Carlos Alberto Kamienski

Better network traffic identification through the independent combination of techniques

Traffic identification is currently an important challenge for network management and dimensioning. In recent years, some new algorithms and the different uses of known techniques have been proposed, yet the results are so far limited in scope and frequently disappointing. Furthermore, existing results cannot be directly compared, since networks and traffic profiles differ significantly among collected traces. When submitted to an analysis, considering different networks, data granularities and baselines, most algorithms perform well in one or two scenarios. However, no algorithm has proven better than the others in the majority of the scenarios. Summarizing four years of research in traffic identification, this work shows that the identification abilities of algorithms vary for different situations and proposes a new methodology for traffic identification through the combination of any set of algorithms for traffic identification. Four different combination mechanisms (and many variations) are validated against four different network scenarios that are commonly used in the literature. Combination shows promising results, mainly because it revealed to be robust against bias towards any scenario, which happens in previous identification algorithms.

A stratified traffic sampling methodology for seeing the big picture

This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as powerful tools for deriving traffic properties at the flow level. Our results show that the adequate selection of samples leads to significant improvements allowing further important statistical analysis. Although stratified sampling is a well-known technique, the way we classify the data prior to sampling is innovative and deserves special attention. We evaluate two partitioning clustering methods, namely clustering large applications (CLARA) and K-means, and validate their outcomes by using them as thresholds for stratified sampling. We show that using flow sizes to divide the population we can obtain accurate estimates for both size and flow durations. The presented sampling and clustering classification techniques achieve data reduction levels higher than that of existing methods, on the order of 0.1% while maintaining good accuracy for the estimates of the sum, mean and variance for both flow duration and sizes.

PBMAN: a Policy-based Management Framework for Ambient Networks

Ambient networks aim at providing new networking solutions to highly mobile users considering a mix of current and future wireless technologies. In the last years, policy-based approaches have been proposed as an effective way of managing large networks, e.g. the IETF policy framework. In this paper, we present the design and implementation of PBMAN, a Policy-based Management Framework for Ambient Networks. PBMAN is based on a P2P infrastructure, aimed at providing scalability and self-configuration features

XACML-Based Composition Policies for Ambient Networks

Ambient Networks (AN) pose new challenges to the management discipline, and policies are considered to be an adequate solution for providing flexibility, distributed control, and self-management features. However, the current state-of the art IETF policy framework was not designed for the challenges of new 3G/4G environments such as AN. This paper presents PBMAN, a policy-based architecture and a composition framework that extends the AN architecture, where policies are intrinsically at the underlying layer by design and not as a later ad-on. The use of policies and their interaction with network composition is the main research challenge of PBMAN. The current architecture has been designed based on previous experience, on a design-implement-test development cycle. The framework was used to model a video on demand scenario, whereto composition policies based on an extended version of the XACML policy language have been written.

The case for interdomain dynamic QoS-based service negotiation in the internet

The evolution of the Internet towards a global infrastructure for real time voice and video applications involves providing stringent Quality of Service (QoS) levels. Although some architectures, such as IntServ and DiffServ, have been defined and implemented, end-to-end QoS remains an unresolved problem. Recently, there has been a trend to deal with QoS at a higher-level layer, in the form of an overlay network. However, little attention has been given to the influence of the current domain interconnection structures in providing the right incentives and evolution paths towards QoS deployment. In this paper, we look at the Internet trying to identify the main problems and limitations of current interconnection models that impact QoS, as well as we suggest and evaluate evolution strategies for end-to-end QoS deployment. Particularly, we state the case for the interdomain dynamic QoS-based service negotiation in the Internet through an overlay network. This phase is needed before any end-to-end resource provisioning takes place. Three service negotiation models are presented and compared through simulation and analyses.

Service creation and execution with the Service Refinement Cycle

Service composition is today mostly a manual process and automated service creation techniques are not ready for prime time in IT and network system development. This paper presents the Service Refinement Cycle as an integrated framework for dealing with the service lifecycle composed of stages like service creation, deployment, execution and management. The main realization of the cycle is the Service Code, which contains executable specifications (code) that may run at any compatible engine.

A step towards understanding Joost IPTV

Recently, peer-to-peer (P2P) streaming applications have drawn attention to both users and research community. The P2P approach for IPTV has the appealing feature of providing TV-like quality content distribution service (for both on-demand and live TV), which has been attracting a large number of users from across the globe. However, there is very little understanding about their network architecture and resource consumption. This work aims at having an in-depth understanding of Joost, a video-on-demand P2P system for distributing TV content, created by Skype and Kazaa founders. Results show that Joost relies on UDP for content delivery with an asymmetric bandwidth consumption of until 750 Kbps (download) and 480 Kbps (upload). We also evaluated the Joost control plane, which is mainly based on TCP. Along with other P2P IPTV technologies, such systems could have a great impact on network bandwidth utilization, even more than P2P file transfer ones.

On the use of peer-to-peer architectures for the management of highly dynamic environments

Scalable distributed management is a key challenge for current Internet services and necessary for future ubiquitous services of wireless mobile users. Policy-based management (PBM) is seen as a practical solution for dealing with the needs of new advanced services for highly dynamic wireless environments. The IETF developed a two-tier client/server PBM framework, yet it requires some important extensions in such environments. In this paper we look into new management mechanisms for dealing with these limitations by proposing the peer-to-peer policy management infrastructure (P4MI), a PBM framework based on peer-to-peer technology as the main enabling mechanism. We instantiate this abstract framework to ambient networks, a new concept aimed at creating network solutions for new mobile and wireless systems. We show that the P4MI is both a scalable and a complete PBM solution for coping with the challenges of ambient networks

IoT Link: An Internet of Things Prototyping Toolkit

The Internet of Things (IoT) application development is a complex task that requires a wide range of expertise. Currently, the IoT community lacks a development toolkit that enables inexperienced developers to develop IoT prototypes rapidly. Filling this gap, we propose a development toolkit based on a model-driven approach, called IoT Link. IoT Link allows inexperienced developers to compose mash up applications through a graphical domain-specific language that can be easily configured and wired together to create an IoT application. Through visual components, IoT Link encapsulates the complexity of communicating with devices and services on the internet and abstracts them as virtual objects that are accessible through different communication technologies. Consequently, it solves interoperability between heterogeneous IoT components. Based on the visual model, IoT Link is able to generate a complete Java project including an extendable Java code. In a controlled experiment, IoT Link was 42% faster than using a Java library and able to outperform the Java librarys user satisfactions.

Workflow specification and scheduling with security constraints in hybrid clouds

Hybrid cloud management must deal with resources from both public and private clouds, as well as their interaction. When workflows are executed in a hybrid cloud, dependencies among their components bring new factors to be considered during specification, scheduling, and virtual machine provisioning. In this paper, we describe three components, namely workflow code, scheduler, and resource allocator, which enable the specification and execution of workflows in hybrid clouds in the context of the AltoStratus middleware. We present a case study that shows the interaction among these components, and their applicability in practice.