A Peer-to-Peer Middleware Framework for Resilient Persistent Programming

The persistent programming systems of the 1980s offered a programming model that integrated computation and long-term storage. In these systems, reliable applications could be engineered without requiring the programmer to write translation code to manage the transfer of data to and from non-volatile storage. More importantly, it simplified the programmer's conceptual model of an application, and avoided the many coherency problems that result from multiple cached copies of the same information. Although technically innovative, persistent languages were not widely adopted, perhaps due in part to their closed-world model. Each persistent store was located on a single host, and there were no flexible mechanisms for communication or transfer of data between separate stores. Here we re-open the work on persistence and combine it with modern peer-to-peer techniques in order to provide support for orthogonal persistence in resilient and potentially long-running distributed applications. Our vision is of an infrastructure within which an application can be developed and distributed with minimal modification, whereupon the application becomes resilient to certain failure modes. If a node, or the connection to it, fails during execution of the application, the objects are re-instantiated from distributed replicas, without their reference holders being aware of the failure. Furthermore, we believe that this can be achieved within a spectrum of application programmer intervention, ranging from minimal to totally prescriptive, as desired. The same mechanisms encompass an orthogonally persistent programming model. We outline our approach to implementing this vision, and describe current progress.Comment: Submitted to EuroSys 200

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

The role of response mechanisms in determining reaction time performance: Piéron’s Law revisited

A response mechanism takes evaluations of the importance of potential actions and selects the most suitable. Response mechanism function is a nontrivial problem that has not received the attention it deserves within cognitive psychology. In this article, we make a case for the importance of considering response mechanism function as a constraint on cognitive processes and emphasized links with the wider problem of behavioral action selection. First, we show that, contrary to previous suggestions, a well–known model of the Stroop task (Cohen, Dunbar, & McClelland, 1990) relies on the response mechanism for a key feature of its results—the interference–facilitation asymmetry. Second, we examine a variety of response mechanisms (including that in the model of Cohen et al., 1990) and show that they all follow a law analogous to Piéron's law in relating their input to reaction time. In particular, this is true of a decision mechanism not designed to explain RT data but based on a proposed solution to the general problem of action selection and grounded in the neurobiology of the vertebrate basal ganglia. Finally, we show that the dynamics of simple artificial neurons also support a Piéron–like law