Software-Defined Networking is gaining increasing interest in the academic and the industrial communities alike. SDN principles call for commodity networking devices and for shifting all intelligence to a logically centralized controller. In this demo we build on a programmable enterprise WLAN platform in order to implement and deploy a location analytics solution to be used in shopping malls, airports, and similar venues for location-based advertisement and visitors profiling. Our solution can run on commodity devices and in many cases can be adapted to run over an existing WLAN infrastructure.

Ubiquity of internet-connected media-and sensor-equipped portable devices has emerged a range of opportunities for direct involvement of citizens into public decision making, leading to a new participatory format of public administration functioning. Intersecting the power of the crowdsourcing problem-solving paradigm by directly relying on human intelligence, with instantaneity and situation-awareness of mobile technologies, one gets a context-aware crowdsourcing approach for problem-solving in the right circumstances with the right people. In this paper, we present a prototype implementation of a context-aware mobile crowdsourcing system that enables the deployment and execution of crowdsourcing campaigns with users carrying mobile devices. The system is designed to maximize conditions for user participation, while minimizing the usage of energy. The paper describes the system architecture, defines an optimized sampling algorithm, and outlines a preliminary experimentation study carried out.

As the number and capabilities of mobile devices is rapidly increasing, new challenges arise in the way services are currently designed. Users are seeking for more complex and advanced functionalities able to satisfy their increasing requirements. As a consequence, in ubiquitous environments, a different way to design services has to be introduced in order to guarantee services always up to date in a transparent and efficient way. In this paper, we present and analyze a framework for distributed cooperative service evolution in a wireless nomadic environment. In particular, we assume a disconnected network architecture, where users' mobility is exploited to achieve a scalable behavior, and communication is based on localized peer-to-peer interactions among neighboring nodes. Service management is achieved by introducing autonomic services, whose operations are based on a distributed evolution process, which draws tools and concepts from evolutionary computation (and genetic algorithms in particular). The latter relies on the concept of recombination , i.e., the exchange of information among service users, which collaborate to enhance their fitness , defined as the ability of the actual service to fulfill user's requirements. We introduce a general framework for analyzing service recombination policies and exploit results from martingales theory to study their convergence properties.

Technology is taking us to a world where myriads of heavily networked devices interact with the physical world in multiple ways, and at multiple scales, from the global Internet scale down to micro- and nano-devices. Many of these devices are highly mobile and autonomous, and must adapt to the surrounding environment in a totally distributed and unsupervised way. fundamental research challenge is the design of robust decentralized computing systems, which are capable of operating under changing environments, and yet exhibit the desired behavior and response time, under unpredictable operating constraints, such as traffic demand, energy consumption, size, and processing power. These systems should be able to adapt and learn how to react to unforeseen scenarios, as well as to display desired emergent properties.

The technology world is experiencing the emergence of a generation of massive-scale networked digital systems, performing complex operations that are partially out of the control of the systems' designers. This is the case, e.g., of pervasive computing environments, characterized by the proliferation of embedded electronic devices with communication and computing capabilities, able to network themselves forming a “digital halo” surrounding the user in its daily activities. In this paper, we advocate the use of bottom-up design patterns, able to build on results in complex systems science and systems biology, for devising new solutions for designing and managing such environments. We also present a possible application to a novel cyberphysical ecosystem, that we call the Energy Web, arising from the combination of innovative information and communication technologies with distributed renewable energy sources.

This paper addresses the design and performance evaluation of relay strategies for opportunistic Delay Tolerant Networks (DTNs) augmented with throwboxes. By opportunistic we mean that a node does not have any knowledge regarding its past and future contact opportunities with the other nodes. We consider a network model composed of both mobile relay nodes and throwboxes, where throwboxes are stationary wireless devices acting simply as fixed relays. We propose and evaluate various relay strategies, where the goal is to take advantage of the presence of throwboxes to minimize resources consumption at mobile nodes. Under Markovian assumptions we introduce a mathematical framework which allows us to calculate the main performance metrics (average delivery delay, overhead, etc.) of each proposed relay scheme. The obtained results highlight the various trade-offs that are left to network designers when adding throwboxes to a DTN, and draw insights on the effectiveness of these strategies.

Distributed estimation of global parameters in intermittently connected mobile environments is a challenging problem. In this paper, we introduce a set of methods, based on gossip techniques and population protocols, for performing such task. The applicability of such techniques to various environments, characterized by different mobility patterns, is evaluated through numerical simulations and discussed extensively. Guidelines are provided to help practitioners choosing the right method for their specific application problem.

This paper deals with the problem of supporting sink mobility in a wireless sensor network. It focuses on a specific scenario, where mobile nodes act themselves as both end-users, when querying the WSN for specific information, and as sinks, when gathering the queried data. Due to the mobility of users and to the topology of the network, sinks experience frequent disconnections from the WSN. A system architecture, and the related protocols, capable of supporting the envisioned application domain has been proposed. The performance of the proposed system architecture has been evaluated by means of simulative studies, together with addressing the impact of mobility, deployment geometry and routing parameters.

This paper deals with a system level design solution to support information gathering in the presence of a mobile querying node that experiences frequent disconnections from a Wireless Sensor Network (WSN), an application scenario that embraces the area of Intelligent Transportation Systems (ITS). The proposed scheme basically relies on the network capability of autonomously adapting to sink mobility in order to properly deliver the requested data. The system is defined as far as its functional elements and related communications protocols, together with validating its effectiveness by means of a simulative study. In particular, the performance in terms of delivering latency and packet delivery ratio has been investigated for several network topologies, architecture and mobility pattern, always highlighting a remarkable quality of provided services together with robustness with regard to operative conditions.

Recently, research on disconnected networks has been fostered by several studies on delay-tolerant networks, which are designed in order to sustain disconnected operations. We focus on the emerging notion of connectivity which exists in such networks, where the message exchange between nodes is enforced by leveraging storage capabilities at intermediate relays, with the aim of achieving connectivity over time. The problem, under the constraint of intermittent connectivity, is hence to devise efficient mechanisms for message delivery, and evaluate the performance thereof. In this paper, we introduce a graph-based model able to capture the evolution of the connectivity properties of such systems over time. We show that, for most networks of interest, such connectivity graphs can be modeled as Erdos-Renyi random graphs. Furthermore, we show that, under a uniformity assumption, the time taken for the connectivity graph to become connected scales as Theta((n log n)/lambda) with the number of nodes in the network. Hence we found that, using epidemic routing techniques, message delay is O((n log2n)/(lambda log log n)). The model is validated by numerical simulations and by a comparison with the connectivity patterns emerging from real experiments.

In this work, we introduce a framework to let forwarding schemes evolve in order to adapt to changing and a priori unknown environments. The framework is inspired by genetic algorithms: at each node a genotype describes the forwarding scheme used, a selection process fosters the diffusion of the fittest genotypes in the system and new genotypes are created by combining existing ones or applying random changes. A case study implementation is presented and its performance evaluated via numerical simulations.

This demonstration presents a data-centric opportunistic dissemination platform. The proposed platform achieves system wide delivery of data exploiting opportunistic communications among mobile nodes. The prototype is developed over java-enabled smartphones and relies on Bluetooth connectivity for achieving proximity communications. The platform is described in all its functional components, together with the details of its software implementation.

In this work, we present a multi-resolution data management scheme for efficiently storing and diffusing information, which is originating from sensors and augmenting mobile applications. The proposed mechanism exploits the discrete wavelet transform properties for providing a location-dependent data management scheme, which alleviates the constraints on the storage resources needed for running context-aware mobile applications. The data management scheme has been implemented and evaluated by means of numerical simulations.

The emergence of future pervasive ICT environments, characterized by the massive proliferation of embedded electronic devices with communication and computing capabilities, are posing enormous challenges to existing approaches to networking, service provisioning and system management. In this paper, we make a case to go for biology as possible source of novel, revolutionary design patterns suitable to large-scale highly dynamic ICT systems. We also present a case study, the EU- funded BIONETS project, which tackles the increased complexity of large-scale ubiquitous systems by applying an evolutionary framework to the provisioning of pervasive services.

Several recent studies have addressed the suitability of current wireless technologies for industrial communications which, frequently, are requested to cope with severe timing constraints. Most of the analysis that have lately appeared in the literature have focused on the performance offered by the lower layers of the communication stack. However, in order to obtain a complete picture, it is important to analyze how this gets coupled with the features of higher layer protocols typically employed by industrial communication applications. In this paper, we investigate the performance obtained by an application layer protocol, derived from those currently employed by wired fieldbuses, running over COTS devices based on two popular wireless communication standards, namely, IEEE 802.15.4 and IEEE 802.11. In particular, we present a mapping of the application service elements onto the services offered by the mentioned wireless systems and discuss some possible design choices. A prototype of the application layer protocol is then implemented for each considered wireless technology and the performance figures evaluated by means of experimental measurements.

Current wireless technologies offer a viable solution for implementing communication systems capable of satisfying the severe timing requirements often required for operations at the lowest levels of factory automation systems. Most of the contributions appeared in the literature on this subject aimed at investigating the suitability to industrial applications of some wireless communication protocols. In this paper, we address the problem from a different perspective. Namely, we are interested in characterizing the application layer performance of a field-bus protocol running over an IEEE 802.11g-based wireless LAN. We provide a preliminary Java-based implementation of such application protocol, and test it on laptops running a Linux operating system and off-the-shelf 802.11 cards. The performance of the application layer protocol are extensively tested on an experimental system characterized by environmental conditions similar to those of industrial installations.

In this paper, we analyze the performance of a family of opportunistic forwarding schemes (the K-copy relaying strategies) over disconnected wireless networks. We introduce a classification of mobility models based on their dynamic properties, and characterize the M2(marks-memory less) class. Statistical tools are combined with numerical simulations to show that some of the most used mobility models in the literature fall within the M2class. A mathematical framework is provided for evaluating the performance of opportunistic forwarding schemes in the presence of M2mobility, and it is shown that the finiteness of the mean time necessary to deliver a message depends only on the mobility characteristics and not on the relaying protocol specification