Existing approaches to computing-based cyber undergraduate majors typically take one of two forms: a broad exploration of both technical and human aspects, or a deep technical exploration of a single discipline relevant to cybersecurity. This paper describes the creation of a third approach--a multifarious major, consistent with Cybersecurity Curricula 2017, the ABET Cybersecurity Program Criteria, and the National Security Agency Center for Academic Excellence--Cyber Operations criteria. Our novel curriculum relies on a 10-course common foundation extended by one of five possible concentrations, each of which is delivered through a disciplinary lens and specialized into a highly relevant computing interest area serving society's diverse cyber needs. The journey began years ago when we infused cybersecurity education throughout our programs, seeking to keep offerings and extracurricular activities relevant in society's increasingly complex relationship with cyberspace. This paper details the overarching design principles, decision-making process, benchmarking, and feedback elicitation activities. A surprising key step was merging several curricula proposals into a single hybrid option. The new major attracted a strong initial cohort, meeting our enrollment goals and exceeding our diversity goals. We provide several recommendations for any institution embarking on a process of designing a new cyber-named major.

The P4 language enables a range of new network applications. However, it is still far from easy to implement and optimize P4 programs for PISA hardware. Programmers must engage in a tedious "trial and error" process wherein they write their program (guessing it will fit within the hardware) and then check by compiling it. If it fails, they repeat the process. In this paper, we argue that programmers should define elastic data structures that stretch automatically to make use of available switch resources. We present P4All, an extension of P4 that supports elastic switch programming. Elastic data structures also make P4All modules reusable across different applications and hardware targets, where resource needs and constraints may vary.Our design is oriented around use of symbolic primitives (integers that may take on a range of possible values at compile time), arrays, and loops. We show how to use these primitive mechanisms to build a range of reusable libraries such as hash tables, Bloom filters, sketches, and key-value stores. We also explain the important role that elasticity plays in modular programming, and we allow programmers to declare utility functions that control the relative share of data-plane resources apportioned to each module.

Managing and securing networks requires collecting and analyzing network traffic data in real time. Existing telemetry systems do not allow operators to express the range of queries needed to perform management or scale to large traffic volumes and rates. We present Sonata, an expressive and scalable telemetry system that coordinates joint collection and analysis of network traffic. Sonata provides a declarative interface to express queries for a wide range of common telemetry tasks; to enable real-time execution, Sonata partitions each query across the stream processor and the data plane, running as much of the query as it can on the network switch, at line rate. To optimize the use of limited switch memory, Sonata dynamically refines each query to ensure that available resources focus only on traffic that satisfies the query. Our evaluation shows that Sonata can support a wide range of telemetry tasks while reducing the workload for the stream processor by as much as seven orders of magnitude compared to existing telemetry systems.

The concern over the quality of delivering video streaming services in mobile wireless networks is addressed in this work. A framework that enhances the Quality of Experience (QoE) of end users through a quality driven resource allocation scheme is proposed. To play a key role, an objective no-reference quality metric, Pause Intensity (PI), is adopted to derive a resource allocation algorithm for video streaming. The framework is examined in the context of 3GPP Long Term Evolution (LTE) systems. The requirements and structure of the proposed PI-based framework are discussed, and results are compared with existing scheduling methods on fairness, efficiency and correlation (between the required and allocated data rates). Furthermore, it is shown that the proposed framework can produce a trade-off between the three parameters through the QoE-aware resource allocation process.

Software-defined networks (SDNs) are a new kind of network architecture in which a controller machine manages a distributed collection of switches by instructing them to install or uninstall packet-forwarding rules and report traffic statistics. The recently formed Open Networking Consortium, whose members include Google, Facebook, Microsoft, Verizon, and others, hopes to use this architecture to transform the way that enterprise and data center networks are implemented.

Modern networks provide a variety of interrelated services including routing, traffic monitoring, load balancing, and access control. Unfortunately, the languages used to program today's networks lack modern features - they are usually defined at the low level of abstraction supplied by the underlying hardware and they fail to provide even rudimentary support for modular programming. As a result, network programs tend to be complicated, error-prone, and difficult to maintain.