Urban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven approaches in urban computing have emerged for researchers and companies. They aim to address historical urbanization issues by exploiting sensing data gathered by mobile devices under the so-called mobile crowdsensing (MCS) paradigm. This work shows how to exploit sensing data to improve traditionally experience-based approaches for urban decisions. In particular, we apply widely known Machine Learning (ML) techniques to achieve highly accurate results in predicting categories of local businesses (LBs) (e.g., bars, restaurants), and their attractiveness in terms of classes of temporal demands (e.g., nightlife, business hours). The performance evaluation is conducted in Luxembourg city and the city of Munich with publicly available crowdsensed datasets. The results highlight that our approach does not only achieve high accuracy, but it also unveils important hidden features of the interaction of citizens and LBs.

The huge increase of population living in cities calls for a sustainable urban development. Mobile crowdsensing (MCS) leverages participation of active citizens to improve performance of existing sensing infrastructures. In typical MCS systems, sensing tasks are allocated and reported on individual-basis. In this paper, we investigate on collaboration among users for data delivery as it brings a number of benefits for both users and sensing campaign organizers and leads to better coordination and use of resources. By taking advantage from proximity, users can employ device-to-device (D2D) communications like Wi-Fi Direct that are more energy efficient than 3G/4G technology. In such scenario, once a group is set, one of its member is elected to be the owner and perform data forwarding to the collector. The efficiency of forming groups and electing suitable owners defines the efficiency of the whole collaborative-based system. This paper proposes three policies optimized for MCS that are compliant with current Android implementation of Wi-Fi Direct. The evaluation results, obtained using CrowdSenSim simulator, demonstrate that collaborative-based approaches outperform significantly individual-based approaches.

The Internet of Things (IoT) paradigm makes the Internet more pervasive. IoT devices are objects equipped with computing, storage and sensing capabilities and they are interconnected with communication technologies. Smart cities exploit the most advanced information technologies to improve public services. For being effective, smart cities require a massive amount of data, typically gathered from sensors. The application of the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms and to produce a large amount of data following Sensing as a Service (S2aaS) business models. Having citizens involved in the process through mobile crowdsensing (MCS) techniques unleashes potential benefits as MCS augments the capabilities of existing sensing platforms. To this date, it remains an open challenge to quantify the costs the users sustain to contribute data with IoT devices such as the energy from the batteries and the amount of data generated at city-level. In this paper, we analyze existing solutions, we provide guidelines to design a large-scale urban level simulator and we present preliminary results from a prototype.

The Automatic Identification System is a universal shipborne system adopted to improve safety at sea and efficiency of navigation. This system allows to identify and localize vessels in a short range for collision avoidance by exchanging messages with navigational information.

The convergence of iterative decoding schemes utilizing belief propagation is considered. A quantitative bound for the output L-values of a Turbo decoder is given that only depends on the received word and thus is independent from the decoder iterations. Further, it is shown that the exponential increase of the L-values in each iteration within an LDPC decoder is limited by the degree of the variable nodes.

This contribution aims to show how path diversity can reduce the high variability of the Internet traffic. We attempt to improve the traffic behavior of a connection between two network entities. The most used transmission protocols as TCP and UDP are not capable to carry out all the traffic generated by the Internet as they lead to congestion and packet loss out of the connections required QoS. We present here the state of our research based on the discovery of disjoint connection paths on a network topology. We have designed a new transmission protocol that takes advantage of route diversity. We propose a TCP protocol based on Multiple Paths MPTCP for a data transmission between two network entities in a well-defined environment. Multipath routing and multipath transport protocols seem to be a relevant solution to avoid the drawbacks generated by the use of a single path for each data connection. MPTCP aims to avoid or reduce the congestions appearance and the high variability of the Internet traffic. A simulator has been developed on top of Scilab in order to evaluate the gain provided by the route diversity.

A common technique to deploy linear prediction to non-stationary signals is time segmentation and local analysis. Variations of a process within such a segment cause inaccuracies. In this paper, we model the temporal changes of linear prediction coefficients (LPCs) as a Fourier series. We obtain a compact description of the vocal tract model limited by the predictor order and the maximum Doppler frequency. Filter stability is guaranteed by all-pass filtering, deploying the human ear's insensitivity to absolute phase. The periodicity constraint induced by the Fourier series is counteracted by oversampling in the Doppler domain. With this approach, the number of coefficients required for the vocal tract modeling is significantly reduced compared to a LPC system with block-wise adaptation while exceeding its prediction gain. As a by-product it is found that the Doppler frequency of the vocal tract is in the order of 10 Hz. A generalization of the algorithm to an auto-regressive moving average model with time-correlated filter coefficients is straight forward.

Decisions on sources with memory transmitted over independent channels can be taken by employing trellis calculations. In this paper, it is shown that for a certain class of functions their moments can be computed in the trellis, too. This is done by generalizing the forward/backward recursion known from the BCJR algorithm [1]. In analogy to the symbol probabilities, by introducing a constraint at a certain depth in the trellis we obtain symbol moments. These moments are required for an efficient implementation of the discriminated belief propagation algorithm in [2], and can furthermore be utilized to compute conditional entropies in the trellis. The moment computation algorithm has the same asymptotic complexity as the BCJR algorithm. It is applicable to any commutative semi-ring, thus also providing a generalization of the Viterbi algorithm [3].

In this paper we present a protocol for unlinkable communication, i.e. where an attacker cannot map the sender and receiver node of a communication. Existing anonymity protocols either do not guarantee unlinkability (e.g. Tor and Mix networks), or produce huge overhead -- the dining cryptographers network causes quadratic number of messages. Our protocol needs only a linear number of messages while it still guarantees unlinkability. We introduce a measure of unlinkability and show that our protocol offers the highest possible degree of unlinkability. We show how to use the protocol in practice by adapting it to Internet and ad hoc communication.

This contribution is attempting to show how a route diversity can improve the traffic behavior of a connection between two network entities. The most used transmission protocols TCP and UDP control the quasi-totality of the Internet traffic. However they are not capable to carry out all the traffic generated by the Internet as they lead to congestion and packet loss out of the quality of service required specially for critical connections that need to be treat with a higher priority. In this paper, we focus on multipath routing and multipath transport protocols that seem to be a relevant solution to avoid the drawbacks generated by the use of a single path by each connection packet. Pushing connection packets on multiple paths during all the data transaction should bring a better QoS. We mention a new protocol design for the next generation Internet. This protocol has been developed in order to avoid or reduce the congestions appearance and the high variability of the Internet traffic. We suggest a TCP protocol based on Multiple Paths MPTCP for a data transmission between two network entities in a well-defined environment. A simulator has been developed in order to evaluate the gain provided by the route diversity.

The paper deals with coding for direct-sequence code-division multiple-access (DS-CDMA) channels. A novel method for interleaver design is introduced which significantly improves the probability of error on Gaussian multiple-access channels. It is theoretically shown for a certain kind of interleaving and finite code length that almost the complete influence of interuser interference can be eliminated. Hence, the performance of a coded DS-CDMA system comes close to transmission without interuser interference. Simulations are used to confirm the analysis.

A new spread-spectrum multiple-access scheme applicable for both the uplink and the downlink of a mobile radio communications system is proposed, which is termed "interleaved frequency-division multiple-access". This scheme combines the advantages of spread-spectrum and multicarrier transmission. Moreover, it can be viewed as a special kind of a multicarrier spread-spectrum scheme where user discrimination is carried out using frequency-division multiple-access. The multiple-access capability is achieved by assigning to each user a different set of orthogonal subcarriers. The orthogonality between the different users is maintained at the receiver, even in time-dispersive channels resulting in no multiple-access interference. However, the cost to avoid multiple-access interference is to allow for intersymbol interference and therefore equalization is required at the receiver.

Proposes a modification of generalized concatenated codes, which allows to construct some of the best known binary codes in a simple way. Furthermore, a large class of optimal linear unequal error protection codes (LUEP codes) can easily be generated. All constructed codes can be efficiently decoded by the Blokh-Zyablov-Zinov'ev algorithm if an appropriate metric is used.>

We propose an algorithm for bounded minimum distance decoding of (partial) unit memory codes up to half the "designed" extended row distance. It makes use of a reduced trellis with the nodes found by bounded minimum distance decoding of the block codes used in the unit memory code. The results can be extended to general multimemory codes. The complexity of this algorithm is upper bounded by 2(d~/sub 1sup r/-2d/sub /spl alpha) times the complexity of the bounded minimum distance decoder of the block codes in the unit memory code. Here d/sub /spl alpha is the linear increase of the designed extended row distance d~/sub isup r/.>

A Reed-Solomon code decoding algorithm based on Newton's interpolation is presented. This algorithm has as main application fast generalized-minimum-distance decoding of Reed-Solomon codes. It uses a modified Berlekamp-Massey algorithm to perform all necessary generalized-minimum-distance decoding steps in only one run. With a time-domain form of the new decoder the overall asymptotic generalized-minimum-distance decoding complexity becomes O(dn), with n the length and d the distance of the code (including the calculation of all error locations and values). This asymptotic complexity is optimal. Other applications are the possibility of fast decoding of Reed-Solomon codes with adaptive redundancy and a general parallel decoding algorithm with zero delay.>