Adnan Al-Anbuky

Performance Analysis of Cooperative Virtual MIMO Systems for Wireless Sensor Networks

Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs.

A Smart City Lighting Case Study on an OpenStack-Powered Infrastructure

The adoption of embedded systems, mobile devices and other smart devices keeps rising globally, and the scope of their involvement broadens, for instance, in smart city-like scenarios. In light of this, a pressing need emerges to tame such complexity and reuse as much tooling as possible without resorting to vertical ad hoc solutions, while at the same time taking into account valid options with regard to infrastructure management and other more advanced functionalities. Existing solutions mainly focus on core mechanisms and do not allow one to scale by leveraging infrastructure or adapt to a variety of scenarios, especially if actuators are involved in the loop. A new, more flexible, cloud-based approach, able to provide device-focused workflows, is required. In this sense, a widely-used and competitive framework for infrastructure as a service, such as OpenStack, with its breadth in terms of feature coverage and expanded scope, looks to fit the bill, replacing current application-specific approaches with an innovative application-agnostic one. This work thus describes the rationale, efforts and results so far achieved for an integration of IoT paradigms and resource ecosystems with such a kind of cloud-oriented device-centric environment, by focusing on a smart city scenario, namely a park smart lighting example, and featuring data collection, data visualization, event detection and coordinated reaction, as example use cases of such integration.

An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a global scale. However, the IoT system can suffer from poor performances when its underlying networks are not optimized. In this paper, an ontology model for representing and facilitating context sharing between network entities in WSNs is proposed for the first time. The context model aims to enable optimal context-aware management of WSNs in IoT, which will also harness the rich context knowledge of IoT systems.

Distributed WSN Data Stream Mining Based on Fuzzy Clustering

This paper proposes a distributed wireless sensor network (WSN) data stream clustering algorithm to minimize sensor nodes energy consumption and consequently extend the network lifetime. The paper follows the strategy of trading-off communication for computation through distributed clustering and successive transmission of local clusters. We present an energy efficient algorithm we developed, Subtractive Fuzzy Cluster Means (SUBFCM), and analyze its energy efficiency as well as clustering performance in comparison with state-of-the-art standard data clustering algorithms such as Fuzzy C-means and K-means algorithms. Simulations show that SUBFCM can achieve WSN data stream clustering with significantly less energy than that required by Fuzzy C-means and K-means algorithms.

Microwave Nondestructive Testing of Wood Anisotropy and Scatter

A microwave-focused beam transmission measurement is identified as a good candidate for fast, accurate, and affordable industrial wood testing. In this paper, the transmission measurement setup, in its various forms, is used to study woods properties, considering the wood as anisotropic heterogeneous and multiphase dielectric. The depolarization of a linearly polarized plane wave in an anisotropic media is considered first. It is used for grain angle detection for arbitrary grain inclination in 3-D space. A good correlation with visually inspected grain angle values is obtained. A scattering experiment is performed, measuring the transmission through the wood when the transmitting and the receiving antenna axes are at the right angle. The results indicate that the annual ring arrangement strongly influences scattering in the sideways direction, while other investigated parameters (defects, gradual density variation, and bulk density) show poor correlation with the measured scattering coefficient.

Wireless sensor networks and human comfort index

Conventional wireless home automation networks (WHANs) incorporate embedded wireless sensors and actuators that monitors and control home living environment. WHANs primary goal is to maintain user comfort and efficient home management. Conventional WHAN lacks “intelligence” in terms of managing compound human comfort, and it deals with multitude of human comfort factors individually instead of collectively. This paper presents wireless sensor networks-based Human Comfort Ambient Intelligence system. A fuzzy-rule-based system for the measurement of human comfort index in a living space is presented. The system is evaluated and tested with simulated and empirical data. It explores the complex relationship between multiple comfort factors. The comfort factors considered here include thermal comfort, visual comfort, indoor air comfort and acoustical comfort.

Development of Intelligent Wireless Sensor Networks for Human Comfort Index Measurement

Abstract Conventional wireless home automation networks (WHANs) incorporate embedded wireless sensors and actuators that monitors and control home living environment. WHANs primary goal is to maintain user comfort and efficient home management. Conventional WHAN lacks higher “intelligence” in term of managing compound human comfort where as it deals with multitude of human comfort factors individually instead of collectively. This paper presents wireless sensor networks (WSN) based Human Comfort Ambient Intelligence (HCAmI) system. The design of a Fuzzy Rule Based System (FRBS) for the measurement of Human Comfort Index (HCI) in a living space is presented. The design of FRBS is described and the system is evaluated and tested by using combined simulated and empirical data. It explores the complex relationship between multiple comfort factors in human comfort provisioning. The comfort factors considered here include thermal comfort, visual comfort, indoor air comfort and acoustical comfort.

Virtual Brokers for Large-Scale Publish/Subscribe in Wireless Sensor Networks

Brokers are critical elements for many publish and subscribe (pub/sub) systems. They are dedicated devices with large computation and storage capacities, but they could suffer from scalability problems when comes to actual large-scale implementations in wireless sensor networks. Inspired by the recent virtual MIMO concept for wireless sensor networks, this paper proposes the idea of ‘virtual brokers’ for large-scale pub/sub systems in sensor networks, and presents in detail the design of a three-stage algorithm for forming a virtual broker around multiple co-located sensor nodes using only network connectivity information. Using computer modeling, we conduct an investigation of our virtual broker formation algorithm and preliminary results demonstrate the potential of our algorithm for scalable formation of virtual brokers.

Passive House sensor networks: Human centric thermal comfort concept

The focus of this work lies on analysing Passive House (PH) requirement from human comfort perspective. The investigation will lead into plans for utilising Wireless Sensor Networks (WSN) as an enabling tool in human comfort solution. WSNs are used as cooperative smart objects that closely monitor living spaces environmental comfort (thermal comfort, visual comfort, indoor air comfort, acoustical comfort and spatial comfort), user preferences and energy consumption, manipulating appropriate Environmental Factors and Physiological Factors towards improving human comfort without sacrificing energy needs of a Passive House. The work concentrates on determining the thermal comfort of a living space where mobile node (occupant) and static nodes (environment) work together in calculating thermal comfort Predicted Mean Vote (PMV) value. This paper presents Java based SunSPOT sensor node, embedded with sensing engine and PMV engine to determine thermal comfort of a living space. We also present interpolation based PMV engine that will be used to determine thermal comfort where no sensor present. The experiment and simulation results indicate that the proposed engines exhibit a great potential in providing solution for PH activity.

In-network storage for virtual broker-based publish/subscribe in WSNs

Data centricity is a key characteristic that distinguishes wireless sensor networks (WSNs) from other types of wireless networks. In traditional WSNs, sensors detect environmental attributes or events, which are transmitted to and stored on dedicated base stations or sinks at the network edge for further processing. With advances in data storage technologies, it becomes possible for embedded sensor devices to cooperatively store and maintain data within the WSN for later retrieval by in-network users such as humans who interact with their environments which have been smartified by embedded intelligence. In this paper, an in-network storage scheme is proposed for a virtual broker (VB) based pub/sub system in WSNs. The proposed scheme is shown to achieve good performance in terms of storage load balancing, communication cost, and energy efficiency.