A real-time power monitoring and energy-efficient network/interface selection tool for android smartphones

Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types

A real-time power monitoring and energy-efficient network/interface selection tool for android smartphones

Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types

Experimental analysis of connectivity management in mobile operating systems

We are immerse in a world that becomes more and more mobile every day, with ubiquitous connectivity and increasing demand for mobile services. Current mobile terminals support several access technologies, enabling users to gain connectivity in a plethora of scenarios and favoring their mobility. However, the management of network connectivity using multiple interfaces is still starting to be deployed. The lack of smart connectivity management in multi interface devices forces applications to be explicitly aware of the variations in the connectivity state (changes in active interface, simultaneous access from several interfaces, etc.). In this paper, we analyze the present state of the connection management and handover capabilities in the three major mobile operating systems (OSes): Android, iOS and Windows. To this aim, we conduct a thorough experimental study on the connectivity management of each operating system, including several versions of the OS on different mobile terminals, analyzing the differences and similarities between them. Moreover, in order to assess how mobility is handled and how this can affect the final user, we perform an exhaustive experimental analysis on application behavior in intra- and inter-technology handover. Based on this experience, we identify open issues in the smartphone connectivity management policies and implementations, highlighting easy to deploy yet unimplemented improvements, as well as potential integration of mobility protocols.This work has been partially supported by the European Community through the CROWD project, FP7-ICT-318115.Publicad

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

Seamless multimedia delivery within a heterogeneous wireless networks environment: are we there yet?

The increasing popularity of live video streaming from mobile devices such as Facebook Live, Instagram Stories, Snapchat, etc. pressurises the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of Quality of Experience (QoE) as the basis for network control, customer loyalty and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users’ quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: adaptation, energy efficiency and multipath content delivery. Discussions, challenges and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

Context Aware Handover Algorithms For Mobile Positioning Systems

This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95 percent of cases studied while two other applications performed correct handover in only 50 percent of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

Mesh networks for handheld mobile devices

Mesh communications emerge today as a very popular networking solution. Mesh networks have a decentralized and multihop design. These characteristics arouse interest in research for relevant novel features, such as cooperation among nodes, distribution of tasks, scalability, communication with limited infrastructure support, and the support of mobile devices as mesh nodes. In addition to the inexistence of a solution that implements mesh networks with mobile devices at the data link layer (Layer 2), there is also a need to reconsider existing metrics with new information to tackle the intrinsic characteristics of mobile devices, e.g., the limited energy resources of their battery. To tackle this problem, this thesis presents a detailed study about projects, routing protocols and metrics developed in the area of mesh networks. In addition, two data link layer solutions, Open802.11s and B.A.T.M.A.N-advanced, have been adapted and deployed in a real mesh network testbed with off the shelf routers devices installed with a customized operating system. From this testbed, Open802.11s has proved to offer better performance than B.A.T.M.A.N-advanced. Following this, a breakthrough in this work has been the integration of the 802.11s on an Android mobile device and its subsequent incorporation in the mesh network. This allowed the study of eventual limitations imposed by the mobile device on the operation of the mesh network, namely performance and energy scarcity. With this, another major novelty has followed, by designing, implementing and evaluating several energy related metrics regarding the battery status of mobile devices. This has enabled the participation of mobile devices in mesh routing paths in an efficient way. Our main objective was to implement a mesh network with mobile devices. This has been achieved and validated through the evaluation of diverse testing scenarios performed in a real mesh testbed. The obtained results also show that the operation of a mesh with mobile devices can be enhanced, including the lifetime of mobile devices, when an energy-aware metric is used.As redes mesh surgem hoje em dia como uma solução de rede em crescimento e expansão. Neste tipo de redes o comportamento entre os nós é descentralizado e numa topologia de multihop. Estas características despertam interesse na pesquisa e desenvolvimento de novas funcionalidades tais como: cooperação entre nós, distribuição de tarefas, escalabilidade da rede e comunicações mesmo em casos de uma infraestrutura limitada e o suporte de dispositivos móveis como nós de uma rede mesh. Associado à inexistência de um projecto que implemente redes mesh em dispositivos móveis na camada de ligação de dados (Layer 2), surge a necessidade de repensar as métricas já existentes com novas informações que façam face às novas características dos dispositivos móveis, neste caso, os recursos limitados de bateria. Por forma a resolver este problema, este trabalho apresenta um estudo detalhado sobre os projetos, protocolos de routing e métricas desenvolvidas na área das redes mesh. Além disso, duas soluções que utilizam a camada de ligação de dados, Open802.11s e BATMAN-advanced, estes foram adaptadao e implementados num testbed real utilizando routers com um sistema operacional costumizado instalado. Deste testbed, concluiu-se que o Open802.11s obtem um melhor desempenho que o BATMAN-advanced. Assim, um dos avanços deste trabalho foi a integração do Open802.11s num dispositivo móvel Android e sua posterior incorporação na rede mesh. Isto permitiu o estudo de eventuais limitações impostas pelo dispositivo móvel ao funcionar numa rede mesh, ou seja, desempenho e a escassez de energia. Com isso, foi concebida outra novidade, através da concepção, avaliação e implementação de várias métricas relacionadas com a energia e que têm por base o estado da bateria do dispositivo. Isto permitiu que os dispositivos móveis participem na rede mesh e a sua gestão de bateria seja feita de forma eficiente. O principal objectivo era a implementação de uma rede mesh com dispositivos móveis. Este foi alcançado e validado através de diversos cenários de teste reais. Os resultados obtidos demonstram também que o funcionamento de uma rede mesh com dispositivos móveis pode ser melhorada, incluindo o tempo de vida dos dispositivos móveis, quando uma métrica que considera a energia é utilizada