The legality of deep packet inspection

Deep packet inspection is a technology which enables the examination of the content of information packets being sent over the Internet. The Internet was originally set up using “end-to-end connectivity” as part of its design, allowing nodes of the network to send packets to all other nodes of the network, without requiring intermediate network elements to maintain status information about the transmission. In this way, the Internet was created as a “dumb” network, with “intelligent” devices (such as personal computers) at the end or “last mile” of the network. The dumb network does not interfere with an application's operation, nor is it sensitive to the needs of an application, and as such it treats all information sent over it as (more or less) equal. Yet, deep packet inspection allows the examination of packets at places on the network which are not endpoints, In practice, this permits entities such as Internet service providers (ISPs) or governments to observe the content of the information being sent, and perhaps even manipulate it. Indeed, the existence and implementation of deep packet inspection may challenge profoundly the egalitarian and open character of the Internet. This paper will firstly elaborate on what deep packet inspection is and how it works from a technological perspective, before going on to examine how it is being used in practice by governments and corporations. Legal problems have already been created by the use of deep packet inspection, which involve fundamental rights (especially of Internet users), such as freedom of expression and privacy, as well as more economic concerns, such as competition and copyright. These issues will be considered, and an assessment of the conformity of the use of deep packet inspection with law will be made. There will be a concentration on the use of deep packet inspection in European and North American jurisdictions, where it has already provoked debate, particularly in the context of discussions on net neutrality. This paper will also incorporate a more fundamental assessment of the values that are desirable for the Internet to respect and exhibit (such as openness, equality and neutrality), before concluding with the formulation of a legal and regulatory response to the use of this technology, in accordance with these values.

Process makes perfect: High-performance design creates healthy environments for high-performance learning

Considering the staggering benefits of high-performance schools, it seems an obvious choice to “go green.” High-performance schools offer an exceptionally cost-effective means to enhance student learning, using on average 33 percent less energy than conventionally designed schools, and provide substantial health gains, including reduced respiratory problems and absenteeism. According to the 2006 study, Greening America's Schools, Costs and Benefits, co-sponsored by the American Institute of Architects (AIA) and Capital E, a green building consulting firm, high-performance lighting is a key element of healthy learning environments, contributing to improved test scores, reduced off-task behavior, and higher achievement among students. Few argue this point more convincingly than architect Heinz Rudolf, of Portland-Oregon-based Boora Architects, who has designed sustainable schools for more than 80 school districts in Oregon, Washington, Colorado, and Wyoming, and has pioneered the high-performance school movement. Boora's recently completed project, the Baker Prairie Middle School in Canby, Oregon is one of the most sustainable K-12 facilities in the state, and illustrates Rudolf's progressive and research-intensive approach to school design.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.