Goodbye, ALOHA!

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.Peer ReviewedPostprint (author's final draft

IETF standardization in the field of the Internet of Things (IoT): a survey

Smart embedded objects will become an important part of what is called the Internet of Things. However, the integration of embedded devices into the Internet introduces several challenges, since many of the existing Internet technologies and protocols were not designed for this class of devices. In the past few years, there have been many efforts to enable the extension of Internet technologies to constrained devices. Initially, this resulted in proprietary protocols and architectures. Later, the integration of constrained devices into the Internet was embraced by IETF, moving towards standardized IP-based protocols. In this paper, we will briefly review the history of integrating constrained devices into the Internet, followed by an extensive overview of IETF standardization work in the 6LoWPAN, ROLL and CoRE working groups. This is complemented with a broad overview of related research results that illustrate how this work can be extended or used to tackle other problems and with a discussion on open issues and challenges. As such the aim of this paper is twofold: apart from giving readers solid insights in IETF standardization work on the Internet of Things, it also aims to encourage readers to further explore the world of Internet-connected objects, pointing to future research opportunities

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Abstracting information on body area networks

Healthcare is changing, correction...healthcare is in need of change. The population ageing, the increase in chronic and heart diseases and just the increase in population size will overwhelm the current hospital-centric healthcare. There is a growing interest by individuals to monitor their own physiology. Not only for sport activities, but also to control their own diseases. They are changing from the passive healthcare receiver to a proactive self-healthcare taker. The focus is shifting from hospital centred treatment to a patient-centric healthcare monitoring. Continuous, everyday, wearable monitoring and actuating is part of this change. In this setting, sensors that monitor the heart, blood pressure, movement, brain activity, dopamine levels, and actuators that pump insulin, “pump” the heart, deliver drugs to specific organs, stimulate the brain are needed as pervasive components in and on the body. They will tend for people’s need of self-monitoring and facilitate healthcare delivery. These components around a human body that communicate to sense and act in a coordinated fashion make a Body Area Network (BAN). In most cases, and in our view, a central, more powerful component will act as the coordinator of this network. These networks aim to augment the power to monitor the human body and react to problems discovered with this observation. One key advantage of this system is their overarching view of the whole network. That is, the central component can have an understanding of all the monitored signals and correlate them to better evaluate and react to problems. This is the focus of our thesis. In this document we argue that this multi-parameter correlation of the heterogeneous sensed information is not being handled in BANs. The current view depends exclusively on the applica- tion that is using the network and its understanding of the parameters. This means that every application will oversee the BAN’s heterogeneous resources managing them directly without taking into consideration other applications, their needs and knowledge. There are several physiological correlations already known by the medical field. Correlating blood pressure and cross sectional area of blood vessels to calculate blood velocity, estimating oxygen delivery from cardiac output and oxygen saturation, are such examples. This knowledge should be available in a BAN and shared by the several applications that make use of the network. This architecture implies a central component that manages the knowledge and the resources. And this is, in our view, missing in BANs. Our proposal is a middleware layer that abstracts the underlying BAN’s resources to the applica- tion, providing instead an information model to be queried. The model describes the correlations for producing new information that the middleware knows about. Naturally, the raw sensed data is also part of the model. The middleware hides the specificities of the nodes that constitute the BAN, by making available their sensed production. Applications are able to query for information attaching requirements to these requests. The middleware is then responsible for satisfying the requests while optimising the resource usage of the BAN. Our architecture proposal is divided in two corresponding layers, one that abstracts the nodes’ hardware (hiding node’s particularities) and the information layer that describes information available and how it is correlated. A prototype implementation of the architecture was done to illustrate the concept.This work was partially supported by PhD scholarship SFRH/BD/28843/2006 from Fundação da Ciência e Tecnologia from Portugal