Seamless Application Delivery Using Software Defined Exchanges

One of the main challenges in delivering content over the Internet today is the absence of a centralized monitoring and control system [38]. Software Defined Networking has paved the way to provide a much needed control over network traffic. OpenFlow is now being standardized as part of the Open Networking Foundation, and Software Defined Exchanges (SDXes) provide a framework to use OpenFlow for multi-domain routing. Prototype deployments of Software Defined Exchanges have recently come into existence as a platform for Future Internet Architecture to eliminate the need for core routing technology used in today’s Internet. In this work, we look at how application delivery, in particular, Dynamic Adaptive Streaming over HTTP (DASH) and Nowcasting take advantage of a Software Defined Exchange. We compare unsophisticated controllers to more sophisticated ones which we call a ”load balancer” and find that implementing a good controller for inter-domain routing can result in better network utilization and application performance. We then design, develop and evaluate a prototype for a Content Distribution Network (CDN) that uses resources at SDXes to provide higher quality bitrates for a DASH client

A Roadmap for Benchmarking in Wireless Networks

Experimentation is evolving as a viable and realistic performance analysis approach in wireless networking research. Realism is provisioned by deploying real software (network stack, drivers, OS), and hardware (wireless cards, network equipment, etc.) in the actual physical environment. However, the experimenter is more likely to be dogged by tricky issues because of calibration problems and bugs in the software/hardware tools. This, coupled with difficulty of dealing with multitude of hardware/software parameters and unpredictable characteristics of the wireless channel in the wild, poses significant challenges in the way of experiment repeatability and reproducibility. Furthermore, experimentation has been impeded by the lack of standard definitions, measurement methodologies and full disclosure reports that are particularly important to understand the suitability of protocols and services to emerging wireless application scenarios. Lack of tools to manage large number experiment runs, deal with huge amount of measurement data and facilitate peer-verifiable analysis further complicates the process. In this paper, we present a holistic view of benchmarking in wireless networks and formulate a procedure complemented by step-by-step case study to help drive future efforts on benchmarking in wireless network applications and protocols

E-sense : a wireless sensor network testbed and system for monitoring inbuilding environments

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical references leaves 85-88.Wireless sensor networks consist of small, smart and battery-powered devices suitable for widespread deployment to monitor an environment by taking physical measurements. Wireless sensor nodes are deployed over an area in a random manner. They need to self-establish a wireless multi-hop network and routing paths from all sensor nodes to a central base station. In this thesis, we present our E-Sense system, a wireless sensor network testbed consisting of MICA2 sensor nodes which can be used to monitor an indoor environment like office buildings and homes. The testbed can be accessed through the Internet and provides a webbased interface to the sensor network. The users of the network can be located at any point in the Internet. Via the web based interface, the users can submit various types of queries to the sensor network and get the replies including the physical measurement results. The E-Sense system also includes a distributed and energy-aware routing protocol that we designed and implemented. The protocol aims efficient and balanced usage of energy in the sensor nodes to prolong the lifetime of the network. The routing protocol is based on a many-to-one routing tree where each node independently determines its next parent depending on the values of RSSI (Received Signal Strength Indicator). The protocol can also adjust the transmit power to further decrease the energy spent in each sensor node. The testbed will be useful for experimental studies at both application and network levels.Berker, BerkM.S

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Une approche générique pour l'automatisation des expériences sur les réseaux informatiques

This thesis proposes a generic approach to automate network experiments for scenarios involving any networking technology on any type of network evaluation platform. The proposed approach is based on abstracting the experiment life cycle of the evaluation platforms into generic steps from which a generic experiment model and experimentation primitives are derived. A generic experimentation architecture is proposed, composed of an experiment model, a programmable experiment interface and an orchestration algorithm that can be adapted to network simulators, emulators and testbeds alike. The feasibility of the approach is demonstrated through the implementation of a framework capable of automating experiments using any combination of these platforms. Three main aspects of the framework are evaluated: its extensibility to support any type of platform, its efficiency to orchestrate experiments and its flexibility to support diverse use cases including education, platform management and experimentation with multiple platforms. The results show that the proposed approach can be used to efficiently automate experimentation on diverse platforms for a wide range of scenarios.Cette thèse propose une approche générique pour automatiser des expériences sur des réseaux quelle que soit la technologie utilisée ou le type de plate-forme d'évaluation. L'approche proposée est basée sur l'abstraction du cycle de vie de l'expérience en étapes génériques à partir desquelles un modèle d'expérience et des primitives d'expérimentation sont dérivés. Une architecture générique d'expérimentation est proposée, composée d'un modèle d'expérience générique, d'une interface pour programmer des expériences et d'un algorithme d'orchestration qui peux être adapté aux simulateurs, émulateurs et bancs d'essai de réseaux. La faisabilité de cette approche est démontrée par la mise en œuvre d'un framework capable d'automatiser des expériences sur toute combinaison de ces plateformes. Trois aspects principaux du framework sont évalués : son extensibilité pour s'adapter à tout type de plate-forme, son efficacité pour orchestrer des expériences et sa flexibilité pour permettre des cas d'utilisation divers, y compris l'enseignement, la gestion des plate-formes et l'expérimentation avec des plates-formes multiples. Les résultats montrent que l'approche proposée peut être utilisée pour automatiser efficacement l'expérimentation sur les plates-formes d'évaluation hétérogènes et pour un éventail de scénarios variés

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Optimizing Computations and Allocations on High Performance and Cloud Computing Systems

Over the last decade, many research and development projects have focused on Cloud Computing systems. After forming around the early research papers and the first commercial cloud offerings in 2006-2008, the field has seen a tremendous progress and has provided the primary infrastructure and technology for applications at small, medium, and large scales. Cloud Computing systems have provided diverse on-demand resources to individual researchers and developers, groups and entire institutions, as well as commercial companies and government organizations. Clouds have also found their niche in scientific computing applications, offering attractive alternatives to High Performance Computing models and systems. While cloud economics and technologies have significantly matured recently, there is much active research revolving around topics such as optimality, usability, manageability, and reproducibility in the latest studies. This dissertation presents our findings and relevant developments at the intersection of Cloud Computing and such “flavors” of computing as High Performance Computing and High Throughput Computing. We primarily focus on optimality issues in this area and propose solutions that address the needs of individual researchers and research groups with limited computational and financial resources

Optimizing Computations and Allocations on High Performance and Cloud Computing Systems

Over the last decade, many research and development projects have focused on Cloud Computing systems. After forming around the early research papers and the first commercial cloud offerings in 2006-2008, the field has seen a tremendous progress and has provided the primary infrastructure and technology for applications at small, medium, and large scales. Cloud Computing systems have provided diverse on-demand resources to individual researchers and developers, groups and entire institutions, as well as commercial companies and government organizations. Clouds have also found their niche in scientific computing applications, offering attractive alternatives to High Performance Computing models and systems. While cloud economics and technologies have significantly matured recently, there is much active research revolving around topics such as optimality, usability, manageability, and reproducibility in the latest studies. This dissertation presents our findings and relevant developments at the intersection of Cloud Computing and such “flavors” of computing as High Performance Computing and High Throughput Computing. We primarily focus on optimality issues in this area and propose solutions that address the needs of individual researchers and research groups with limited computational and financial resources