Multi-tenancy in relational databases has been a topic of interest for a couple of years. On the one hand, ever increasing capabilities and capacities of modern hardware easily allow for multiple database applications to share one system. On the other hand, cloud computing leads to outsourcing of many applications to service architectures, which in turn leads to offerings for relational databases in the cloud, as well. The ability to benchmark multi-tenancy database systems (MT-DBMSs) is imperative to evaluate and compare systems and helps to reveal otherwise unnoticed shortcomings. With several tenants sharing a MT-DBMS, a benchmark is considerably different compared to classic database benchmarks and calls for new benchmarking methods and performance metrics. Unfortunately, there is no single, well-accepted multi-tenancy benchmark for MT-DBMSs available and few efforts have been made regarding the methodology and general tooling of the process. We propose a method to benchmark MT-DBMSs and provide a framework for building such benchmarks. To support the cumbersome process of defining and generating tenants, loading and querying their data, and analyzing the results we propose and provide MULTE, an open-source framework that helps with all these steps.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

Recent years have witnessed a surge in demand for infrastructure and services to cover high demands on processing big chunks of data and applications resulting in a mega Cloud Datacenter. A datacenter is of high complexity with increasing difficulties to identify, allocate efficiently and fast an appropriate host for the requested virtual machine (VM). Establishing a good awareness of all datacenter’s resources enables the allocation “placement” policies to make the best decision in reducing the time that is needed to allocate and create the VM(s) at the appropriate host(s). However, current algorithms and policies of placement “allocation” do not focus efficiently on awareness of the resources of the datacenter, and moreover, they are based on conventional static techniques. Which are adversely impacting on the allocation progress of the policies. This thesis proposes a new Agent-based allocation/placement policy that employs some of the Multi-Agent system features to get a good awareness of Cloud Datacenter resources and also provide an efficient allocation decision for the requested VMs. Specifically, (a) The Multi-Agent concept is used as a part of the placement policy (b) A Contract Net Protocol is devised to establish good awareness and (c) A verification process is developed to fully dimensional VM specifications during allocation. These new results show a reduction in response time of VM allocation and the usage improvement of occupied resources. The proposed Agent-based policy was implemented using the CloudSim toolkit and consequently was compared, based on a series of typical numerical experiments, with the toolkit’s default policy. The comparative study was carried out in terms of the time duration of VM allocation and other aspects such as the number of available VM types and the amount of occupied resources. Moreover, a two-stage comparative study was introduced through this thesis. Firstly, the proposed policy is compared with four state of the art algorithms, namely the Random algorithm and three one-dimensional Bin-Packing algorithms. Secondly, the three Bin-Packing algorithms were enhanced to have a two-dimensional verification structure and were compared against the proposed new algorithm of the Agent-based policy. Following a rigorous comparative study, it was shown that, through the typical numerical experiments of all stages, the proposed new Agent-based policy had superior performance in terms of the allocation times. Finally, avenues arising from this thesis are included. / Al al-Bayt University in Jordan.

Описаны проблемы работы с ресурсами в крупных IT-компаниях и возможности применения облачных технологий для их решения. Исследованы существующие программные продукты для построения облачных платформ. Разработана и реализована архитектура продукта для работы с разными платформами виртуализации на основе существующего интерфейса взаимодействия OpenStack. / The problems of working with resources in large IT companies and the possibilities of using cloud technologies to solve them are described. The existing software products for building cloud platforms are investigated. The product architecture for working with different virtualization platforms based on the existing OpenStack interaction interface has been developed and implemented.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increases energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices causes a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

This thesis investigates the possibility of communication with a PCI eXtensions for Instrumentation (PXI) system from inside of a container or a virtual machine (VM). While the usage of virtual environments with PCI have been established, it was unknown whether it is possible to have an application running inside of a virtual environment and have it communicate with a PXI system outside this environment. Should it be possible to have communication with a PXI system from inside of a virtual environment, this would make it possible to have a virtual environment prepared with all the necessary software for the PXI and this virtual environment could be transferred and installed into other computers without the need to change any of the software.The investigation was done by creating several different test environments to better understand how both the PXI drivers and the virtual environment work and to see how they interact with each other.While it turned out not to be possible to realize such a virtual environment using the equipment described in this thesis, it was learned that it was theoretically possible to make use of VM for communication with a PXI system, although doing this in practice is dependant on the specific PXI modules involved. / Denna avhandling undersöker möjligheten för kommunikation med ett PCI eXtensions for Instrumentation (PXI) system från inuti en container eller en virtuell maskin (VM). Medan användandet av virtuella miljöer med Peripheral Component Interconnect (PCI) är etablerat, det är i nuläget inte känt om det är möjligt att ha en applikation körandes inuti en virtuell miljö och ha den kommunicera med ett PXI system utanför denna miljö. Om det vore möjligt att ha kommunikation från inuti den virtuella miljö, skulle det vara möjligt att ha en virtuell miljö förbered med all nödvändig mjukvara för PXI som kan flyttas och installeras i nya fysiska platser utan att behöva göra ändringar i mjukvaran. Denna undersökningen gjordes genom att skapa flera olika test miljöer för att att ska en bättre förståelse för hur både PXI drivare och den virtuella miljön fungerar och hur de interagerar med varandra. Trots att det visade sig inte var möjligt med den utrustning som beskrivs i denna avhandling, det vissade sig dock vara teoretiskt möjligt att använda VM för kommunikation med PXI system, men det är då starkt beroende på vad för PXI moduler involverade.

Increasing the number of processors has become the mainstream for the modern chip design approaches. However, most applications are designed or written for single core processors; so they do not benefit from the numerous underlying computation resources. Moreover, there exists a large base of legacy software which requires an immense effort and cost of rewriting and re-engineering to be made parallel. In the past decades, there has been a growing interest in automatic parallelization. This is to relieve programmers from the painful and error-prone manual parallelization process, and to cope with new architecture trend of multi-core and many-core CPUs. Automatic parallelization techniques vary in properties such as: the level of paraellism (e.g., instructions, loops, traces, tasks); the need for custom hardware support; using optimistic execution or relying on conservative decisions; online, offline or both; and the level of source code exposure. Transactional Memory (TM) has emerged as a powerful concurrency control abstraction. TM simplifies parallel programming to the level of coarse-grained locking while achieving fine-grained locking performance. This dissertation exploits TM as an optimistic execution approach for transforming a sequential application into parallel. The design and the implementation of two frameworks that support automatic parallelization: Lerna and HydraVM, are proposed, along with a number of algorithmic optimizations to make the parallelization effective. HydraVM is a virtual machine that automatically extracts parallelism from legacy sequential code (at the bytecode level) through a set of techniques including code profiling, data dependency analysis, and execution analysis. HydraVM is built by extending the Jikes RVM and modifying its baseline compiler. Correctness of the program is preserved through exploiting Software Transactional Memory (STM) to manage concurrent and out-of-order memory accesses. Our experiments show that HydraVM achieves speedup between 2×-5× on a set of benchmark applications. Lerna is a compiler framework that automatically and transparently detects and extracts parallelism from sequential code through a set of techniques including code profiling, instrumentation, and adaptive execution. Lerna is cross-platform and independent of the programming language. The parallel execution exploits memory transactions to manage concurrent and out-of-order memory accesses. This scheme makes Lerna very effective for sequential applications with data sharing. This thesis introduces the general conditions for embedding any transactional memory algorithm into Lerna. In addition, the ordered version of four state-of-art algorithms have been integrated and evaluated using multiple benchmarks including RSTM micro benchmarks, STAMP and PARSEC. Lerna showed great results with average 2.7× (and up to 18×) speedup over the original (sequential) code. While prior research shows that transactions must commit in order to preserve program semantics, placing the ordering enforces scalability constraints at large number of cores. In this dissertation, we eliminates the need for commit transactions sequentially without affecting program consistency. This is achieved by building a cooperation mechanism in which transactions can forward some changes safely. This approach eliminates some of the false conflicts and increases the concurrency level of the parallel application. This thesis proposes a set of commit order algorithms that follow the aforementioned approach. Interestingly, using the proposed commit-order algorithms the peak gain over the sequential non-instrumented execution in RSTM micro benchmarks is 10× and 16.5× in STAMP. Another main contribution is to enhance the concurrency and the performance of TM in general, and its usage for parallelization in particular, by extending TM primitives. The extended TM primitives extracts the embedded low level application semantics without affecting TM abstraction. Furthermore, as the proposed extensions capture common code patterns, it is possible to be handled automatically through the compilation process. In this work, that was done through modifying the GCC compiler to support our TM extensions. Results showed speedups of up to 4× on different applications including micro benchmarks and STAMP. Our final contribution is supporting the commit-order through Hardware Transactional Memory (HTM). HTM contention manager cannot be modified because it is implemented inside the hardware. Given such constraint, we exploit HTM to reduce the transactional execution overhead by proposing two novel commit order algorithms, and a hybrid reduced hardware algorithm. The use of HTM improves the performance by up to 20% speedup. / Ph. D.

Detta examensarbete handlar om undersökning av tre olika användningsfall inom datalagring; Cold Storage, High Performance Storage och Virtual Machine Storage. Rapporten har som syfte att ge en översikt över kommersiella distribuerade filsystem samt en djupare undersökning av distribuerade filsystem som bygger på öppen källkod och därmed hitta en optimal lösning för dessa användnings-fall. I undersökningen ingick att analysera och jämföra tidigare arbeten där jämförelser mellan pre-standamätningar, dataskydd och kostnader utfördes samt lyfta upp diverse funktionaliteter (snapshotting, multi-tenancy, datadeduplicering, datareplikering) som moderna distribuerade filsy-stem kännetecknas av. Både kommersiella och öppna distribuerade filsystem undersöktes. Även en kostnadsuppskattning för kommersiella och öppna distribuerade filsystem gjordes för att ta reda på lönsamheten för dessa två typer av distribuerat filsystem.Efter att jämförelse och analys av olika tidigare arbeten utfördes, visade sig att det öppna distribue-rade filsystemet Ceph lämpade sig bra som en lösning utifrån kraven som sattes som mål för High Performance Storage och Virtual Machine Storage. Kostnadsuppskattningen visade att det var mer lönsamt att implementera ett öppet distribuerat filsystem. Denna undersökning kan användas som en vägledning vid val mellan olika distribuerade filsystem. / In this thesis, a study of three different uses cases has been made within the field of data storage, which are as following: Cold Storage, High Performance Storage and Virtual Machine Storage. The purpose of the survey is to give an overview of commercial distributed file systems and a deeper study of open source codes distributed file systems in order to find the most optimal solution for these use cases. Within the study, previous works concerning performance, data protection and costs were an-alyzed and compared in means to find different functionalities (snapshotting, multi-tenancy, data duplication and data replication) which distinguish modern distributed file systems. Both commercial and open distributed file systems were examined. A cost estimation for commercial and open distrib-uted file systems were made in means to find out the profitability for these two types of distributed file systems.After comparing and analyzing previous works, it was clear that the open source distributed file sys-tem Ceph was proper as a solution in accordance to the objectives that were set for High Performance Storage and Virtual Machine Storage. The cost estimation showed that it was more profitable to im-plement an open distributed file system. This study can be used as guidance to choose between different distributed file systems.

Context. As the number of organizations using cloud application platforms to host their applications increases, the priority of distributing physical resources within those platforms is increasing simultaneously. The goal is to host a higher quantity of applications per physical server, while at the same time retain a satisfying rate of performance combined with certain scalability. The modern needs of customers occasionally also imply an assurance of certain privacy for their applications. Objectives. In this study two types of instances for hosting applications in cloud application platforms, virtual machines and application containers, are comparatively analyzed. This investigation has the goal to expose advantages and disadvantages between the instances in order to determine which is more appropriate for being used in cloud application platforms, in terms of performance, scalability and user isolation. Methods. The comparison is done on a server running Linux Ubuntu 16.04. The virtual machine is created using Devstack, a development environment of Openstack, while the application container is hosted by Docker. Each instance is running an apache web server for handling HTTP requests. The comparison is done by using different benchmark tools for different key usage scenarios and simultaneously observing the resource usage in respective instance. Results. The results are produced by investigating the user isolation and resource occupation of respective instance, by examining the file system, active process handling and resource allocation after creation. Benchmark tools are executed locally on respective instance, for a performance comparison of the usage of physical resources. The amount of CPU operations executed within a given time is measured in order determine the processor performance, while the speed of read and write operations to the main memory is measured in order to determine the RAM performance. A file is also transmitted between host server and application in order to compare the network performance between respective instance, by examining the transfer speed of the file. Lastly a set of benchmark tools are executed on the host server to measure the HTTP server request handling performance and scalability of each instance. The amount of requests handled per second is observed, but also the resource usage for the request handling at an increasing rate of served requests and clients. Conclusions. The virtual machine is a better choice for applications where privacy is a higher priority, due to the complete isolation and abstraction from the rest of the physical server. Virtual machines perform better in handling a higher quantity of requests per second, while application containers is faster in transferring files through network. The container requires a significantly lower amount of resources than the virtual machine in order to run and execute tasks, such as responding to HTTP requests. When it comes to scalability the prefered type of instance depends on the priority of key usage scenarios. Virtual machines have quicker response time for HTTP requests but application containers occupy less physical resources, which makes it logically possible to run a higher quantity of containers than virtual machines simultaneously on the same physical server.

Cette thèse se place dans le contexte de l’hébergement de services informatiques virtualisés et apporte deux contributions. Elle propose premièrement un système d’aide à la gestion modulaire, déplaçant les machines virtuelles du centre pour le maintenir dans un état satisfaisant. Ce système permet en particulier d’intégrer la notion de consommation électrique des serveurs ainsi que des règles propres à cette consommation. Sa modularité permet de plus l’adaptation de ses composants à des problèmes de grande taille. Cette thèse propose de plus un outil pour comparer différents gestionnaires de centres virtualisés. Cet outil injecte un scénario de montée en charge reproductible dans une infrastructure virtualisée. L’injection d’un tel scénario permet d’évaluer les performances du système de gestion du centre grâce à des sondes spécifiques. Le langage utilisé pour cette injection est extensible et permet l’utilisation de scénarios paramétrés. / This thesis considers the virtualized IT services hosting and makes two contributions. It first proposes a modular system of management aids, to move the virtual machines of the center in order to keep it in a good condition. This system allows in particular to integrate the concept of server power consumption and rules specific to that concept. What’s more, its modularity allows to adjust its components to handle larger problems. This thesis proposes also a tool to compare different virtualized centers managers. This tool injects a reproductible load increase scenario in a virtualized infrastructure. The injection of such a scenario is used to evaluate the performance of the system center manager, using performances probes. The language used for this injection is extensible and allows the creation of parameterized scenarios. The contributions of this thesis were presented in two international conferences and a french conference.