- When: 1st November 2018 13:00 - 14:00
- Where: Cole 1.33b
- Series: Systems Seminars Series
- Format: Seminar, Talk
Record linkage is the process of identifying records that refer to the same real-world entities, in situations where entity identifiers are unavailable. Records are linked on the basis of similarity between common attributes, with every pair being classified as a link or non-link depending on their degree of similarity. Record linkage is usually performed in a three-step process: first groups of similar candidate records are identified using indexing, pairs within the same group are then compared in more detail, and finally classified. Even state-of-the-art indexing techniques, such as Locality Sensitive Hashing, have potential drawbacks. They may fail to group together some true matching records with high similarity. Conversely, they may group records with low similarity, leading to high computational overhead. We propose using metric space indexing to perform complete record linkage, which results in a parameter-free record linkage process combining indexing, comparison and classification into a single step delivering complete and efficient record linkage. Our experimental evaluation on real-world datasets from several domains shows that linkage using metric space indexing can yield better quality than current indexing techniques, with similar execution cost, without the need for domain knowledge or trial and error to configure the process.
Virtualisation is a powerful tool used for the isolation, partitioning, and sharing of physical computing resources. Employed heavily in data centres, becoming increasingly popular in industrial settings, and used by home-users for running alternative operating systems, hardware virtualisation has seen a lot of attention from hardware and software developers over the last ten?fifteen years.
From the hardware side, this takes the form of so-called hardware assisted virtualisation, and appears in technologies such as Intel-VT, AMD-V and ARM Virtualization Extensions. However, most forms of hardware virtualisation are typically same-architecture virtualisation, where virtual versions of the host physical machine are created, providing very fast isolated instances of the physical machine, in which entire operating systems can be booted. But, there is a distinct lack of hardware support for cross-architecture virtualisation, where the guest machine architecture is different to the host.
I will talk about my research in this area, and describe the cross-architecture virtualisation hypervisor Captive that can boot unmodified guest operating systems, compiled for one architecture in the virtual machine of another.
I will talk about the challenges of full system simulation (such as memory, instruction, and device emulation), our approaches to this, and how we can efficiently map guest behaviour to host behaviour.
Finally, I will discuss our plans for open-sourcing the hypervisor, the work we are currently doing and what future work we have planned.
In this talk, I will talk about the possibility of using Bayesian nonparametric clustering, or Dirichlet Process Mixture model to solve human activity recognition problem. In particular, I will discuss how the technique can be useful when the activity labels are not annotated and/or the activity evolves over the time. This initial study is built on an existing work on using directional statistical models (von Mises-Fisher) distribution, called Hierarchical Mixture of Conditional Independent von Mises Fisher distribution (HMCIvMFs), for unknown events detection and learning. Markov chain Monte Carlo sampling based learning algorithm will be presented together with some initial experiment results.
We have explored data coordination techniques that permit distributed systems to be constructed by interconnecting services. In such systems the network latency is often a problem. For example, large data volumes might have to be transmitted across the network if computation cannot be co-located close to data sources. One solution to this problem is the ability to deploy services in appropriate geographical locations and compose them together to create distributed ecosystems. Hence we seek to be able to deploy such services rapidly and dynamically enact and orchestrate them. However, this goal is hindered by the size of the deployments. Currently, virtual machine appliances that host such services on top of monolithic kernels are very large, thus are potentially slow to deploy as they may need to be transmitted across a network.
Our principles led us to take the route of re-engineering the standard software stack to create self-contained applications that are less-bloated and consequently much smaller based on Unikernels. Unikernels are compact library operating systems that enable a single application to be statically linked against a simple kernel that manages the underlying resources presented by a hypervisor. In this talk I will present Stardust – a specialised Unikernel that aims to support the deployment of application services based on the Java programming language.
Biography: Dr. Anil Madhavapeddy is a University Lecturer at the Cambridge Computer Laboratory, and a Fellow of Pembroke College where he is Director of Studies for Computer Science. He has worked in industry (NetApp, Citrix, Intel), academia (Cambridge, Imperial, UCLA) and startups (XenSource, Unikernel Systems, Docker) over the past two decades. At Cambridge, he directs the OCaml Labs research group which delves into the intersection of functional programming and systems, and is a maintainer on many open source projects such as OpenBSD, OCaml, Xen and Docker.
9:30: Introduction by Professor Saleem Bhatti
9:35: Lecture 1
10:35: Break with tea and coffee
11:15: Lecture 2
12:15: Lunch (not provided)
14:00: Lecture 3
15:00: Close by Professor Simon Dobson
Lecture 1: Rebuilding Operating Systems with Functional Principles
The software stacks that we deploy across computing devices in the world are based on shaky foundations. Millions of lines of C code crammed into monolithic operating system kernels, mixed with layers of scheduling logic, wrapped in a hypervisor, and served with a dose of nominal security checking on the side. In this talk, I will describe an alternative approach to constructing reliable, specialised systems with a familiar developer experience. We will use modular functional programming to build several services such as a secure web server that have no reliance on conventional operating systems, and explain how to express their logic in a high level, functional fashion. By the end of it, everyone in the audience should be able to build their own so-called unikernels!
Lecture 2: The First Billion Real Deployments of Unikernels
Unikernels offer a path to a more sane basis for driving applications on hardware, but will they ever be adopted for real? For the past fifteen years, an intrepid group of adventurers have been developing the MirageOS application stack in the OCaml programming language. Along the way, it has been deployed in many unusual industrial situations that I will describe in this talk, starting with the Docker container stack, then moving onto the Xen hypervisor that drives billions of servers worldwide. I will explain the challenges of using functional programming in industry, but also the rewards of seeing successful deployments quietly working in mission-critical areas of systems software.
Lecture 3: Programming the Next Trillion Embedded Devices
The unikernel approach of compiling highly specialised applications from high-level source code is perfectly suited to programming the trillions of embedded devices that are making their way around the world. However, this raises new challenges from a programming language perspective: how can we run on a spectrum of devices from the very tiny (with just kilobytes of RAM) to specialised hardware? I will describe the new frontier of functional metaprogramming (programs which generate more programs) that we are using to compile a single application to many heterogenous devices, and a Git-like model to coordinate across thousands of nodes. I will conclude with by motivating the need for a next-generation operating system to power new exciting applications such as augmented and virtual reality in our situated environments, and remove the need for constant centralised coordination via the Internet.
The core problem in many sensing applications is that we’re trying to
infer high-resolution information from low-resolution observations —
and keep our trust in this information as the sensors degrade. How can
we do this in a principled way? There’s an emerging body of work on
using topology to manage both sensing and analytics, and in this talk I
try to get a handle on how this might work for some of the problems
we’re interested in. I will present an experiment we did to explore
these ideas, which highlights some fascinating problems.
Self-organisation and self-governance offer an effective approach to resolving collective action problems in multi-agent systems, such as fair and sustainable resource allocation. Nevertheless, self-governing systems which allow unrestricted and unsupervised self-modification expose themselves to several risks, including the Suber’s paradox of self-amendment (rules specify their own amendment) and Michel’s iron law of oligarchy (that the system will inevitably be taken over by a small clique and be run for its own benefit, rather than in the collective interest). This talk will present an algorithmic approach to resisting both the paradox and the iron law, based on the idea of interactional justice derived from sociology, and legal and organizational theory. The process of interactional justice operationalised in this talk uses opinion formation over a social network with respect to a shared set of congruent values, to transform a set of individual, subjective self-assessments into a collective, relative, aggregated assessment.
Using multi-agent simulation, we present some experimental results about detecting and resisting cliques. We conclude with a discussion of some implications concerning institutional reformation and stability, ownership of the means of coordination, and knowledge management processes in ‘democratic’ systems.
Jeremy Pitt is Professor of Intelligent and Self-Organising Systems in the Department of Electrical & Electronic Engineering at Imperial College London, where he is also Deputy Head of the Intelligent Systems & Networks Group. His research interests focus on developing formal models of social processes using computational logic, and their application in self-organising multi-agent systems, for example fair and sustainable common-pool resource management in ad hoc and sensor network. He also has strong interests in human-computer interaction, socio-technical systems, and the social impact of technology; with regard to the latter he has edited two books, This Pervasive Day (IC Press, 2012) and The Computer After Me (IC Press, 2014). He has been an investigator on more than 30 national and European research projects and has published more than 150 articles in journals and conferences. He is a Senior Member of the ACM, a Fellow of the BCS, and a Fellow of the IET; he is also an Associate Editor of ACM Transactions on Autonomous and Adaptive Systems and an Associate Editor of IEEE Technology and Society Magazine.
“Indoor environment quality has a significant effect on worker productivity through a complex interplay of factors such as temperature, humidity and levels of Volatile Organic Compounds (VOCs).
In this talk I will discuss my Masters project which used off the shelf sensors and Raspberry Pis to collect environmental readings at one minute intervals throughout the Computer Science buildings. The prevalence of erroneous readings due to sensor failure and the strategy used for the identification and correction of such faults will be presented. Identifiable correlations between environmental variables and attempts to model these relationships will be discussed
Past studies identifying the ideal environmental conditions for human comfort and productivity allow for the objective assessment of indoor environmental conditions. An adaptation of Frešer’s environment rating system will be presented, showing how VOC levels can be incorporated into assessments of environment quality and how this can be communicated to building users.”
“Cloud computing is becoming an almost ubiquitous part of the computing landscape. For many companies today, moving their entire infrastructure and workloads to the cloud reduces complexity, time to deployment, and saves money. Spot Instances, a subset of Amazon’s cloud computing infrastructure (EC2), expands on this. They allow a user to bid on spare compute capacity in Amazon’s data centres at heavily discounted prices. If demand was ever to increase such that the user’s maximum bid is exceeded, their compute instance is terminated.
In this work, we conduct one of the first detailed analyses of how location affects the overall cost of deployment of a spot instance. We simultaneously examine the reliability of pricing data of a spot instance, and whether a user can be confident that their instance has a low risk of termination.
We analyse spot pricing data across all available Amazon Web Services regions for 60 days on a variety of instance types. We find that location does play a critical role in spot instance pricing and also that pricing differs depending on the granularity of the location – from a more coarse-grained AWS region to a more fine-grained Availability Zone within a region. We relate the pricing differences we find to the price’s stability, confirming whether we can be confident in the bid prices we make.
We conclude by showing that it is very possible to run workloads on Spot Instances achieving
both a very low risk of termination as well as paying very low amounts per hour.”