Implementing Network Protocols as Distributed Logic Programs

Declarative networking [2, 4, 3, 1] is an application of database query-language and processing techniques to the domain of networking. Declarative networking is based on the observation that network protocols deal at their core with computing and maintaining distributed state (e.g., routes, sessions, performance statistics) according to basic information locally available at each node (e.g., neighbor tables, link measurements, local clocks) while enforcing constraints such as local routing policies. Recursive query languages studied in the deductive database literature [6] are a natural fit for expressing the relationship between base data, derived data, and the associated constraints. Simple extensions to these languages and their implementations enable the natural expression and efficient execution of network protocols. Declarative networking aims to accelerate the process of specifying, implementing, experimenting with and evolving designs for network architectures. Declarative networking can reduce program sizes of distributed protocols by orders of magnitude relative to traditional approaches. In addition to serving as a platform for rapid prototyping of network protocols, declarative networking also open up opportunities for automatic protocol optimization and hybridization, program checking and debugging. This paper presents an introduction to declarative networking using a simple routing protocol example. For more details on declarative networking related projects, refer to the NetDB@Penn website [5], and the RapidNet [7] declarative networking engine

Surface coatings and catalyst production by electrodeposition

Electrodeposition and electrocodeposition in low gravity are discussed. The goal is to provide a better understanding of the role of convection and buoyancy in the mechanisms of formation of some electrodeposited surfaces, fluid flow in the vicinity of electrodepositing surfaces, the influence of a moving medium upon codeposition, the effect of gravity upon the dispersion (coagulation) of neutral particles that are desired for codeposition and preparation of improved surface coatings and metal catalysts

Peer-To-Peer Backup for Personal Area Networks

FlashBack is a peer-to-peer backup algorithm designed for power-constrained devices running in a personal area network (PAN). Backups are performed transparently as local updates initiate the spread of backup data among a subset of the currently available peers. Flashback limits power usage by avoiding flooding and keeping small neighbor sets. Flashback has also been designed to utilize powered infrastructure when possible to further extend device lifetime. We propose our architecture and algorithms, and present initial experimental results that illustrate FlashBack’s performance characteristic

Maintaining Distributed Recursive Views Incrementally

This paper proposes an algorithm to compute incrementally the changes to distributed recursive database views in response to insertions and deletions of base facts. Our algorithm uses a pipelined semi-näıve (PSN) evaluation strategy introduced in declarative networking. Unlike prior work, our algorithm is formally proven to be correct for recursive query computation in the presence of message reordering in the system. Our proof proceeds in two stages. First, we show that all the operations performed by our PSN algorithm computes the same set of results as traditional centralized semi-näıve evaluation. Second, we prove that our algorithm terminates, even in the presence of cyclic derivations due to recursion

Real-Time MapReduce Scheduling

In this paper, we explore the feasibility of enabling the scheduling of mixed hard and soft real-time MapReduce applications. We first present an experimental evaluation of the popular Hadoop MapReduce middleware on the Amazon EC2 cloud. Our evaluation reveals tradeoffs between overall system throughput and execution time predictability, as well as highlights a number of factors affecting real-time scheduling, such as data placement, concurrent users, and master scheduling overhead. Based on our evaluation study, we present a formal model for capturing real-time MapReduce applications and the Hadoop platform. Using this model, we formulate the offline scheduling of real-time MapReduce jobs on a heterogeneous distributed Hadoop architecture as a constraint satisfaction problem (CSP) and introduce various search strategies for the formulation. We propose an enhancement of MapReduce’s execution model and a range of heuristic techniques for the online scheduling. We further outline some of our future directions that apply state-of-the-art techniques in the real-time scheduling literature

MOSAIC: Unified Platform for Dynamic Overlay Selection and Composition

MOSAIC constructs new overlay networks with desired characteristics by composing existing overlays with subsets of those attributes. Thus, MOSAIC overcomes the problem of multiple network infrastructures that are partial solutions, while preserving deployability. Composition of control and/or data planes is possible in the system. MOSAIC overlays are specified in Mozlog, a declarative language that specifies overlay properties without binding them to a particular implementation or underlying network. This paper focuses on the runtime aspects of MOSAIC: how it enables interoperability between different overlay networks and how it implements switching between different overlay compositions, permitting dynamic compositions with both existing overlay networks and legacy applications. The system is validated experimentally using declarative overlay compositions concisely specified in Mozlog: an indirection overlay that supports mobility (i3), a resilient overlay (RON), and scalable lookups (Chord), all of which are combined to provide new functionality. MOSAIC provides the benefits of runtime composition to simultaneously deliver application-aware mobility, NAT traversal and reliability with low performance overhead, demonstrated by measurements on both a local cluster and PlanetLab