Jocelyne Elias

Energy-aware topology design for wireless body area networks

Wireless Body Area Networks (WBANs) represent one of the most promising approaches for improving the quality of life, allowing remote patient monitoring and other healthcare applications. In such networks, traffic routing plays an important role together with the positioning of relay nodes, which collect the information from biosensors and send it towards the sinks. This work investigates the optimal design of wireless body area networks by studying the joint data routing and relay positioning problem in a WBAN, in order to increase the network lifetime. To this end, we propose an integer linear programming model which optimizes the number and location of relays to be deployed and the data routing towards the sinks, minimizing both the network installation cost and the energy consumed by wireless sensors and relays. We solve the proposed model in realistic WBAN scenarios, and discuss the effect of different parameters on the characteristics of the planned networks. Numerical results demonstrate that our model can design energy-efficient and cost-effective wireless body area networks in a very short computing time, thus representing an interesting framework for the WBAN planning problem.

Optimal design of energy-efficient and cost-effective wireless body area networks

Wireless Body Area Networks (WBANs) represent one of the most promising approaches for improving the quality of life, allowing remote patient monitoring and other healthcare applications. The deployment of a WBAN is a critical issue that impacts both the network lifetime and the total energy consumed by the network. This work investigates the optimal design of wireless body area networks by studying the joint data routing and relay positioning problem, in order to increase the network lifetime. To this end, we propose a mixed integer linear programming model, the Energy-Aware WBAN Design model, which optimizes the number and location of relays to be deployed and the data routing towards the sink, minimizing both the network installation cost and the energy consumed by wireless sensors and relays. We solve the proposed model in both realistic WBAN scenarios and general topologies, and compare the model performance to the most notable approaches proposed in the literature. Numerical results demonstrate that our model (1) provides a good tradeoff between the energy consumption and the number of installed relays, and (2) designs energy-efficient and cost-effective WBANs in a short computation time, thus representing an interesting framework for the dynamic WBAN design problem.

Non-cooperative spectrum access in cognitive radio networks: A game theoretical model

Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the primary operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. Furthermore, we consider both non-elastic and elastic user traffic, to model real-time as well as data transfer applications. Finally, we consider an alternative formulation of the spectrum access problem, where players use replicator dynamics to adjust their strategies, and we derive convergence conditions to Nash equilibrium points. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.

Cross-Technology Interference Mitigation in Body Area Networks: An Optimization Approach

In recent years, wearable devices and wireless body area networks have gained momentum as a means to monitor peoples behavior and simplify their interaction with the surrounding environment, thus representing a key element of the body-to-body networking (BBN) paradigm. Within this paradigm, several transmission technologies, such as 802.11 and 802.15.4, that share the same unlicensed band (namely, the industrial, scientific, and medical band) coexist, dramatically increasing the level of interference and, in turn, negatively affecting network performance. In this paper, we analyze the cross-technology interference (CTI) caused by the utilization of different transmission technologies that share the same radio spectrum. We formulate an optimization model that considers internal interference, as well as CTI to mitigate the overall level of interference within the system, explicitly taking into account node mobility. We further develop three heuristic approaches to efficiently solve the interference mitigation problem in large-scale network scenarios. Finally, we propose a protocol to compute the solution that minimizes CTI in a distributed fashion. Numerical results show that the proposed heuristics represent efficient and practical alternatives to the optimal solution for solving the CTI mitigation (CTIM) problem in large-scale BBN scenarios.

A Priority based Cross Layer Routing Protocol for healthcare applications

Wireless body area networks (WBANs) represent one of the most promising approaches for improving the quality of life, allowing remote patient monitoring and other healthcare applications. Data dissemination and medium access in a WBAN are critical issues that impact the network reliability, the efficiency and the total energy consumed by the network. In this paper, we propose a Priority-based Cross Layer Routing Protocol (PCLRP) along with a Priority Cross Layer Medium Access Channel protocol (PCLMAC) for healthcare applications.PCLRP combined with PCLMAC ensures reliable traffic dissemination and customized channel access for intra- and inter-body communications. Simulation results show that the proposed protocol achieves customized quality of services and outperforms state of the art existing protocols in terms of power consumption, packet delivery ratio and delay.

Joint Spectrum Access and Pricing in Cognitive Radio Networks with Elastic Traffic

This paper studies the economic interactions between Secondary Users and Primary Operators in a Cognitive Radio Network scenario. Secondary Users transmit their traffic, eventually splitting it over multiple available frequency spectra, each owned by an independent primary network operator. Users are charged a fixed price per unit of bandwidth used, and face spectrum access costs. The transmission rate of each secondary user is assumed to be function of network congestion (like for TCP traffic) and the price per bandwidth unit. Primary operators sell spare bandwidth to secondary users, and set spectrum access prices to maximize their revenue. We provide sufficient conditions for the existence and uniqueness of the Nash equilibrium considering a peculiar class of spectrum pricing functions, viz. polynomial functions, which lead to efficient spectrum allocation, and we derive optimal price and spectrum allocation settings. Finally, we discuss numerical cognitive radio network examples that provide insights into the models solution.

Multi-Attribute Decision Making Handover Algorithm for Wireless Body Area Networks

In this paper, we tackle the Wireless Body area Network (WBAN) handover issue where a mobile patient has to select at any time the best access technology according to multiple criteria. We particularly focus on the decision schemes and investigate the Multi-Attribute Decision Making (MADM) methods. The fundamental objective of the MADM methods is to determine among a finite set of alternatives the optimal one. Therefore, we propose a Multi-Attribute Decision Making Handover Algorithm (MADMHA) which helps patients mobile terminal to dynamically select the best network by providing a ranking order between the list of available candidates. It is a seamless handover approach that guarantees continuous connectivity with respect to the QoS requirements of the WBAN generated traffic types, network history and user preference. Simulation results prove the efficiency of our proposed approach versus the Received Signal Strength Indicator (RSSI) and Data Rate (DR) based handover approaches. Indeed, compared to these latters, MADMHA significantly reduces the packet overhead and the number of handover, while limiting the packet loss ratio.

Optimization Models for Congestion Mitigation in Virtual Networks

Virtualization of network functions and services can significantly reduce capital and operational expenditures of telecommunication operators through the sharing of a single network infrastructure. However, the utilization of the same resources can increase their congestion due to the spatio-temporal correlation of traffic demands and computational loads. In this paper, we propose novel orchestration mechanisms to optimally control and reduce the resource congestion of a physical infrastructure based on the NFV paradigm. In particular, we formulate the network functions composition problem as a nonlinear optimization model to accurately capture the congestion of the physical resources. In order to meet both efficiency and load balancing goals of the physical operator, we introduce two variants of such model to minimize the total and the maximum congestion in the network. Our models allow us to efficiently compute the optimal solution in a short computing time. Numerical results, obtained with real ISP topologies and network instances, show that the proposed approach represents an efficient and practical solution to control the congestion in virtual networks. Furthermore, they indicate that a holistic approach that optimizes the virtual system by jointly considering all elements/components would further improve the performance.

Cross Technology Interference Mitigation in Body-to-Body Area Networks

In recent years, Body-to-Body Networks (BBNs) have gained momentum as a means to monitor people behavior and simplify their interaction with the surrounding environment; thus representing a key element of the Internet of Things (IoT) networking paradigm. Within BBNs, several transmission technologies sharing the same unlicensed band (namely the ISM band) coexist, increasing dramatically the level of interference, which in turn negatively affects the network performance. In this paper, we consider an IoT system composed of several BBNs and we analyze the Cross Technology Interference (CTI) problem caused by the utilization of different transmission technologies that share the same radio spectrum. We formulate an optimization model considering both the Mutual and Cross Technology Interference in order to mitigate the overall level of interference within the IoT system, taking explicitly into account the node mobility. We further develop two heuristic approaches to solve efficiently the interference mitigation problem in large scale network scenarios. Numerical results show that the proposed heuristics represent two efficient and practical alternatives to the optimal solution for solving the CTI mitigation problem in large scale IoT scenarios.

Efficient Orchestration Mechanisms for Congestion Mitigation in NFV: Models and Algorithms

Network Functions Virtualization (NFV) has recently gained momentum among network operators as a means to share their physical infrastructure among virtual operators, which can independently compose and configure their communication services. However, the spatio-temporal correlation of traffic demands and computational loads can result in high congestion and low network performance for virtual operators, thus leading to service level agreement breaches. In this paper, we analyze the congestion resulting from the sharing of the physical infrastructure and propose innovative orchestration mechanisms based on both centralized and distributed approaches, aimed at unleashing the potential of the NFV technology. In particular, we first formulate the network functions composition problem as a non-linear optimization model to accurately capture the congestion of physical resources. To further simplify the network management, we also propose a dynamic pricing strategy of network resources, proving that the resulting system achieves a stable equilibrium in a completely distributed fashion, even when all virtual operators independently select their best network configuration. Numerical results show that the proposed approaches consistently reduce resource congestion. Furthermore, the distributed solution well approaches the performance that can be achieved using a centralized network orchestration system.