resource access, Public Safety Situation Aware services can be fully supported without interfering with a existing primary user activity.

In this paper, we investigate the ability of using Delay Tolerant Networking (DTN) in Public Safety networks, where bandwidth and storage are constrained. We formalize the problem as a Wardrop equilibrium over a time-discretized graph. Driven by our findings, we propose RECOR, a centralized REsource-Constrained ORacle-based DTN routing mechanism, which spreads the demand across multiple store-carry forward paths to satisfy the node storage and link transport constraints observed in intervention situations. By applying the proposed mechanism to real Bluetooth-based DTN traces, we show that the transmission bottleneck can be compensated, but only up to a certain extent, by increasing storage capacity and delay. We also analyze the benefit of strategies that provide more resources to highly connected nodes (e.g. ambulances and firetrucks) which can then feed incentives and policies for DTN network engineering. Finally, the idea presented here is general and suggests the necessity of trace-driven simulation and specific modeling tools for appropriate design of future DTN resource management policies.

Major wireless operators are nowadays facing network capacity issues in striving to meet the growing demands of mobile users. At the same time, 3G-enabled devices increasingly benefit from ad hoc radio connectivity (e.g., Wi-Fi). In this context of hybrid connectivity, we propose Push-and-track, a content dissemination framework that harnesses ad hoc communication opportunities to minimize the load on the wireless infrastructure while guaranteeing tight delivery delays. It achieves this through a control loop that collects user-sent acknowledgements to determine if new copies need to be reinjected into the network through the 3G interface. Push-and-Track includes multiple strategies to determine how many copies of the content should be injected, when, and to whom. The short delay-tolerance of common content, such as news or road traffic updates, make them suitable for such a system. Based on a realistic large-scale vehicular dataset from the city of Bologna composed of more than 10,000 vehicles, we demonstrate that Push-and-Track consistently meets its delivery objectives while reducing the use of the 3G network by over 90%.

Connectivity patterns in intermittently-connected mobile networks (ICMN) can be modeled as edge-Markovian dynamic graphs. We propose a new model for epidemic propagation on such graphs and calculate a closed-form expression that links the best achievable delivery ratio to common ICMN parameters such as message size, maximum tolerated delay, and link lifetime. These theoretical results are compared to those obtained by replaying a real-life contact trace.

We analyze the dynamics of a mobility data set collected in a pipelined disruption-tolerant network (DTN), a particular class of intermittently-connected wireless networks characterized by a 1-D topology. First, we collected and investigated traces of contact times among thousands of participants of a rollerblading tour in Paris. The data set shows extreme dynamics in the mobility pattern of a large number of nodes. Most strikingly, fluctuations in the motion of the rollerbladers cause a typical accordion phenomenon—the topology expands and shrinks with time, thus influencing connection times and opportunities between participants. Second, we show through an analytical model that the accordion phenomenon, through the variation of the average node degree, has a major impact on the performance of epidemic dissemination. Finally, we test epidemic dissemination and other existing forwarding schemes on our traces, and conclude that routing should adapt to the varying, though predictable, nature of the network. To this end, we propose DA-SW (Density-Aware Spray-and-Wait), a measurement-oriented variant of the spray-and-wait algorithm that tunes, in a dynamic fashion, the number of a message copies to be disseminated in the network. The particularity of DA-SW is that it relies on a set of abaci that represents the three phases of the accordion phenomenon: aggregation, expansion, and stabilization. We show that DA-SW leads to performance results that are close to the best case (obtained with an oracle).

Is the temporal dimension alone sufficient to characterize contacts in opportunistic networks? Several studies analyze the temporal aspect of contacts with significant results concerning contact and inter-contact distributions. Nevertheless, only the temporal dimension does not give a complete overview of contact characterization. In this paper, we propose the surround indicator as a metric to exhibit the contact's surrounding environment in opportunistic networks. We evaluate the surround indicator on two existing datasets and show that contacts have too heterogeneous and too unstable surrounds to be considered only in terms of duration. Besides a large variability of the surrounding environment within the duration of a single contact, it is frequent to observe contacts of identical duration that exhibit differences in their surrounds of more than a hundred times.

Mobile wireless ad hoc networks (MANETs) naturally support a traffic mix of elastic and real-time flows but the shared nature and lossy properties of the radio medium make their coexistence challenging. We argue in this paper for a new kind of elastic data transport service which would preserve the quality of real-time priority flows while guaranteeing an acceptable (tunable) end-to-end delivery time of elastic data. We propose to use mechanisms from Delay Tolerant Networking (DTN) to support hop-by-hop data transfer from source to destination and an adaptation of TCP which monitors its aggressiveness towards local VoIP traffic on each hop. The scheme is evaluated in simulation on a simple 4-node scenario and in a more realistic case where doubling data transfer time allows for the support of seven VoIP flows of medium quality against none for standard TCP.

We analyze the dynamics of a mobility dataset collected in a pipelined disruption-tolerant network (DTN), a particular class of intermittently-connected wireless networks characterized by a one-dimensional topology. First, we collected and investigated traces of contact times among a thousand participants of a rollerblading tour in Paris. The dataset shows extreme dynamics in the mobility pattern of a large number of nodes. Most strikingly, fluctuations in the motion of the rollerbladers cause a typical accordion phenomenon - the topology expands and shrinks with time, thus influencing connection times and opportunities between participants. Second, we show through an analytical model that the accordion phenomenon, through the variation of the average node degree, has a major impact on the performance of epidemic dissemination. Finally, we test epidemic dissemination and other existing forwarding schemes on our traces, and argue that routing should adapt to the varying, though predictable, nature of the network. To this end, we propose DA-SW (density-aware spray-and-wait), a measurement-oriented variant of the spray-and-wait algorithm that tunes, in a dynamic fashion, the number of a message copies disseminated in the network. We show that DA-SW leads to performance results that are close to the best case (obtained with an oracle).

In this paper we address the issue of designing a routing scheme for ad hoc networks, which aims at maximizing the number of flows with satisfied bandwidth demands. In general, selecting a multi-hop wireless path for bandwidth-guaranteed flows is challenging because of the broadcast nature of the wireless medium. Thus, in this study we formulate the route selection problem by considering a synchronized multi-rate TDMA access scheme. Once the route is found, the radio resources are reserved as time slots in the TDMA frames along the path the flow takes. We demonstrate that selecting routes so as to maximize the number of accepted flows is an APX-complete problem (i.e., there are no polynomial-time approximation schemes), even under simplified rules for bandwidth reservation. This result is stronger than previously established in other studies. Guided by our analysis, we propose a new cumulated available resources and Topology Aware (CARTA) routing heuristic, which selects routes bypassing heavily loaded and highly interfered network regions. Simulations performed with random topologies of up to 100 nodes and various traffic configurations show that CARTA obtains a more balanced utilization of the network resources, and up to 25% capacity increase than the second best metric from the literature we tested, at the cost of a limited increase in path lengths.

In this paper we propose HYMAD, a hybrid DTN-MANET routing protocol which uses DTN between disjoint groups of nodes while using MANET routing within these groups. HYMAD is fully decentralized and only makes use of topological information exchanges between the nodes. We evaluate the scheme in simulation by replaying real life traces which exhibit this highly dynamic connectivity. The results show that HYMAD outperforms the multi-copy Spray-and-Wait DTN routing protocol it extends, both in terms of delivery ratio and delay, for any number of message copies. Our conclusion is that such a hybrid DTN-MANET approach offers a promising venue for the delivery of elastic data in mobile ad-hoc networks as it retains the resilience of a pure DTN protocol while significantly improving performance.

The purpose of this work is to bridge the gap between high-end networked devices and wireless networks of ubiquituous and resource-constrained sensors and actuators by extensively applying Service-Oriented Architecture (SOA) patterns. We present a multi-level approach that implements existing SOA standards on higher tiers, and propose a novel protocol stack, WSN-SOA, which brings the benefits of SOA to low capacity nodes without the overhead of XML-based technologies. This solution fully supports network dynamicity, auto-configuration, service discovery, device heterogeneity and interoperability with legacy architectures. As a proof-of-concept, we have studied a surveillance scenario in which the detection of an intruder, conducted within the range of a network of wireless sensors (e.g., MICAz from Crossbow), leads to the automatic triggering of tracking activities by a Linux-powered network camera and of alerts and video streams toward a control room.

In wireless mesh networks (WMNs) traffic is routed from mobile clients through a multihop wireless backbone to and from Internet gateways (IGWs). Because of their limited number, IGWs become the major traffic bottlenecks. The purpose of this work is to explore the benefits of introducing load-dependent routing metrics to increase WMN capacity and performance. We use weighted shortest path routing and introduce LAETT a weight metric that captures both traffic load and link quality. We compare the scheme to ETT and MIC, two load independent metrics, and show in simulation its benefits for various network and traffic configurations.

We propose in this work a single copy and multi-hop opportunistic routing scheme for sparse delay tolerant networks (DTNs). The scheme uses as only input the estimates of the average inter-contact times between the nodes in the network. Defined as the fixed point of a recursive process, it aims at minimizing delivery time in case of independent exponential pairwise inter-contacts. The two properties of loop-free forwarding and polynomial convergence make the scheme workable for routing in DTNs. The routing performances of the scheme are evaluated on three publicly available reference data sets. Comparisons with well known single-copy schemes, including MED and thetwohoprelay strategy, consistently demonstrate improvements for both delivery ratio and delay.

We consider the challenge of enhancing sensor networks for surveillance and global security with increased distributed data processing capabilities, including multi-sensor fusion, data aggregation or mining, and rule-based alert generation. We advocate a novel architecture that will enable the creation of more resilient and complex monitoring applications. We exemplify its benefits in a chemical accident scenario. The architecture introduces new processing nodes in the field and derives the requirements for the software they will run. We propose to consider the use of a service oriented architecture (SOA) to program and deploy the data processing applications. We analyze existing and on-going work within the Web Services community and conclude that it is possible to implement the architecture with an appropriate combination of COTS (commercial off-the-shelf software components). We conclude with our plans to move forward in this direction and validate the approach on a hardware and software testbed.

Abstract Because a delay‐tolerant network (DTN) can often be partitioned, routing is a challenge. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high‐dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and a large‐scale evaluation of routing schemes using MobySpace by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visits of nodes to each possible location. We present simulation results for single‐copy and multi‐copy routing strategies that use MobySpace as a means to route bundles or to control flooding. We show that routing based on MobySpace can achieve good performance compared to a number of common algorithms. Copyright © 2007 John Wiley & Sons, Ltd.

Because a delay tolerant network (DTN) can often be partitioned, routing is a challenge. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high-dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and a large scale evaluation of this routing scheme in the context of ambient networking by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visits of nodes to each possible location. We show that routing based on MobySpace can achieve good performance compared to that of a number of standard algorithms, especially for nodes that are present in the network a large portion of the time. We determine that the degree of homogeneity of node mobility patterns has a high impact on routing. And finally, we study the ability of nodes to learn their own mobility patterns.

We present a suitable virtually documented environment system providing the user with high level interaction possibilities. The system is dedicated to applications where the operator needs to have his hands free in order to access information, carry out measurements and/or operate on a device (e.g. maintenance, instruction). The system merges video images acquired through a head‐mounted video camera with synthetic data (multimedia documents including CAD models and text) and presents these merged images to the operator. Registration techniques allow the operator to visualise information properly correlated to the real world: this is an essential aspect in order to achieve a feeling of presence in a real environment. We increase the sense of immersion through high level Human‐Computer Interaction (HCI) allowing hands‐free access to information through vocal commands as well as multimodal interaction associating speech and gesture. In this way, the user can access information and manipulate it in a very natural manner. We discuss the construction of the documentation system and the requested functionalities which led to the system architecture.