Dynamic Routing Algorithms and Methods for Controlling Traffic Flows of Cloud Applications and Services

Nowadays, we see a steady growth in the use of cloud computing in modern business. This enables to reduce the cost of IT infrastructure owning and operation; however, there are some issues related to the management of data processing centers.One of these issues is the effective use of companies’ computing and network resources. The goal of optimization is to manage the traffic in cloud applications and services within data centers.Taking into account the multitier architecture of modern data centers, we need to pay a special attention to this task. The advantage of modern infrastructure virtualization is the possibility to use software-defined networks and software-defined data storages. However, the existing optimization of algorithmic solutions does not take into account the specific features of the network traffic formation with multiple application types.The task of optimizing traffic distribution for cloud applications and services can be solved by using software-defined infrastructure of virtual data centers.We have developed a simulation model for the traffic in software-defined networks segments of data centers involved in processing user requests to cloud application and services within a network environment.Our model enables to implement the traffic management algorithm of cloud applications and to optimize the access to storage systems through the effective use of data transmission channels. During the experimental studies, we have found that the use of our algorithm enables to decrease the response time of cloud applications and services and, therefore, to increase the productivity of user requests processing and to reduce the number of refusals

Advancing Operating Systems via Aspect-Oriented Programming

Operating system kernels are among the most complex pieces of software in existence to- day. Maintaining the kernel code and developing new functionality is increasingly compli- cated, since the amount of required features has risen significantly, leading to side ef fects that can be introduced inadvertedly by changing a piece of code that belongs to a completely dif ferent context. Software developers try to modularize their code base into separate functional units. Some of the functionality or “concerns” required in a kernel, however, does not fit into the given modularization structure; this code may then be spread over the code base and its implementation tangled with code implementing dif ferent concerns. These so-called “crosscutting concerns” are especially dif ficult to handle since a change in a crosscutting concern implies that all relevant locations spread throughout the code base have to be modified. Aspect-Oriented Software Development (AOSD) is an approach to handle crosscutting concerns by factoring them out into separate modules. The “advice” code contained in these modules is woven into the original code base according to a pointcut description, a set of interaction points (joinpoints) with the code base. To be used in operating systems, AOSD requires tool support for the prevalent procedu- ral programming style as well as support for weaving aspects. Many interactions in kernel code are dynamic, so in order to implement non-static behavior and improve performance, a dynamic weaver that deploys and undeploys aspects at system runtime is required. This thesis presents an extension of the “C” programming language to support AOSD. Based on this, two dynamic weaving toolkits – TOSKANA and TOSKANA-VM – are presented to permit dynamic aspect weaving in the monolithic NetBSD kernel as well as in a virtual- machine and microkernel-based Linux kernel running on top of L4. Based on TOSKANA, applications for this dynamic aspect technology are discussed and evaluated. The thesis closes with a view on an aspect-oriented kernel structure that maintains coherency and handles crosscutting concerns using dynamic aspects while enhancing de- velopment methods through the use of domain-specific programming languages

Market-Based Scheduling in Distributed Computing Systems

In verteilten Rechensystemen (bspw. im Cluster und Grid Computing) kann eine Knappheit der zur Verfügung stehenden Ressourcen auftreten. Hier haben Marktmechanismen das Potenzial, Ressourcenbedarf und -angebot durch geeignete Anreizmechanismen zu koordinieren und somit die ökonomische Effizienz des Gesamtsystems zu steigern. Diese Arbeit beschäftigt sich anhand vier spezifischer Anwendungsszenarien mit der Frage, wie Marktmechanismen für verteilte Rechensysteme ausgestaltet sein sollten

A Comparative Study of Online Scheduling Algorithms for Networks of Workstations

Networks of workstations offer large amounts of unused processing time. Resource management systems are able to exploit this computing capacity by assigning compute-intensive tasks to idle workstations. To avoid interferences between multiple, concurrently running applications, such resource management systems have to schedule application jobs carefully. Continuously arriving jobs and dynamically changing amounts of available CPU capacity make traditional scheduling algorithms difficult to apply in workstation networks. Online scheduling algorithms promise better results by adapting schedules to changing situations. This paper compares six online scheduling algorithms by simulating several workload scenarios. Based on the insights gained by the simulations, the three online scheduling algorithms performing best were implemented in the Winner resource management system. Experiments conducted with Winner in a real workstation network confirm the simulation results obtained. 1 Introducti..