CoWiSMoN: A Framework for Cognitive Wireless Sensor Mobile Network System for Emergency Rescue Management

One of the crucial aspects of disaster management of emergency situations is the early assessment of needs and damages. In most disaster situations, higher fatality and increased casualty results from lack of access to timely available emergency services rather than the initial disaster itself. This is usually caused by lack of access to the affected area in order to properly assess the situation for relevant and urgent measures. Cognitive wireless sensor networks provide an opportunity to overcome this situation especially through interconnection via mobile systems. This paper presents a cognitive wireless sensor mobile networks-based framework (CoWiSMoN), designed to offer real-time emergency services to victims and rescue personnel in event of disasters. Critical issues underlying the implementation of such a system are discussed and analyzed.

Using Graphs to Visualise and Detect Anomalies in Access Control System Transactions

Physical Access Control Systems are commonly used to secure doors in buildings such as airports, hospitals, government buildings and offices. These systems are designed primarily to provide an authentication mechanism, but they also log each door access as a transaction in a database. Unsupervised learning techniques can be used to detect inconsistencies or anomalies in the mobility data, such as a cloned or forged Access Badge, or unusual behaviour by staff members. In this paper, we present an overview of our method of inferring directed graphs to represent a physical building network and the flows of mobility within it. We demonstrate how the graphs can be used for Visual Data Exploration, and outline how to apply algorithms based on Information Theory to the graph data in order to detect inconsistent or abnormal behaviour.

Wireless Energy Harvesting and Spectrum Sharing in Cognitive Radio

A wireless energy harvesting protocol is proposed for a decode-and-forward relay- assisted secondary user (SU) network in a cognitive spectrum sharing paradigm. An expression for the outage probability of the relay-assisted cognitive network is derived subject to the following power constraints: 1) the maximum power that the source and the relay in the SU network can transmit from the harvested energy, 2) the peak interference power from the source and the relay in the SU network at the primary user (PU) network, and 3) the interference power of the PU network at the relay-assisted SU network. The results show that as the energy harvesting conversion efficiency improves, the relay- assisted network with the proposed wireless energy harvesting protocol can operate with outage probabilities below 20% for some practical applications.

Creating secure wireless regions using configurable beamforming

We present a novel approach to network security against passive eavesdroppers by employing a configurable beam-forming technique to create tightly defined regions of coverage for targeted users. In contrast to conventional encryption methods, our security scheme is developed at the physical layer by configuring antenna array beam patterns to transmit the data to specific regions. It is shown that this technique can effectively reduce vulnerability of the physical regions to eavesdropping by adapting the antenna configuration according to the intended user's channel state information. In this paper we present the application of our concept to 802.11n networks where an antenna array is employed at the access point, and consider the issue of minimizing the coverage area of the region surrounding the targeted user. A metric termed the exposure region is formally defined and used to evaluate the level of security offered by this technique. A range of antenna array configurations are examined through analysis and simulation, and these are subsequently used to obtain the optimum array configuration for a user traversing a coverage area.

On the Security of Cognitive Radio Networks

Cognitive radio has emerged as an essential recipe for future high-capacity high-coverage multi-tier hierarchical networks. Securing data transmission in these networks is of utmost importance. In this paper, we consider the cognitive wiretap channel and propose multiple antennas to secure the transmission at the physical layer, where the eavesdropper overhears the transmission from the secondary transmitter to the secondary receiver. The secondary receiver and the eavesdropper are equipped with multiple antennas, and passive eavesdropping is considered where the channel state information of the eavesdropper’s channel is not available at the secondary transmitter. We present new closedform expressions for the exact and asymptotic secrecy outage probability. Our results reveal the impact of the primary network on the secondary network in the presence of a multi-antenna wiretap channel.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

Improvisation, Indeterminacy and Game-Mediated Participation in Network Music Performance

This chapter focuses on the relationship between improvisation and indeterminacy. We discuss the two practices by referring to play theory and game studies and situate it in recent network music performance. We will develop a parallel with game theory in which indeterminacy is seen as a way of articulating situations where structural decisions are left to the discernment of the performers and discuss improvisation as a method of play. The improvisation-indeterminacy relationship is discussed in the context of network music performance, which employs digital networks in the exchange of data between performers and hence relies on topological structures with varying degrees of openness and flexibility. Artists such as Max Neuhaus and The League of Automatic Music Composers initiated the development of a multitude of practices and technologies exploring the network as an environment for music making. Even though the technologies behind “the network” have shifted dramatically since Neuhaus’ use of radio in the 1960’s, a preoccupation with distribution and sharing of artistic agency has remained at the centre of networked practices. Gollo Föllmer, after undertaking an extensive review of network music initiatives, produced a typology that comprises categories as diverse as remix lists, sound toys, real/virtual space installations and network performances. For Föllmer, “the term ‘Net music’ comprises all formal and stylistic kinds of music upon which the specifics of electronic networks leave considerable traces, whereby the electronic networks strongly influence the process of musical production, the musical aesthetic, or the way music is received” (2005: 185).

A Scheme Design of Cloud + End Technology in Demand Side Management

Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.

An empirical polarization domain channel availability model for cognitive radio

In dynamic spectrum access networks, cognitive radio terminals monitor their spectral environment in order to detect and opportunistically access unoccupied frequency channels. The overall performance of such networks depends on the spectrum occupancy or availability patterns. Accurate knowledge on the channel availability enables optimum performance of such networks in terms of spectrum and energy efficiency. This work proposes a novel probabilistic channel availability model that can describe the channel availability in different polarizations for mobile cognitive radio terminals that are likely to change their orientation during their operation. A Gaussian approximation is used to model the empirical occupancy data that was obtained through a measurement campaign in the cellular frequency bands within a realistic operational scenario.