OPEN DOORS AND OPEN MINDS: WHAT FACULTY AUTHORS CAN DO TO ENSURE OPEN ACCESS TO THEIR WORK THROUGH THEIR INSTITUTION

The Internet has brought unparalleled opportunities for expanding availability of research by bringing down economic and physical barriers to sharing. The digitally networked environment promises to democratize access, carry knowledge beyond traditional research niches, accelerate discovery, encourage new and interdisciplinary approaches to ever more complex research challenges, and enable new computational research strategies. However, despite these opportunities for increasing access to knowledge, the prices of scholarly journals have risen sharply over the past two decades, often forcing libraries to cancel subscriptions. Today even the wealthiest institutions cannot afford to sustain all of the journals needed by their faculties and students. To take advantage of the opportunities created by the Internet and to further their mission of creating, preserving, and disseminating knowledge, many academic institutions are taking steps to capture the benefits of more open research sharing. Colleges and universities have built digital repositories to preserve and distribute faculty scholarly articles and other research outputs. Many individual authors have taken steps to retain the rights they need, under copyright law, to allow their work to be made freely available on the Internet and in their institutionâ s repository. And, faculties at some institutions have adopted resolutions endorsing more open access to scholarly articles. Most recently, on February 12, 2008, the Faculty of Arts and Sciences (FAS) at Harvard University took a landmark step. The faculty voted to adopt a policy requiring that faculty authors send an electronic copy of their scholarly articles to the universityâ s digital repository and that faculty authors automatically grant copyright permission to the university to archive and to distribute these articles unless a faculty member has waived the policy for a particular article. Essentially, the faculty voted to make open access to the results of their published journal articles the default policy for the Faculty of Arts and Sciences of Harvard University. As of March 2008, a proposal is also under consideration in the University of California system by which faculty authors would commit routinely to grant copyright permission to the university to make copies of the facultyâ s scholarly work openly accessible over the Internet. Inspired by the example set by the Harvard faculty, this White Paper is addressed to the faculty and administrators of academic institutions who support equitable access to scholarly research and knowledge, and who believe that the institution can play an important role as steward of the scholarly literature produced by its faculty. This paper discusses both the motivation and the process for establishing a binding institutional policy that automatically grants a copyright license from each faculty member to permit deposit of his or her peer-reviewed scholarly articles in institutional repositories, from which the works become available for others to read and cite.

Fast Approximate Reconciliation of Set Differences

We present new, simple, efficient data structures for approximate reconciliation of set differences, a useful standalone primitive for peer-to-peer networks and a natural subroutine in methods for exact reconciliation. In the approximate reconciliation problem, peers A and B respectively have subsets of elements SA and SB of a large universe U. Peer A wishes to send a short message M to peer B with the goal that B should use M to determine as many elements in the set SB–SA as possible. To avoid the expense of round trip communication times, we focus on the situation where a single message M is sent. We motivate the performance tradeoffs between message size, accuracy and computation time for this problem with a straightforward approach using Bloom filters. We then introduce approximation reconciliation trees, a more computationally efficient solution that combines techniques from Patricia tries, Merkle trees, and Bloom filters. We present an analysis of approximation reconciliation trees and provide experimental results comparing the various methods proposed for approximate reconciliation.

Adaptive Reliable Multicast

An increasing number of applications, such as distributed interactive simulation, live auctions, distributed games and collaborative systems, require the network to provide a reliable multicast service. This service enables one sender to reliably transmit data to multiple receivers. Reliability is traditionally achieved by having receivers send negative acknowledgments (NACKs) to request from the sender the retransmission of lost (or missing) data packets. However, this Automatic Repeat reQuest (ARQ) approach results in the well-known NACK implosion problem at the sender. Many reliable multicast protocols have been recently proposed to reduce NACK implosion. But, the message overhead due to NACK requests remains significant. Another approach, based on Forward Error Correction (FEC), requires the sender to encode additional redundant information so that a receiver can independently recover from losses. However, due to the lack of feedback from receivers, it is impossible for the sender to determine how much redundancy is needed. In this paper, we propose a new reliable multicast protocol, called ARM for Adaptive Reliable Multicast. Our protocol integrates ARQ and FEC techniques. The objectives of ARM are (1) reduce the message overhead due to NACK requests, (2) reduce the amount of data transmission, and (3) reduce the time it takes for all receivers to receive the data intact (without loss). During data transmission, the sender periodically informs the receivers of the number of packets that are yet to be transmitted. Based on this information, each receiver predicts whether this amount is enough to recover its losses. Only if it is not enough, that the receiver requests the sender to encode additional redundant packets. Using ns simulations, we show the superiority of our hybrid ARQ-FEC protocol over the well-known Scalable Reliable Multicast (SRM) protocol.

Extending snBench to Support a Video-Based Intrusion Detection and Alerting System with a Centralized Hash Table

In this project we design and implement a centralized hashing table in the snBench sensor network environment. We discuss the feasibility of this approach and compare and contrast with the distributed hashing architecture, with particular discussion regarding the conditions under which a centralized architecture makes sense. There are numerous computational tasks that require persistence of data in a sensor network environment. To help motivate the need for data storage in snBench we demonstrate a practical application of the technology whereby a video camera can monitor a room to detect the presence of a person and send an alert to the appropriate authorities.