A Novel Dual-band Printed Diversity Antenna for Mobile Terminals

A novel dual-band printed diversity antenna is proposed and studied. The antenna, which consists of two back-to- back monopoles with symmetric configuration, is printed on a printed circuit board. The effects of some important parameters of the proposed antenna are deeply studied and the design methodology is given. A prototype of the proposed antenna operating at UMTS (1920-2170 MHz) and 2.4-GHz WLAN (2400-2484 MHz) bands is provided to demonstrate the usability of the methodology in dual-band diversity antenna for mobile terminals. In the above two bands, the isolations of the prototype are larger than 13 dB and 16 dB, respectively. The measured radiation patterns of the two monopoles in general cover complementary space regions. The diversity performance is also evaluated by calculating the envelope correlation coefficient, the mean effective gains of the antenna elements and the diversity gain. It is proved that the proposed antenna can provide spatial and pattern diversity to combat multipath fading.

A Cross-Layer Optimized Scheme and Its Application in Mobile Multimedia Networks with QoS Provision

To cope with the rapid growth of multimedia applications that requires dynamic levels of quality of service (QoS), cross-layer (CL) design, where multiple protocol layers are jointly combined, has been considered to provide diverse QoS provisions for mobile multimedia networks. However, there is a lack of a general mathematical framework to model such CL scheme in wireless networks with different types of multimedia classes. In this paper, to overcome this shortcoming, we therefore propose a novel CL design for integrated real-time/non-real-time traffic with strict preemptive priority via a finite-state Markov chain. The main strategy of the CL scheme is to design a Markov model by explicitly including adaptive modulation and coding at the physical layer, queuing at the data link layer, and the bursty nature of multimedia traffic classes at the application layer. Utilizing this Markov model, several important performance metrics in terms of packet loss rate, delay, and throughput are examined. In addition, our proposed framework is exploited in various multimedia applications, for example, the end-to-end real-time video streaming and CL optimization, which require the priority-based QoS adaptation for different applications. More importantly, the CL framework reveals important guidelines as to optimize the network performance

Design and Analysis of Inexact Floating-Point Adders

Power has become a key constraint in nanoscale inte-grated circuit design due to the increasing demands for mobile computing and higher integration density. As an emerging compu-tational paradigm, an inexact circuit offers a promising approach to significantly reduce both dynamic and static power dissipation for error-tolerant applications. In this paper, an inexact floating-point adder is proposed by approximately designing an exponent sub-tractor and mantissa adder. Related operations such as normaliza-tion and rounding are also dealt with in terms of inexact computing. An upper bound error analysis for the average case is presented to guide the inexact design; it shows that the inexact floating-point adder design is dependent on the application data range. High dynamic range images are then processed using the proposed inexact floating-point adders to show the validity of the inexact design; comparison results show that the proposed inexact floating-point adders can improve the power consumption and power-delay product by 29.98% and 39.60%, respectively.

Mobile Wearable Communications

This special issue provides the latest research and development on wireless mobile wearable communications. According to a report by Juniper Research, the market value of connected wearable devices is expected to reach $1.5 billion by 2014, and the shipment of wearable devices may reach 70 million by 2017. Good examples of wearable devices are the prominent Google Glass and Microsoft HoloLens. As wearable technology is rapidly penetrating our daily life, mobile wearable communication is becoming a new communication paradigm. Mobile wearable device communications create new challenges compared to ordinary sensor networks and short-range communication. In mobile wearable communications, devices communicate with each other in a peer-to-peer fashion or client-server fashion and also communicate with aggregation points (e.g., smartphones, tablets, and gateway nodes). Wearable devices are expected to integrate multiple radio technologies for various applications' needs with small power consumption and low transmission delays. These devices can hence collect, interpret, transmit, and exchange data among supporting components, other wearable devices, and the Internet. Such data are not limited to people's personal biomedical information but also include human-centric social and contextual data. The success of mobile wearable technology depends on communication and networking architectures that support efficient and secure end-to-end information flows. A key design consideration of future wearable devices is the ability to ubiquitously connect to smartphones or the Internet with very low energy consumption. Radio propagation and, accordingly, channel models are also different from those in other existing wireless technologies. A huge number of connected wearable devices require novel big data processing algorithms, efficient storage solutions, cloud-assisted infrastructures, and spectrum-efficient communications technologies.

Belfast Soundwalks

The Belfast Soundwalks project, led by Professor Pedro Rebelo and co-ordinated by Dr Sarah Bass (Sonic Arts Research Centre) in collaboration with Belfast City Council (BCC), aims to use sonic art to engage the public through the development of a locative mobile phone app. Targeting both tourists and citizens of the city, this project aims to sonically enhance the experience of a number of areas of the city, including destinations that may not traditionally be accessed as attractions by visitors and/or disregarded or undervalued by local residents. The project will bring together a number of sonic artists/composers who will create approximately ten soundwalks around the city, while liaising with BCC to distribute the resulting app to the public in line with their tourism and cultural strategy. The project is centred on the development of smart phone apps which provide unique listening experiences associated with key places in the city. The user’s location in the city is tracked through GPS which triggers sound materials ranging from speech to environmental sound and abstract imagined sound worlds. Additionally, local community groups will be consulted in order to evaluate and reflect upon the effectiveness of the soundwalks.

The project builds on the success of the Literary Belfast app and aims to further strengthen links between Queen’s University Belfast and Belfast City Council through facilitating the dissemination of an art form not widely experienced by the general public. Through the newly created Institute for Collaborative Research in the Humanities, directed by Professor John Thompson we are articulating this project with Queen’s consortium partners, Newcastle University and Durham University.

“The Arts and Humanities Research Council (AHRC) funds world-class, independent researchers in a wide range of subjects: ancient history, modern dance, archaeology, digital content, philosophy, English literature, design, the creative and performing arts, and much more. This financial year the AHRC will spend approximately £98m to fund research and postgraduate training in collaboration with a number of partners. The quality and range of research supported by this investment of public funds not only provides social and cultural benefits but also contributes to the economic success of the UK. For further information on the AHRC, please go to: www.ahrc.ac.uk”.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

Design and deployment of secure, robust, and resilient SDN Controllers

The scale of the Software-Defined Network (SDN) Controller design problem has become apparent with the expansion of SDN deployments. Initial SDN deployments were small-scale, single controller environments for research and usecase testing. Today, enterprise deployments requiring multiple controllers are gathering momentum e.g. Google’s backbone network, Microsoft’s public cloud, and NTT’s edge gateway. Third-party applications are also becoming available e.g. HP SDN App Store. The increase in components and interfaces for the evolved SDN implementation increases the security challenges of the SDN controller design. In this work, the requirements of a secure, robust, and resilient SDN controller are identified, stateof-the-art open-source SDN controllers are analyzed with respect to the security of their design, and recommendations for security improvements are provided. This contribution highlights the gap between the potential security solutions for SDN controllers and the actual security level of current controller designs.

Towards automated Android app collusion detection

Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.