This paper presents a novel 'Cloud-based' solution for teaching computer networks in an educational context. One key advantage of the system is its ability to comission and decomission virtual infrastructures comprised of routers, switches and virtual machines on demand. It makes use of hardware located in different physical locations, VMWare software to manage the virtual resources and NetLab+ to manage the configuration of multiple different virtual scenarios.The key features of the cloud infrastructure are described and evaluated.
One of the major obstacles to the adoption of quantum computing is the requirement to define quantum circuits at the quantum gate level. Many programmers are familiar with high-level or lowlevel programming languages but not quantum gates nor the low-level quantum logic required to derive useful results from quantum computers. The steep learning curve involved when progressing from quantum gates to complex simulations such as Shor's algorithm has proven too much for many developers. The purpose of this paper and the software presented within, addresses this challenge by providing a Software Development Kit (SDK), translation layer, emulator and a framework of techniques for executing Intel 8080/Z80 assembler on a quantum computer, i.e. all salient points of CPU execution, logic, arithmetic and bitwise manipulation will be executed on the quantum computer using quantum circuits. This provides a novel means of displaying the equivalency and interoperability of quantum and classical computers. Developers and researchers can use the SDK to write code in Intel 8080/Z80 assembler which is executed locally via traditional emulation and remotely on a quantum computer in parallel. The emulator features side-by-side code execution with visibility of the running quantum circuit and re-usable/overridable methods. This enables programmers to learn, reuse and contrast techniques for performing any traditional CPU based technique/instruction on a quantum computer; e.g. a programmer may know how to multiply and perform checks on a classical CPU but is not able to perform the same tasks in a quantum implementation, this SDK allows the programmer to pick and choose the methods they would like to use to fulfil their requirements. The SDK makes use of open-source software, specifically Python and Qiskit for the emulation, translation, API calls and execution of user supplied code or binaries.
This paper describes an optimised and novel approach to an Autonomous Virtual Server Management System in a 'Cloud Computing' environment and it presents a set of preliminary test results. One key advantage of this system is its ability to improve hardware power consumption through autonomously moving virtual servers around a network to balance out hardware loads. This has a potentially important impact on issues of sustainability with respect to both energy efficiency and economic viability. Another key advantage is the improvement of the overall end-user experience for services within the Cloud. This has been investigated through the configuration of a cloud-computing test-bed rig. The key features of this rig and some predictions of what may be achieved with it are described and evaluated. I.
This paper describes a novel modular design of an autonomous management distributed system (AMDS) for cloud computing environments and it presents its implementation with the Scala programming language. The AMDS was designed from the ground up with distributed deployment, modularity and security in mind, using a full object oriented approach. A key feature of this system is the ability to gather and store information from various networking and monitoring devices from within the same computing cluster. Another key feature is the ability to intelligently control VMWare vSphere local instances based on analysis of collected data and predefined parameters. vSphere in turn, once it receives commands from the AMDS, proceeds to issue instructions to multiple locally monitored ESXi severs in order to maximize energy efficiency, reduce the carbon footprint and minimize running costs. The predefined parameters are based on results from a previous paper written by the authors. The AMDS has been deployed on the authors' test bed and is currently running successfully. Test results show highly potential industrial applications in datacenter energy management and lowering of operating costs.
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