MONROE-Nettest: A Configurable Tool for Dissecting Speed Measurements in Mobile Broadband Networks

As the demand for mobile connectivity continues to grow, there is a strong need to evaluate the performance of Mobile Broadband (MBB) networks. In the last years, mobile "speed", quantified most commonly by data rate, gained popularity as the widely accepted metric to describe their performance. However, there is a lack of consensus on how mobile speed should be measured. In this paper, we design and implement MONROE-Nettest to dissect mobile speed measurements, and investigate the effect of different factors on speed measurements in the complex mobile ecosystem. MONROE-Nettest is built as an Experiment as a Service (EaaS) on top of the MONROE platform, an open dedicated platform for experimentation in operational MBB networks. Using MONROE-Nettest, we conduct a large scale measurement campaign and quantify the effects of measurement duration, number of TCP flows, and server location on measured downlink data rate in 6 operational MBB networks in Europe. Our results indicate that differences in parameter configuration can significantly affect the measurement results. We provide the complete MONROE-Nettest toolset as open source and our measurements as open data.Comment: 6 pages, 3 figures, submitted to INFOCOM CNERT Workshop 201

On the User Perception of Configurable Reference Process Models - Initial Insights

Enterprise Systems potentially lead to significant efficiency gains but require a well-conducted configuration process. A configurable reference modelling language based on the widely used EPC notation, which can be used to specify Configurable EPCs (C-EPCs), has been developed to support the task of Enterprise Systems configuration. This paper presents a laboratory experiment on C-EPCs and discusses empirical data on the comparison of C-EPCs to regular EPCs. Using the Method Adoption Model we report on modeller’s perceptions as to the usefulness and ease of use of C-EPCs, concluding that C-EPCs provide sufficient yet improvable conceptual support towards reference model configuration

Business Process Configuration According to Data Dependency Specification

Configuration techniques have been used in several fields, such as the design of business process models. Sometimes these models depend on the data dependencies, being easier to describe what has to be done instead of how. Configuration models enable to use a declarative representation of business processes, deciding the most appropriate work-flow in each case. Unfortunately, data dependencies among the activities and how they can affect the correct execution of the process, has been overlooked in the declarative specifications and configurable systems found in the literature. In order to find the best process configuration for optimizing the execution time of processes according to data dependencies, we propose the use of Constraint Programming paradigm with the aim of obtaining an adaptable imperative model in function of the data dependencies of the activities described declarative.Ministerio de Ciencia y Tecnología TIN2015-63502-C3-2-RFondo Europeo de Desarrollo Regiona

Techniques for the dynamic randomization of network attributes

Critical infrastructure control systems continue to foster predictable communication paths and static configurations that allow easy access to our networked critical infrastructure around the world. This makes them attractive and easy targets for cyber-attack. We have developed technologies that address these attack vectors by automatically reconfiguring network settings. Applying these protective measures will convert control systems into «moving targets» that proactively defend themselves against attack. This «Moving Target Defense» (MTD) revolves about the movement of network reconfiguration, securely communicating reconfiguration specifications to other network nodes as required, and ensuring that connectivity between nodes is uninterrupted. Software-defined Networking (SDN) is leveraged to meet many of these goals. Our MTD approach eliminates adversaries targeting known static attributes of network devices and systems, and consists of the following three techniques: (1) Network Randomization for TCP/UDP Ports; (2) Network Randomization for IP Addresses; (3) Network Randomization for Network Paths In this paper, we describe the implementation of the aforementioned technologies. We also discuss the individual and collective successes for the techniques, challenges for deployment, constraints and assumptions, and the performance implications for each technique

MiceTrap: scalable traffic engineering of datacenter mice flows using OpenFlow

Datacenter network topologies are inherently built with enough redundancy to offer multiple paths between pairs of end hosts for increased flexibility and resilience. On top, traffic engineering (TE) methods are needed to utilize the abundance of bisection bandwidth efficiently. Previously proposed TE approaches differentiate between long-lived flows (elephant flows) and short-lived flows (mice flows), using dedicated traffic management techniques to handle elephant flows, while treating mice flows with baseline routing methods. We show through an example that such an approach can cause congestion to short-lived (but not necessarily less critical) flows. To overcome this, we propose MiceTrap, an OpenFlow-based TE approach targeting datacenter mice flows. MiceTrap employs scalability against the number of mice flows through flow aggregation, together with a software-configurable weighted routing algorithm that offers improved load balancing for mice flows