64-bit architechtures and compute clusters for high performance simulations

Simulation of large complex systems remains one of the most demanding of high performance computer systems both in terms of raw compute performance and efficient memory management. Recent availability of 64-bit architectures has opened up the possibilities of commodity computers accessing more than the 4 Gigabyte memory limit previously enforced by 32-bit addressing. We report on some performance measurements we have made on two 64-bit architectures and their consequences for some high performance simulations. We discuss performance of our codes for simulations of artificial life models; computational physics models of point particles on lattices; and with interacting clusters of particles. We have summarised pertinent features of these codes into benchmark kernels which we discuss in the context of wellknown benchmark kernels of the 32-bit era. We report on how these these findings were useful in the context of designing 64-bit compute clusters for high-performance simulations

Simulations of Large-scale WiFi-based Wireless Networks: Interdisciplinary Challenges and Applications

Wireless Fidelity (WiFi) is the fastest growing wireless technology to date. In addition to providing wire-free connectivity to the Internet WiFi technology also enables mobile devices to connect directly to each other and form highly dynamic wireless adhoc networks. Such distributed networks can be used to perform cooperative communication tasks such ad data routing and information dissemination in the absence of a fixed infrastructure. Furthermore, adhoc grids composed of wirelessly networked portable devices are emerging as a new paradigm in grid computing. In this paper we review computational and algorithmic challenges of high-fidelity simulations of such WiFi-based wireless communication and computing networks, including scalable topology maintenance, mobility modelling, parallelisation and synchronisation. We explore similarities and differences between the simulations of these networks and simulations of interacting many-particle systems, such as molecular dynamics (MD) simulations. We show how the cell linked-list algorithm which we have adapted from our MD simulations can be used to greatly improve the computational performance of wireless network simulators in the presence of mobility, and illustrate with an example from our simulation studies of worm attacks on mobile wireless adhoc networks.Comment: Future Generation Computer Systems, Article in Pres

RF free ultrasonic positioning

All wearable centric location sensing technologies must address the issue of clock synchronisation between signal transmitting systems and signal receiving systems. GPS receivers, for example, compensate for synchronisation errors by incorporating a model of the receiver clock offset in the navigation solution. Drift between satellite clocks is also monitored to keep signal data in synch with GPS time. Most ultrasonic positioning systems solve the synchronisation problem by using a second medium for communication between transmitter and receiver devices. The transmitters in these systems emit RF signals (pings) to indicate the transmission of subsequent ultrasound signals (chirps). By subtracting the arrival time of the ping from that of the chirps, the receiver is able to compute the distance to each transmitter. In this paper, we describe an ultrasonic positioning system that does not use RF signals to achieve synchronisation. Instead, it exploits a periodic chirp transmission pattern to model the receiver’s position using chirp reception times exclusively. Not only does the system improve on the accuracy of previous technologies but it also eliminates bulky RF circuitry – a definite advantage for wearable applications where component size and weight are critical for usability.

Guppy: Process-Oriented Programming on Embedded Devices

Guppy is a new and experimental process-oriented programming language, taking much inspiration (and some code-base) from the existing occam-pi language. This paper reports on a variety of aspects related to this, specifically language, compiler and run-time system development, enabling Guppy programs to run on desktop and embedded systems. A native code-generation approach is taken, using C as the intermediate language, and with stack-space requirements determined at compile-time

Optimising lower layers of the protocol stack to improve communication performance in a wireless temperature sensor network

The function of wireless sensor networks is to monitor events or gather information and report the information to a sink node, a central location or a base station. It is a requirement that the information is transmitted through the network efficiently. Wireless communication is the main activity that consumes energy in wireless sensor networks through idle listening, overhearing, interference and collision. It becomes essential to limit energy usage while maintaining communication between the sensor nodes and the sink node as the nodes die after the battery has been exhausted. Thus, conserving energy in a wireless sensor network is of utmost importance. Numerous methods to decrease energy expenditure and extend the lifetime of the network have been proposed. Researchers have devised methods to efficiently utilise the limited energy available for wireless sensor networks by optimising the design parameters and protocols. Cross-layer optimisation is an approach that has been employed to improve wireless communication. The essence of cross-layer scheme is to optimise the exchange and control of data between two or more layers to improve efficiency. The number of transmissions is therefore a vital element in evaluating overall energy usage. In this dissertation, a Markov Chain model was employed to analyse the tuning of two layers of the protocol stack, namely the Physical Layer (PHY) and Media Access Control layer (MAC), to find possible energy gains. The study was conducted utilising the IEEE 802.11 channel, SensorMAC (SMAC) and Slotted-Aloha (S-Aloha) medium access protocols in a star topology Wireless Temperature Sensor Network (WTSN). The research explored the prospective energy gains that could be realised through optimizing the Forward Error Correction (FEC) rate. Different Reed Solomon codes were analysed to explore the effect of protocol tuning on energy efficiency, namely transmission power, modulation method, and channel access. The case where no FEC code was used and analysed as the control condition. A MATLAB simulation model was used to identify the statistics of collisions, overall packets transmitted, as well as the total number of slots used during the transmission phase. The bit error probability results computed analytically were utilised in the simulation model to measure the probability of successful transmitting data in the physical layer. The analytical values and the simulation results were compared to corroborate the correctness of the models. The results indicate that energy gains can be accomplished by the suggested layer tuning approach.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Pervasive service discovery in low-power and lossy networks

Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere