Energy efficiency perspectives of femtocells in internet of things : recent advances and challenges

Energy efficiency is a growing concern in every aspect of the technology. Apart from maintaining profitability, energy efficiency means a decrease in the overall environmental effects, which is a serious concern in today's world. Using a femtocell in Internet of Things (IoT) can boost energy efficiency. To illustrate, femtocells can be used in smart homes, which is a subpart of the smart grid, as a communication mechanism in order to manage energy efficiency. Moreover, femtocells can be used in many IoT applications in order to provide communication. However, it is important to evaluate the energy efficiency of femtocells. This paper investigates recent advances and challenges in the energy efficiency of the femtocell in IoT. First, we introduce the idea of femtocells in the context of IoT and their role in IoT applications. Next, we describe prominent performance metrics in order to understand how the energy efficiency is evaluated. Then, we elucidate how energy can be modeled in terms of femtocell and provide some models from the literature. Since femtocells are used in heterogeneous networks to manage energy efficiency, we also express some energy efficiency schemes for deployment. The factors that affect the energy usage of a femtocell base station are discussed and then the power consumption of user equipment under femtocell coverage is mentioned. Finally, we highlight prominent open research issues and challenges. © 2013 IEEE

A comprehensive review of wireless body area network

Recent development and advancement of information and communication technologies facilitate people in different dimensions of life. Most importantly, in the healthcare industry, this has become more and more involved with the information and communication technology-based services. One of the most important services is monitoring of remote patients, that enables the healthcare providers to observe, diagnose and prescribe the patients without being physically present. The advantage of miniaturization of sensor technologies gives the flexibility of installing in, on or off the body of patients, which is capable of forwarding physiological data wirelessly to remote servers. Such technology is named as Wireless Body Area Network (WBAN). In this paper, WBAN architecture, communication technologies for WBAN, challenges and different aspects of WBAN are illustrated. This paper also describes the architectural limitations of existing WBAN communication frameworks. blueFurthermore, implementation requirements are presented based on IEEE 802.15.6 standard. Finally, as a source of motivation towards future development of research incorporating Software Defined Networking (SDN), Energy Harvesting (EH) and Blockchain technology into WBAN are also provided

Reliable, Context-Aware and Energy-Efficient Architecture for Wireless Body Area Networks in Sports Applications

RÉSUMÉ Un Réseau Corporel Sans Fil (RCSF, Wireless Body Area Network en anglais ou WBAN) permet de collecter de l'information à partir de capteurs corporels. Cette information est envoyée à un hub qui la transforme et qui peut aussi effectuer d'autres fonctions comme gérer des événements corporels, fusionner les données à partir des capteurs, percevoir d’autres paramètres, exécuter les fonctions d’une interface d’utilisateur, et faire un lien vers des infrastructures de plus haut niveau et d’autres parties prenantes. La réduction de la consommation d'énergie d’un RCSF est un des aspects les plus importants qui doit être amélioré lors de sa conception. Cet aspect peut impliquer le développement de protocoles de Contrôles d'Accès au Support (CAS, Media Access Control en anglais ou MAC), protocoles de transport et de routage plus efficients. Le contrôle de la congestion est un autre des facteurs les plus importants dans la conception d’un RCSF, parce que la congestion influe directement sur la Qualité De Service (QDS, Quality of Service en anglais ou QoS) et l’efficience en énergie du réseau. La congestion dans un RCSF peut produire une grande perte de paquets et une haute consommation d’énergie. La QDS est directement impactée par la perte de paquets. L’implémentation de mesures additionnelles est nécessaire pour atténuer l’impact sur la communication des RCSF. Les protocoles de CAS pour RCSF devraient permettre aux capteurs corporels d’accéder rapidement au canal de communication et d’envoyer les données au hub, surtout pour les événements urgents tout en réduisant la consommation d’énergie. Les protocoles de transport pour RCSF doivent fournir de la fiabilité bout-à-bout et de la QDS pour tout le réseau. Cette tâche peut être accomplie par la réduction du ratio de perte de paquets (Packet Loss Ratio en anglais ou PLR) et de la latence tout en gardant l'équité et la faible consommation d'énergie entre les noeuds. Le standard IEEE 802.15.6 suggère un protocole de CAS qui est destiné à être applicable à tous les types de RCSF; toutefois, ce protocole peut être amélioré pour les RCSF utilisés dans le domaine du sport, où la gestion du trafic pourrait être différente d’autres réseaux. Le standard IEEE 802.15.6 comprend la QDS, mais cela ne suggère aucun protocole de transport ou système de contrôle du débit. Le but principal de ce projet de recherche est de concevoir une architecture pour RCSF en trois phases : (i) Conception d’un mécanisme sensible au contexte et efficient en énergie pour fournir une QDS aux RCSF; (ii) Conception d’un mécanisme fiable et efficient en énergie pour fournir une récupération des paquets perdus et de l’équité dans les RCSF; et (iii) Conception d’un système de contrôle du débit sensible au contexte pour fournir un contrôle de congestion aux RCSF. Finalement, ce projet de recherche propose une architecture fiable, sensible au contexte et efficiente en énergie pour RCSF utilisés dans le domaine du sport. Cette architecture fait face à quatre défis : l'efficacité de l'énergie, la sensibilité au contexte, la qualité de service et la fiabilité. La mise en place de cette solution aidera à l’amélioration des compétences, de la performance, de l’endurance et des protocoles d’entraînement des athlètes, ainsi qu’à la détection des points faibles. Cette solution pourrait être prolongée à l’amélioration de la qualité de vie des enfants, des personnes malades ou âgées, ou encore aux domaines militaires, de la sécurité et du divertissement. L’évaluation des protocoles et schémas proposés a été faite par simulations programmées avec le simulateur OMNeT++ et le système Castalia. Premièrement, le protocole de CAS proposé a été comparé avec les protocoles de CAS suivants : IEEE 802.15.6, IEEE 802.15.4 et T-MAC (Timeout MAC). Deuxièmement, le protocole de CAS proposé a été comparé avec le standard IEEE 802.15.6 avec et sans l’utilisation du protocole de transport proposé. Finalement, le protocole de CAS proposé et le standard IEEE 802.15.6 ont été comparés avec et sans l’utilisation du système de contrôle du débit proposé. Le protocole de CAS proposé surpasse les protocoles de CAS IEEE 802.15.6, IEEE 802.15.4 et T-MAC dans le pourcentage de pertes de paquets d’urgence et normaux, l’efficacité en énergie, et la latence du trafic d’urgence et du trafic normal. Le protocole de CAS proposé utilisé avec le protocole du transport proposé surpasse la performance du standard IEEE 802.15.6 dans le pourcentage de perte de paquets avec ou sans trafic d’urgence, l’efficacité en énergie, et la latence du trafic normal. Le système de contrôle du débit proposé a amélioré la performance du protocole de CAS proposé et du standard IEEE 802.15.6 dans le pourcentage de perte de paquets avec ou sans trafic d’urgence, l’efficacité en énergie, et la latence du trafic d’urgence.----------ABSTRACT Information collected from body sensors in a Wireless Body Area Network (WBAN) is sent to a hub or coordinator which processes the information and can also perform other functions such as managing body events, merging data from sensors, sensing other parameters, performing the functions of a user interface and bridging the WBAN to higher-level infrastructure and other stakeholders. The reduction of the power consumption of a WBAN is one of the most important aspects to be improved when designing a WBAN. This challenge might imply the development of more efficient Medium Access Control (MAC), transport and routing protocols. Congestion control is another of the most important factors when a WBAN is designed, due to its direct impact in the Quality of Service (QoS) and the energy efficiency of the network. The presence of congestion in a WBAN can produce a big packet loss and high energy consumption. The QoS is also impacted directly by the packet loss. The implementation of additional measures is necessary to mitigate the impact on WBAN communications. The MAC protocols for WBANs should allow body sensors to get quick access to the channel and send data to the hub, especially in emergency events while reducing the power consumption. The transport protocols for WBANs must provide end-to-end reliability and QoS for the whole network. This task can be accomplished through the reduction of both the Packet Loss Ratio (PLR) and the latency while keeping fairness and low power consumption between nodes. The IEEE 802.15.6 standard suggests a MAC protocol which is intended to be applicable for all kinds of WBANs. Nonetheless, it could be improved for sports WBANs where the traffic-types handling could be different from other networks. The IEEE 802.15.6 standard supports QoS, but it does not suggest any transport protocol or rate control scheme. The main objective of this research project is to design an architecture for WBANs in three phases: (i) Designing a context-aware and energy-efficient mechanism for providing QoS in WBANs; (ii) Designing a reliable and energy-efficient mechanism to provide packet loss recovery and fairness in WBANs; and (iii) Designing a context-aware rate control scheme to provide congestion control in WBANs. Finally, this research project proposes a reliable, context-aware and energy-efficient architecture for WBANs used in sports applications, facing four challenges: energy efficiency, context awareness, quality of service and reliability. The benefits of this solution will help to improve skills, performance, endurance and training protocols of athletes, and deficiency detection. Also, it could be extended to enhance the quality of life of children, ill and elderly people, and to security, military and entertainment fields. The evaluation of the proposed protocols and schemes was made through simulations programed in the OMNeT++ simulator and the Castalia framework. First, the proposed MAC protocol was compared against the IEEE 802.15.6 MAC protocol, the IEEE 802.15.4 MAC protocol and the T-MAC (Timeout MAC) protocol. Second, the proposed MAC protocol was compared with the IEEE 802.15.6 standard with and without the use of the proposed transport protocol. Finally, both the proposed MAC protocol and the IEEE 802.15.6 standard were compared with and without the use of the proposed rate control scheme. The proposed MAC protocol outperforms the IEEE 802.15.6 MAC protocol, the IEEE 802.15.4 MAC protocol and the T-MAC protocol in the percentage of emergency and normal packet loss, the energy effectiveness, and the latency of emergency and normal traffic. The proposed MAC protocol working along with the proposed transport protocol outperforms the IEEE 802.15.6 standard in the percentage of the packet loss with or without emergency traffic, the energy effectiveness, and the latency of normal traffic. The proposed rate control scheme improved the performance of both the proposed MAC protocol and the IEEE 802.15.6 standard in the percentage of the packet loss with or without emergency traffic, the energy effectiveness and the latency of emergency traffic

mHealth Engineering: A Technology Review

In this paper, we review the technological bases of mobile health (mHealth). First, we derive a component-based mHealth architecture prototype from an Institute of Electrical and Electronics Engineers (IEEE)-based multistage research and filter process. Second, we analyze medical databases with regard to these prototypic mhealth system components.. We show the current state of research literature concerning portable devices with standard and additional equipment, data transmission technology, interface, operating systems and software embedment, internal and external memory, and power-supply issues. We also focus on synergy effects by combining different mHealth technologies (e.g., BT-LE combined with RFID link technology). Finally, we also make suggestions for future improvements in mHealth technology (e.g., data-protection issues, energy supply, data processing and storage)

Energy efficiency considerations in software‐defined wireless body area networks

Wireless body area networks (WBAN) provide remote services for patient monitoring which allows healthcare practitioners to diagnose, monitor, and prescribe them without their physical presence. To address the shortcomings of WBAN, software-defined networking (SDN) is regarded as an effective approach in this prototype. However, integrating SDN into WBAN presents several challenges in terms of safe data exchange, architectural framework, and resource efficiency. Because energy expenses account for a considerable portion of network expenditures, energy efficiency has to turn out to be a crucial design criterion for modern networking methods. However, creating energy-efficient systems is difficult because they must balance energy efficiency with network performance. In this article, the energy efficiency features are discussed that can widely be used in the software-defined wireless body area network (SDWBAN). A comprehensive survey has been carried out for various modern energy efficiency models based on routing algorithms, optimization models, secure data delivery, and traffic management. A comparative assessment of all the models has also been carried out for various parameters. Furthermore, we explore important concerns and future work in SDWBAN energy efficiency

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications