Stepan Ivanov

Cooperative wireless sensor environments supporting body area networks

Wireless Body Area Network (WBAN) in recent years have received significant attention, due to their potential for increasing efficiency in healthcare monitoring. Typical sensors used for WBAN are low powered single transceiver devices utilizing a single channel for transmission at the Medium Access Control (MAC) layer. However, performance of these devices usually degrades when the density of sensors increases. One approach to counter this performance degradation is to exploit multiple channels at the MAC layer, where optimal usage of the channels is achieved through cooperation between the sensor nodes. In this paper we propose a cooperative WBAN environment that supports multi-hop transmission through cooperation involving both environmental sensors and WBAN nodes. Our solution extends the cooperation at the MAC layer to a cross-layered gradient based routing solution that allows interaction between WBAN and environmental sensors in order to ensure data delivery from WBANs to a distant gateway. Extensive simulations for healthcare scenarios have been performed to validate the cooperation at the MAC layer, as well as the cross-layered gradient based routing. Comparisons to other cooperative multi-channel MAC and routing solutions have shown the overall performance improvement of the proposed approach evaluated in terms of packet loss, power consumption and delay.

Precision Farming: Sensor Analytics

The role of wireless sensor networks (WSNs) in agriculture has become prominent as part of the precision farming initiative. In the future, multiple WSN systems will be deployed on every farm. Accurate and timely analyses of the data collected by these systems will become paramount for increasing efficiency and sustainability of farming. Conventionally, analyzing monitoring data is considered to be beyond WSN capabilities, and, therefore, carried out remotely. Meanwhile, in recent years, complexity of the tasks performed by WSNs has been constantly increasing. Modern wireless sensors possess computational capacity sufficient for certain data-analytics functionality. This article overviews modern WSN functionality that incorporates a certain level of intelligence, while the authors explore challenges and potential benefits of WSN-based analytics in the scope of precision farming.

Opportunistic Wireless Networking for Smart Dairy Farming

The integration of precision farming techniques with the Internet of Things, cloud computing, and big data analytics is vital to increase productivity in the challenging dairy industry. At the same time, the energy-efficiency and cost-effectiveness of networking solutions that bring big data from farms to the cloud should be addressed as regards economic and environmental sustainability. This article presents an opportunistic networking paradigm for a pasture-based dairy farm in which cows voluntarily participating in robotic milking are used for mulling delay-tolerant data to a fog computing node at an Internet gateway.

People-Centric Internet of Things—Challenges, Approach, and Enabling Technologies

Technology now offers the possibility of delivering a vast range of low-cost people-centric services to citizens. Internet of Things (IoT) supporting technologies are becoming robust, viable and cheaper. Mobile phones are increasingly more powerful and disseminated. On the other hand, social networks and virtual worlds are experiencing an exploding popularity and have millions of users. These low-cost technologies can now be used to create an Internet of People (IoP), a dynamically configurable integration platform of connected smart objects that allows enhanced, people-centric applications. As opposed to things-centric ones, IoP combines the real, sensory world with the virtual world for the benefit of people while it also enables the development of sensing applications in contexts such as e-health, sustainable mobility, social networks enhancement or fulfilling people’s special needs. This paper identifies the main challenges, a possible approach, and key enabling technologies for a people-centric society based on the Internet of Things.

Personal cloudlets: implementing a user-centric datastore with privacy aware access control for cloud-based data platforms

This paper presents OPENis Personal Cloudlets framework as a novel approach to enhancing users control and privacy over their data on a data driven, cloud-based platform. We introduce the EU FP7 funded project OPENi, the OPENi concept, and the research objectives that influenced the design and implementation of OPENis Personal Cloudlet Framework. We outline OPENis architecture and describe how through the use of REST based endpoints, object-based access control, OPENi Types, and stateless JSON Web Token (JWT) it allows users share, reuse, and control access to their data across many mobile applications while maintaining cloud scalability. Furthermore we describe how a number of the Personal Cloudlet Frameworks features enhance a users privacy and control, including: the User Dashboard, the Privacy Preserving Data Aggregator, and the fine grained access control mechanism.

Fog-enabled WSN system for animal behavior analysis in precision dairy

Monitoring and analysis of animal behavior are two of the prominent applications of Wireless Sensor Networks (WSN) in modern Dairy Farming. Behavioral information collected by sensor devices worn by the animals is expected to provide early detection of stress and onset of specific diseases. Animal mobility coupled with farm-based contextual information is expected to automate and increase efficiency of the pasture. Though some WSN solutions have been proposed for these applications, their realizations commonly depend on high availability of third-party components (e.g. cloud-environment for behavior analysis). This reduces suitability of these solutions for pasture-based dairy farms, where large scale and remote locations significantly restrict accessibility to external components (e.g. poor or no internet connectivity). Meanwhile, continuous design improvement of WSN devices has significantly increased their computational capacity. To take advantage of this, a novel Edge Mining (EM) concept has been proposed under the umbrella of Fog Computing, where to increase availability, data analysis is partially hosted by WSN. In this article, we propose an Edge Mining implementation of our WSN system for analyzing animal mobility and behavior. We develop a novel EM method that could be used for a range of animal activity and behavior analysis. Performance of the method is evaluated regarding the accuracy and suitability for WSN-based execution.

Gravity gradient routing for information delivery in fog Wireless Sensor Networks

Fog Computing is a new paradigm that has been proposed by CISCO to take full advantage of the ever growing computational capacity of the near-user or edge devices (e.g., wireless gateways and sensors). The paradigm proposes an architecture that enables the devices to host functionality of various user-centric services. While the prospects of Fog Computing promise numerous advantages, development of Fog Services remains under-investigated. This article considers an opportunity of Fog implementation for Alert Services on top of Wireless Sensor Network (WSN) technology. In particular, we focus on targeted WSN-alert delivery based on spontaneous interaction between a WSN and hand-held devices of its users. For the alert delivery, we propose a Gravity Routing concept that prioritizes the areas of high user-presence within the network. Based on the concept, we develop a routing protocol, namely the Gradient Gravity Routing (GGR) that combines targeted delivery and resilience to potential sensor-load heterogeneity within the network. The protocol has been compared against a set of state-of-the-art solutions via a series of simulations. The evaluation has shown the ability of GGR to match the performance of the compared solutions in terms of alert delivery ratio, while minimizing the overall energy consumption of the network.

Internet of Nano Things for Dairy Farming

This material is based on work in progress. Over the last decade, precision agriculture has grown in importance in order to meet the increasing food demand and ensure sustainability of farming. Today, advances in the Internet of Things (IoT) paradigm have promoted the use of Wireless Sensor Networks (WSN) for precision farming. However, recent technological developments suggest that use of Nanotechnology has immense potential to further improve the farming productivity. In this paper, we present some use-cases for the application of Internet of Nano Things (IoNT) in dairy farming. Although the use of IoNT involves several challenges, we envisage a multitude of benefits associated with its implementation.

On delay distribution in IEEE 802.11 wireless networks

IEEE 802.11 wireless networks have received much attention over the past number of years. Still certain aspects of behavior of wireless networks have not been studied well enough. For example, understanding MAC layer packet delay distribution remains challenging yet. However, obtaining such distribution is highly beneficial for modeling QoS provided by wireless networks. This paper proposes a way of obtaining MAC delay distribution in case of single-hop networks. The proposed way is based on theory of terminating renewal processes and delivers approximation of good precision.

Joint throughput and packet loss probability analysis of IEEE 802.11 networks

Wireless networks have grown their popularity over the past number of years. Usually wireless networks operate according to IEEE 802.11, which specifies protocols of physical and MAC layers. A number of different studies have been conducted on performance of IEEE 802.11 wireless networks. However, questions of QoS control in such networks have not received sufficient attention from the research community. This paper considers modeling of QoS of IEEE 802.11 networks defined in terms of throughput requirements and packet loss probability limitations. An influence of sizes of packets being transmitted through the network on the QoS is investigated. Extensive simulations confirm results obtained from the mathematical model.