Fairness is an increasingly important concern as machine learning models are used to support decision making in high-stakes applications such as mortgage lending, hiring, and prison sentencing. This paper introduces a new open source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360), released under an Apache v2.0 license (https://github.com/ibm/aif360). The main objectives of this toolkit are to help facilitate the transition of fairness research algorithms to use in an industrial setting and to provide a common framework for fairness researchers to share and evaluate algorithms.The package includes a comprehensive set of fairness metrics for datasets and models, explanations for these metrics, and algorithms to mitigate bias in datasets and models. It also includes an interactive Web experience (https://aif360.mybluemix.net) that provides a gentle introduction to the concepts and capabilities for line-of-business users, as well as extensive documentation, usage guidance, and industry-specific tutorials to enable data scientists and practitioners to incorporate the most appropriate tool for their problem into their work products. The architecture of the package has been engineered to conform to a standard paradigm used in data science, thereby further improving usability for practitioners. Such architectural design and abstractions enable researchers and developers to extend the toolkit with their new algorithms and improvements, and to use it for performance benchmarking. A built-in testing infrastructure maintains code quality.

Absrrucr-The congestion control mechanisms used in TCP have been the focus of numerous studies and have undergone a number of enhancements. However, even with these enhancements, TCP connections still experience alarmingly high loss rates, especially during times of congestion. To alleviate this problem, the IETF is considering active queue management mechanisms, such as RED, for deployment in the network. In this paper, we first show that the effectiveness of RED depends, to a large extent, on the appropriate parameterization of the RED queue. We then show that there is no single set of RED parameters that work well under different congestion scenarios. In light of this observation, we propose and experiment with more a d a p tive RED gateways which self-parameterize themselves based on the traffic mix. Our results show that traffic cognizant parameterization of RED gateways can effectively reduce packet loss while maintaining high link utilizations under a range of network loads.KqwordsCongestion control, Internet, TCP, RED, queue management.

The Internet today provides no support for privacy or authentication of multicast packet. However, an increasing number of applications will require secure multicast senices in order to restrict group membership and enforce accountability of group members. A major problem associated with the deployment of secure multicast delivery services is the scalability of the key distribution protocoL This is particularly true with regard to the handling of group membership changes, such as member departures and/or expulsions, which necessitate the distribution of a new session key to all the remaining group members.As the frequency of group membership changes increases, it becomes necessary to reduce the cost of key distribution operations. This paper explores the use of batching of group membership changes to reduce the frequency, and hence the cost, of key redistribution operations. It focuses explicitly on the problem of cumulnrive member removal and present an algorithm that minimizes the number of messages required to distribute new keys to the remaining group members. The algorithmis used in conjunction with a new multicast key management scheme which uses a set of auxiliary keys in order to improve scalability. In contrast to previous schemes which generate a fixed hierarchy of keys, the proposed scheme dynamically generates the most suitable key hierarchy by composing different keys. Our cumulative member removal algorithm uses Boolean function minimization techniques, and outperforms all other schemes known to us in terms of message complexity.

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The Internet transport infrastructure is moving toward a model of high-speed routers interconnected by intelligent optical core networks. A consensus is emerging in the industry on utilizing an IP-centric control plane within optical networks to support dynamic provisioning and restoration of lightpaths. At the same time, there are divergent views on how IP routers must interact with optical core networks to achieve end-to-end connectivity. This article describes the architectural alternatives for interconnecting IP routers over optical networks, considering the routing and signaling issues. Also, the application of IP-based protocols for dynamic provisioning and restoration of lightpaths, as well as the interworking of multivendor optical networks is described.