Scalable Reliable SD Erlang Design

This technical report presents the design of Scalable Distributed (SD) Erlang: a set of language-level changes that aims to enable Distributed Erlang to scale for server applications on commodity hardware with at most 100,000 cores. We cover a number of aspects, specifically anticipated architecture, anticipated failures, scalable data structures, and scalable computation. Other two components that guided us in the design of SD Erlang are design principles and typical Erlang applications. The design principles summarise the type of modifications we aim to allow Erlang scalability. Erlang exemplars help us to identify the main Erlang scalability issues and hypothetically validate the SD Erlang design

State of Alaska Election Security Project Phase 2 Report

A laska’s election system is among the most secure in the country, and it has a number of safeguards other states are now adopting. But the technology Alaska uses to record and count votes could be improved— and the state’s huge size, limited road system, and scattered communities also create special challenges for insuring the integrity of the vote. In this second phase of an ongoing study of Alaska’s election security, we recommend ways of strengthening the system—not only the technology but also the election procedures. The lieutenant governor and the Division of Elections asked the University of Alaska Anchorage to do this evaluation, which began in September 2007.Lieutenant Governor Sean Parnell. State of Alaska Division of Elections.List of Appendices / Glossary / Study Team / Acknowledgments / Introduction / Summary of Recommendations / Part 1 Defense in Depth / Part 2 Fortification of Systems / Part 3 Confidence in Outcomes / Conclusions / Proposed Statement of Work for Phase 3: Implementation / Reference

A Taxonomy of Self-configuring Service Discovery Systems

We analyze the fundamental concepts and issues in service discovery. This analysis places service discovery in the context of distributed systems by describing service discovery as a third generation naming system. We also describe the essential architectures and the functionalities in service discovery. We then proceed to show how service discovery fits into a system, by characterizing operational aspects. Subsequently, we describe how existing state of the art performs service discovery, in relation to the operational aspects and functionalities, and identify areas for improvement