Eric Jul

Lithium: virtual machine storage for the cloud

To address the limitations of centralized shared storage for cloud computing, we are building Lithium, a distributed storage system designed specifically for virtualization workloads running in large-scale data centers and clouds. Lithium aims to be scalable, highly available, and compatible with commodity hardware and existing application software. The design of Lithium borrows ideas and techniques originating from research into Byzantine Fault Tolerance systems and popularized by distributed version control software, and demonstrates their practical applicability to the performance-sensitive problem of VM hosting. To our initial surprise, we have found that seemingly expensive techniques such as versioned storage and incremental hashing can lead to a system that is not only more robust to data corruption and host failures, but also often faster than naïve approaches and, for a relatively small cluster of just eight hosts, performs well compared with an enterprise-class Fibre Channel disk array.

Scalable virtual machine storage using local disks

In virtualized data centers, storage systems have traditionally been treated as black boxes administered separately from the compute nodes. Direct-attached storage is often left unused, to not have VM availabilty depend on individual hosts. Our work aims to integrate storage and compute, addressing the fundamental limitations of contemporary centralized storage solutions. We are building Lithium, a distributed storage system designed specifically for virtualization workloads running in large-scale data centers and clouds. Lithium aims to be scalable, highly available, and compatible with commodity hardware and existing application software. The design of Lithium borrows techniques from Byzantine Fault Tolerance, stream processing, and distributed version control software, and demonstrates their practical applicability to the performance-sensitive task of virtual machine storage

Data Centre Optimisation Enhanced by Software Defined Networking

Contemporary Cloud Computing infrastructures are being challenged by an increasing demand for evolved cloud services characterised by heterogeneous performance requirements including real-time, data-intensive and highly dynamic workloads. The classical way to deal with dynamicity is to scale computing and network resources horizontally. However, these techniques must be coupled effectively with advanced routing and switching in a multi-path environment, mixed with a high degree of flexibility to support dynamic adaptation and live-migration of virtual machines (VMs). We propose a management strategy to jointly optimise computing and networking resources in cloud infrastructures, where Software Defined Networking (SDN) plays a key enabling role.

Cooperative code-sharing for UMTS femtocells

Femtocells are low-cost, user deployed base-stations that can alleviate indoor coverage problems. However as femtocell deployment density increases, inter-femtocell interference can severely limit their effectiveness. In this paper, we present a protocol for coordinated auto-configuration of femtocells in a UMTS environment. We use an iterated heuristic search (GRASP) to assign orthogonal CDMA spreading codes in the downlink to avoid interference between overlapping signals. The protocol is compared against a baseline of current practice on a range of simulated problems and shown to consistently provide greatly improved performance for data users, providing up to 480% of the average data rate the baseline provides on certain problems.

Confidential Execution of Cloud Services

In this paper, we present Confidential Domain of Execution (CDE), a mechanism for achieving confidential execution of software in an otherwise untrusted environment, e.g., at a Cloud Service Provider. This is achieved by using an isolated execution environment in which any communication with the outside untrusted world is forcibly encrypted by trusted hardware. The mechanism can be useful to overcome the challenging issues in guaranteeing confidential execution in virtualized infrastructures, including cloud computing and virtualized network functions, among other scenarios. Moreover, the proposed mechanism does not suffer from the performance drawbacks typical of other solutions proposed for secure computing, as highlighted by the presented novel validation results.

TRACK: keeping track of highly mobile objects: a lanugage-level proposal position paper

This paper proposes a novel language mechanism to accommodate applications that depend on keeping track of the location of highly mobile objects. New applications are driven by several new trends: new, powerful devices such as smart-phones and Google Glass and vastly improved connectivity between such devices and powerful data centers in the Cloud. Applications running on such new, relatively thin clients, can immensely benefit from the enormous data and compute power provided by Cloud computing. As such devices are inherently highly mobile, they will move along the edge of the cloud and it may be advantageous to track such mobility. Furthermore, objects executing in the cloud may move onto the devices to achieve low latency, or, vice versa, may move from the device into the cloud as to leverage the power of the Cloud. In this position paper, we propose a language mechanism to track the mobility of individual objects, so that an application can rapidly adapt to such mobility. The construct is proposed for Emerald, but will be applicable to most other OO languages albeit not as cleanly as in Emerald. The implementation is integrated into the underlying Emerald virtual machine (i.e., the run-time system). We give an overview of the implementation details and discuss the reliability of the mechanism. Keeping track of devices is modelled by keeping track of an object residing on the device.