“A Decentralised Multimodal Integration of Social Signals: A Bio-Inspired Approach” by Esma Benssassi and “Plug and Play Bench: Simplifying Big Data Benchmarking Using Containers” by Sheriffo Ceesay

Event details

  • When: 26th October 2017 13:00 - 14:00
  • Where: Cole 1.33a
  • Series: Systems Seminars Series
  • Format: Seminar

Esma’s abstract

The ability to integrate information from different sensory modalities in a social context is crucial for achieving an understanding of social cues and gaining useful social interaction and experience. Recent research has focused on multi-modal integration of social signals from visual, auditory, haptic or physiological data. Different data fusion techniques have been designed and developed; however, the majority have not achieved significant accuracy improvement in recognising social cues compared to uni-modal social signal recognition. One of the possible limitations is that these existing approaches have no sufficient capacity to model various types of interactions between different modalities and have not been able to leverage the advantages of multi-modal signals by considering each of them as complementary to the others. We introduce ideas for creating a decentralised model for social signals integration inspired by computational models of multi-sensory integration in neuroscience and the perception of social signals in the human brain.

Sheriffo’s abstract

The recent boom of big data, coupled with the challenges of its processing and storage gave rise to the development of distributed data processing and storage paradigms like MapReduce, Spark, and NoSQL databases. With the advent of cloud computing, processing and storing such massive datasets on clusters of machines is now feasible with ease. However, there are limited tools and approaches, which users can rely on to gauge and comprehend the performance of their big data applications deployed locally on clusters, or in the cloud. Researchers have started exploring this area by providing benchmarking suites suitable for big data applications. However, many of these tools are fragmented, complex to deploy and manage, and do not provide transparency with respect to the monetary cost of benchmarking an application.

In this talk, I will present Plug And Play Bench PAPB (https://github.com/sneceesay77/papb): an infrastructure aware abstraction built to integrate and simplify the process of big data benchmarking. PAPB automates the tedious process of installing, configuring and executing common big data benchmark workloads by containerising the tools and settings based on the underlying cluster deployment framework. Our proof of concept implementation utilises HiBench as the benchmark suite, HDP as the cluster deployment framework and Azure as the cloud platform. The talk will further illustrate the inclusion of cost metrics based on the underlying Microsoft Azure cloud platform.

SRG Seminar: “Adaptive Multisite Computation Offloading in Mobile Clouds” by Dawand Sulaiman and “Topological Ranking-Based Resource Scheduling for Multi-Accelerator Systems” by Teng Yu

Event details

  • When: 12th October 2017 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar

Dawand’s abstract

The concept of using cloud hosted infrastructure as a means to overcome the resource-constraints of mobile devices is known as Mobile Cloud Computing (MCC), and allows applications to run partially on the device, and partially on a remote cloud instance, thereby overcoming any device-specific resource constraints. However, as smart phones and tablets gain more CPU power and longer battery life, the meaning of MCC gradually changes. Instead of being fully dependent on the cloud, a number of nearby devices can be used to coordinate and distribute content and resources in a decentralised manner; this is known as Mobile Ad hoc Cloud Computing. Mobile devices with less computational power and lower battery life can be leveraged by the nearby mobile devices to run resource-intensive applications. Therefore, more efficient and reliable methodologies need to be explored for resource hungry and real time applications such as face recognition, data-intensive, and augmented reality mobile applications.
We present a unified framework which allows each mobile device within the shared environment to intelligently offload its computation to other external platforms. For the individual mobile devices, it is important to make the offloading decision based on network conditions, load of other machines, and mobile device’s own constraints (e.g., mobility and battery). Moreover, to achieve a global optimal task completion time for tasks from all the mobile devices, it is necessary to devise a task scheduling solution that schedules offloaded tasks in real time. The offloading decision engine needs to adapt to the dynamic changes in both the host device and connected nearby and remote devices.

Teng’s abstract

Accelerators are becoming increasingly prevalent in distributed computation. FPGAs have been shown to be fast and power efficient for particular tasks, yet scheduling on multi-accelerator systems is challenging when workloads vary significantly in granularity in terms of task size and/or number of computational unit required.
We present a novel approach for dynamically scheduling tasks on networked multi-accelerator systems which maintains high performance, even in the presence of irregular jobs. Our topological ranking-based scheduling allows realistic irregular workloads to be processed while maintaining a significantly higher level of performance than existing schedulers.

SRG Seminar: “Simulating a pulmonary tuberculosis infection using a network-based metapopulation model” by Michael Pitcher and “A Fake City of People: Modeling the Co-evolution of City and Citizens” by Xue Guo

Event details

  • When: 28th September 2017 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: School Seminar Series, Systems Seminars Series
  • Format: Seminar

Event details
When: 28th September 2017 13:00 – 14:00
Where: Cole 1.33b
Series: Systems Seminars Series
Format: Seminar

Michael Pitcher’s abstract

Tuberculosis (TB) is one of the world’s most deadly infectious diseases, claiming over 1.4 million lives every year. TB infections typically affect the lungs and treatment regimens are long and arduous, requiring at least 6 months of daily chemotherapy. Previous investigations have shown TB to have unique localisations within the lung at varying stages of infection. The initial implant and the primary lesion which arises from it can occur anywhere in the lungs, with a greater probability of occurrence in the lower to middle regions of the lung. However, reactivation of a previously latent form of disease always involves cavitation of the tissue at the apical regions. This difference in spatial location of TB infections suggests two important factors: i) bacteria are able to disseminate across the lung in some manner, and ii) the environment at the top of the lung has some properties that make it preferential for TB replication.

In this project, we aim to build a whole-organ model of the lung and surrounding lymphatics which incorporates both bacterial dissemination possibilities and lung tissue spatial heterogeneity in order to understand their impact on TB. We develop ComMeN (Compartmentalised Metapopulation Network), a Python framework designed to allow the easy creation of complex network-based metapopulations with spatial heterogeneity upon which interaction dynamics can be applied, with discrete event modelling using the Gillespie Algorithm. We then extend this framework to create a TB-specific model, PTBComMeN, which models a TB infection occurring over lung tissue which is divided into patches, each of which contains spatial attributes appropriate to its position in the lung, such as ventilation, perfusion and oxygen tension. Events dictate the interactions between cells and bacteria and their interaction with the environment, with dissemination occurring between edges joining patches on the lung network. This model allows experimentation into studying the effects spatial heterogeneities and bacterial dissemination may have on the progression of disease and the model is designed to provide insight into the factors that result in long treatment times for TB.

Xue Guo’s abstract

By the year 2050, the global urban population will reach 2.5 billion. While the fast pace of urbanisation brings improved quality of life initially, the surging population will inevitably lead to unique urban issues. Emerging research fields, with the aim of creating smarter cities, plan to counteract these problems. To facilitate this research, we need solid models to generate ’fake cities’, which cannot be easily produced by existing random graph algorithms due to spatial constraints. Therefore, we propose a new model for the co-evolution of city and population, which can show how street network forms, how population spreads and how settlements emerge and diminish. The new model will be a random city generator, which could be used to backtrack the history and predict the future of a city, or act as test cases for the validation and evaluation of urban optimisation algorithms.

Containers for HPC environments

Rethinking High performance computing Platforms: Challenges, Opportunities and Recommendations, co-authored by Adam Barker and a team (Ole Weidner, Malcolm Atkinson, Rosa Filgueira Vicente) in the School of Informatics, University of Edinburgh was recently featured in the Communications of the ACM and HPC Wire.

The paper focuses on container technology and argues that a number of “second generation” high-performance computing applications with heterogeneous, dynamic and data-intensive properties have an extended set of requirements, which are not met by the current production HPC platform models and policies. These applications (and users) require a new approach to supporting infrastructure, which draws on container-like technology and services. The paper then goes on to describe cHPC: an early prototype of an implementation based on Linux Containers (LXC).

Ali Khajeh-Hosseini, Co-founder of AbarCloud and former co-founder of ShopForCloud (acquired by RightScale as PlanForCloud) said of this research, “Containers have helped speed-up the development and deployment of applications in heterogeneous environments found in larger enterprises. It’s interesting to investigate their applications in similar types of environments in newer HPC applications.

SRG Seminar: Evaluation Techniques for Detection Model Performance in Anomaly Network Intrusion Detection System by Amjad Al Tobi

Event details

  • When: 1st June 2017 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar

Everyday advancements in technology brings with it novel challenges and threats. Such advancement imposes greater risks than ever on systems and services, including individual privacy information. Relying on intrusion specialists to come up with new signatures to detect different types of new attacks, does not seem to scale with excessive traffic growth. Therefore, anomaly-based detection provides a promising solution for this problem area.

Anomaly-based IDS applies machine learning, data mining and/or artificial intelligence along with many other methods to solve this problem. Currently, these solutions seem not to be tractable for real production environments due to the high false alarms rate. This might be a result of such systems not being able to determine the point at which an update is required. It is not clear how detection models will behave over time, when traffic behaviour has changed since the last time the model was re-generated.
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SRG Seminar: New Network Functionality using ILNPv6 and DNS by Khawar Shehzad

Event details

  • When: 18th May 2017 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar

This research deals with the introduction of a new network functionality based on Identifier-Locator Network Protocol version 6 (ILNPv6), and Domain Name System (DNS). The chosen area of concern is security and specifically mitigation of Distributed Denial of Service (DDoS). The functionality proposed and tested deals with the issues of vulnerability testing, probing, and scanning which directly lead to a successful DDoS attack. The solutions presented can be used as a reactive measure to these security issues. The DDoS is chosen because in recent years DDoS have become the most common and hard to defend attacks. These attacks are on the availability of system/site. There are multiple solutions in the literature but no one solution is based on ILNPv6, and are complex in nature. Similarly, the solutions in literature either require modification in the providers’ networks or they are complex if they are only site-based solutions. Most of these solutions are based on IPv6 protocol and they do not use the concept of naming, as proposed by ILNPv6.

The prime objectives of this research are:

  • to defend against DDoS attacks with the use of naming and DNS
  • to increase the attacker’s effort, reduce vulnerability testing, and random probing by attackers
  • to practically demonstrate the effectiveness of the ILNPv6-based solution for security

SRG Seminar: Investigation of Virtual Network Isolation Security in Cloud Computing Using Penetration Testing by Haifa Al Nasseri

Event details

  • When: 4th May 2017 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Talk

Software Defined Networking (SDN) or Virtual Networks (VNs) are required for cloud tenants to leverage demands. However, multi-tenancy can be compromised without proper isolation. Much research has been conducted into VN Isolation; many researchers are not tackling security aspects or checking if their isolation evaluation is complete. Therefore, data leakage is a major security concern in the cloud in general.

This research uses an OpenStack VN and OpenStack Tenant Network to test multi-tenancy features. We are evaluating the relationship between isolation methods used in cloud VN and the amount of data being leaked through using penetration tests. These tests will be used to identify the vulnerabilities causing cloud VN data leakage and to investigate how the vulnerabilities, and the leaked data, can compromise the tenant Virtual Networks.