In the current telecommunications market that is reaching high saturation levels, mobile network operators (MNOs) try to position themselves among customers through aggressive marketing campaigns and offers. In this environment where customers have multiple MNOs to choose from, different factors influence customers’ decisions. In addition to this, mobile number portability contributes to a phenomenon called churning where customers migrate from one MNO to another. Churning impacts not only the network design but also the pricing methods adopted by MNOs, and hence their revenue. It is because of this that MNOs try to reduce churn through retention campaigns. The key factor for the success of these campaigns is to detect potential churners before they leave the service. The state of the art has focused on proposing methods to identify churners based on data mining techniques, however these techniques doesn’t always offer clear explanations for churn reasons. Instead, we use a technique called agent-based modeling to model customers in the mobile telecommunication market and assess the effects of customers characteristics and behaviors on such market. We propose a model that includes some relevant demographic and psychographic characteristics and the utilizations of usage profiles to describe customers. We show with simple experiments how different factors lead to churn in different ways. We believe the proposed approach is useful because MNOs can use it for explanatory, exploratory and predictive purposes.
This paper presents an asynchronous cascading wake-up MAC protocol for heterogeneous traffic gathering in low-power wireless sensor networks. It jointly considers energy/delay optimization and switches between two modes, according to the traffic type and delay requirements. The first mode is high duty cycle, where energy is traded-off for a reduced latency in presence of realtime traffic (RT). The second mode is low duty cycle, which is used for non-realtime traffic and gives more priority to energy saving. The proposed protocol, DuoMAC, has many features. First, it quietly adjusts the wake-up of a node according to (1) its parent’s wake-up time and, (2) its estimated load. Second, it incorporates a service differentiation through an improved contention window adaptation to meet delay requirements. A comprehensive analysis is provided in the paper to investigate the effectiveness of the proposed protocol in comparison with some state-of-the-art energy-delay efficient duty-cycled MAC protocols, namely DMAC, LL-MAC, and Diff-MAC. The network lifetime and the maximum end-to-end packet latency are adequately modeled, and numerically analyzed. The results show that LL-MAC has the best performance in terms of energy saving, while DuoMAC outperforms all the protocols in terms of delay reduction. To balance the delay/energy objectives, a runtime parameter adaptation mechanism has been integrated to DuoMAC. The mechanism relies on a constrained optimization problem with energy minimization in the objective function, constrained by the delay required for RT. The proposed protocol has been implemented on real motes using MicaZ and TinyOS. Experimental results show that the protocol clearly outperforms LL-MAC in terms of latency reduction, and more importantly, that the runtime parameter adaptation provides additional reduction of the latency while further decreasing the energy cost.
In body sensor networks (BSNs), energy-constrained sensors monitor the vital signs of human beings in healthcare applications. Energy consumption is a fundamental issue, since BSNs must operate properly and autonomously for long period of time without battery recharge or replacement. In addition, the human exposure to electromagnetic radiation must be limited. For all these reasons, the energy consumption in BSNs should be minimized. In this paper, sensor and gateway location optimization for BSNs has been analyzed. A mathematical model has been proposed to minimize the energy consumption of the BSN and the heating effects on human tissues. We distinguish between 'in-body' and 'on-body' sensors depending on their location inside or outside the human body, respectively. The theoretical analysis and the numerical results reveal that in in-BSNs the energy consumption can be significantly reduced when the optimal positions of the gateway or the sensors are computed. However, in on-BSNs the energy consumption is not affected by the devices' location. With power control the interferences are minimized and the human exposure to electromagnetic radiation is reduced.
Nanotechnology is enabling the development of devices in a scale ranging from a few to hundreds of nanometers. Communication between these devices greatly expands the possible applications, increasing the complexity and range of operation of the system. In particular, the resulting nanocommunication networks (or nanonetworks) show great potential for applications in the biomedical field, in which diffusion-based molecular communication is regarded as a promising alternative to EM-based solutions due to the bio-stability and energy-related requirements of this scenario. However, molecular signals suffer a significant amount of attenuation as they propagate through the medium, thus limiting the transmission range. In this paper, a signal amplification scheme for molecular communication nanonetworks is presented wherein a group of emitters jointly transmits a given signal after achieving synchronization. This is achieved by means of quorum sensing (QS), a method used by bacteria to both sense their population and coordinate their actions. By using the proposed methodology, the transmission range is extended proportionally to the number of synchronized emitters. An analytical model of QS is provided and validated through simulation. This model is the main contribution of this work and accounts for the activation threshold (which will eventually determine the resulting amplification level) and the delay of the synchronization process.
The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.
The fundamental features of cognitive radio (CR) systems are their ability to adapt to the wireless environment where they operate and their opportunistic occupation of the licensed spectrum bands assigned to the primary network. CR users in CR systems should not cause any interference to primary users (PUs) of the primary network. For this purpose, CR users need to accurately estimate the features and activities of the primary users. In this paper, a novel characterization of heterogeneous PUs and a novel reconfigurability solution in CR networks are introduced. The characterization of PUs consists of a detector and classifier that distinguishes between heterogenous PUs. The PU characteristics stored in radio environmental maps are utilized by an interference/throughput adapter for the optimization of CR parameters. The performance of the proposed solutions is evaluated by showing false alarm and missed detection probabilities of the detector/classifier in a multipath fading channel with additive white Gaussian noise. Moreover, the impact of the PU characteristics on the CR throughput is analyzed.
The efficient utilization of radio resources is a fundamental issue in cognitive radio (CR) networks. Thus, a novel cognitive radio resource management (RRM) is proposed to improve the spectrum utilization efficiency. An optimization framework for RRM is developed that makes the following contributions: (i) considering heterogeneous primary users (PUs) with multiple features stored in a radio environment map database, (ii) allowing variable CR demands, (iii) assuring interference protection towards PUs. After showing that the optimal solution is computationally infeasible, a suboptimal solution is consequently proposed. Performance evaluation is conducted in terms of total achieved data rate and satisfaction of CR requirements.
The efficient utilization of radio resources is a
fundamental issue in cognitive radio (CR) networks. Thus, a
novel cognitive radio resource management (RRM) is
proposed to improve the spectrum utilization efficiency. An
optimization framework for RRM is developed that makes
the following contributions: (i) considering heterogeneous
primary users (PUs) with multiple features stored in a radio
environment map database, (ii) allowing variable CR
demands, (iii) assuring interference protection towards PUs.
After showing that the optimal solution is computationally
infeasible, a suboptimal solution is consequently proposed.
Performance evaluation is conducted in terms of total
achieved data rate and satisfaction of CR requirements.
Clustering in sensor networks provides energy conservation, network scalability, topology stability, reducing overhead and also allows data aggregation and cooperation in data sensing and processing. Wireless Multimedia Sensor Networks are characterized for directional sensing, the Field of View (FoV), in contrast to scalar sensors in which the sensing area usually is more uniform. In this paper, we first group multimedia sensor nodes in clusters with a novel cluster formation approach that associates nodes based on their common sensing area. The proposed cluster formation algorithm, called Multi-Cluster Membership (MCM), establishes clusters with nodes that their FoVs overlap at least in a minimum threshold area. The name of Multi-Cluster Membership comes from the fact that a node may belong to multiple clusters, if its FoV intersects more than one cluster-head and satisfies the threshold area. Comparing with Single-Cluster Membership (SCM) schemes, in which each node belongs to exactly one cluster, because of the capability of coordination between intersected clusters, MCM is more efficient in terms of energy conservation in sensing and processing subsystems at the cost of adding complexity in the node/cluster coordination. The main imposed difficulty by MCM, is the coordination of nodes and clusters for collaborative monitoring; SCMs usually assign tasks in a round-robin manner. Then, as second contribution, we define a node selection and scheduling algorithm for monitoring the environment that introduces intra and inter-cluster coordination and collaboration, showing how the network lifetime is prolonged with high lifetime prolongation factors particularly in dense deployments.
Wireless sensor networks (WSNs) are made up
of large groups of nodes that perform distributed monitoring
services. Since sensor measurements are often sensitive
data acquired in hostile environments, securing WSN
becomes mandatory. However, WSNs consists of low-end
devices and frequently preclude the presence of a centralized
security manager. Therefore, achieving security is
even more challenging. State-of-the-art proposals rely on:
(1) attended and centralized security systems; or (2)
establishing initial keys without taking into account how to
efficiently manage rekeying. In this paper we present a
scalable group key management proposal for unattended
WSNs that is designed to reduce the rekeying cost when
the group membership changes.
Link Adaptation is a radio resource management
technique that assesses the channel conditions and
selects a transport mode, from a set of possible options,
which is optimised for these conditions according to a
predefined criterion. The optimum transport mode is
commonly determined so as to maximise the throughput.
Although this approach may be appropriate for best-effort
services, its suitability for multimedia services, usually
characterised by tight delay and error performance constraints,
has been questioned. As a result, a number of
alternative algorithms have been proposed in the literature.
In this context, this paper presents and evaluates in a
dynamic radio environment several Link Adaptation algorithms
designed to enhance the provision of delay- and
error-sensitive multimedia packet-data services over wireless
systems. The obtained results demonstrate that
significant improvements in terms of throughput, transmission
delay, error performance and operation of Link
Adaptation itself can be obtained with the proposed
This paper presents a novel methodology for capturing the coupling between the different cells in both the uplink and downlink directions in a Wideband Code Division Multiple Access (WCDMA) scenario. It is based on the definition and computation of the gradient of the uplink cell load factor and the downlink transmitted power, which are the two main parameters that reflect the actual cell load in the two link directions. The paper shows that the gradient is able to capture the relevant information about the spatial distribution of traffic, which has an impact on cell performance. The proposed methodology is also used as the basis for defining and evaluating new Radio Resource Management (RRM) strategies that operate at a multi-cell level.