Distributed design of network codes for wireless multiple unicasts

Previous results on network coding for low-power wireless transmissions of multiple unicasts rely on opportunistic coding or centralized optimization to reduce the power consumption. This paper proposes a distributed strategy for reducing the power consumption in a network coded wireless network with multiple unicasts. We apply a simple network coding strategy called “reverse carpooling,” which uses only XOR and forwarding operations. In this paper, we use the rectangular grid as a simple network model and attempt to increase network coding opportunities without the overhead required for centralized design or coordination. The proposed technique designates “reverse carpooling lines” analogous to a collection of bus routes in a crowded city. Each individual unicast then chooses a route from its source to its destination independently but in a manner that maximizes the fraction of its path spent on reverse carpooling lines. Intermediate nodes apply reverse carpooling opportunistically along these routes. Our network optimization attempts to choose the reverse carpooling lines in a manner that maximizes the expected power savings with respect to the random choice of sources and sinks

Peer to Peer Optimistic Collaborative Editing on XML-like trees

Collaborative editing consists in editing a common document shared by several independent sites. This may give rise to conficts when two different users perform simultaneous uncompatible operations. Centralized systems solve this problem by using locks that prevent some modifications to occur and leave the resolution of confict to users. On the contrary, peer to peer (P2P) editing doesn't allow locks and the optimistic approach uses a Integration Transformation IT that reconciliates the conficting operations and ensures convergence (all copies are identical on each site). Two properties TP1 and TP2, relating the set of allowed operations Op and the transformation IT, have been shown to ensure the correctness of the process. The choice of the set Op is crucial to define an integration operation that satisfies TP1 and TP2. Many existing algorithms don't satisfy these properties and are indeed incorrect i.e. convergence is not guaranteed. No algorithm enjoying both properties is known for strings and little work has been done for XML trees in a pure P2P framework (that doesn't use time-stamps for instance). We focus on editing unranked unordered labeled trees, so-called XML-like trees that are considered for instance in the Harmony pro ject. We show that no transformation satisfying TP1 and TP2 can exist for a first set of operations but we show that TP1 and TP2 hold for a richer set of operations. We show how to combine our approach with any convergent editing process on strings (not necessarily based on integration transformation) to get a convergent process

Optimal measurements to access classical correlations of two-qubit states

We analyze the optimal measurements accessing classical correlations in arbitrary two-qubit states. Two-qubit states can be transformed into the canonical forms via local unitary operations. For the canonical forms, we investigate the probability distribution of the optimal measurements. The probability distribution of the optimal measurement is found to be centralized in the vicinity of a specific von Neumann measurement, which we call the maximal-correlation-direction measurement (MCDM). We prove that for the states with zero-discord and maximally mixed marginals, the MCDM is the very optimal measurement. Furthermore, we give an upper bound of quantum discord based on the MCDM, and investigate its performance for approximating the quantum discord.Comment: 8 pages, 3 figures, version accepted by Phys. Rev.

Using a Cray Y-MP as an array processor for a RISC Workstation

As microprocessors increase in power, the economics of centralized computing has changed dramatically. At the beginning of the 1980's, mainframes and super computers were often considered to be cost-effective machines for scalar computing. Today, microprocessor-based RISC (reduced-instruction-set computer) systems have displaced many uses of mainframes and supercomputers. Supercomputers are still cost competitive when processing jobs that require both large memory size and high memory bandwidth. One such application is array processing. Certain numerical operations are appropriate to use in a Remote Procedure Call (RPC)-based environment. Matrix multiplication is an example of an operation that can have a sufficient number of arithmetic operations to amortize the cost of an RPC call. An experiment which demonstrates that matrix multiplication can be executed remotely on a large system to speed the execution over that experienced on a workstation is described

Centralized vs. decentralized computing : organizational considerations and management options

The long-standing debate over whether to centralize or decentralize computing is examined in terms of the fundamental organizational and economic factors at stake. The traditional debate is examined and found to focus predominantly on issues of efficiency vs. effectiveness, with solutions based on a rationalistic strategy of optimizing in this tradeoff. A more behavioralistic assessment suggests that the driving issues in the debate are the politics of organization and resources, centering on the issue of control. The economics of computing deployment decisions is presented as an important issue, but one that often serves as a field of argument that is based on more political concerns. The current situation facing managers of computing, given the advent of small and comparatively inexpensive computers, is examined in detail, and a set of management options for dealing with this persistent issue is presented

Data Structures for Task-based Priority Scheduling

Many task-parallel applications can benefit from attempting to execute tasks in a specific order, as for instance indicated by priorities associated with the tasks. We present three lock-free data structures for priority scheduling with different trade-offs on scalability and ordering guarantees. First we propose a basic extension to work-stealing that provides good scalability, but cannot provide any guarantees for task-ordering in-between threads. Next, we present a centralized priority data structure based on $k$-fifo queues, which provides strong (but still relaxed with regard to a sequential specification) guarantees. The parameter $k$ allows to dynamically configure the trade-off between scalability and the required ordering guarantee. Third, and finally, we combine both data structures into a hybrid, $k$-priority data structure, which provides scalability similar to the work-stealing based approach for larger $k$, while giving strong ordering guarantees for smaller $k$. We argue for using the hybrid data structure as the best compromise for generic, priority-based task-scheduling. We analyze the behavior and trade-offs of our data structures in the context of a simple parallelization of Dijkstra's single-source shortest path algorithm. Our theoretical analysis and simulations show that both the centralized and the hybrid $k$-priority based data structures can give strong guarantees on the useful work performed by the parallel Dijkstra algorithm. We support our results with experimental evidence on an 80-core Intel Xeon system

Regional Data Archiving and Management for Northeast Illinois

This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the regional transportation agencies, from both technical and business perspectives, about building such a comprehensive transportation information system. Several implementation alternatives are identified and analyzed. This research is carried out in three phases. In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect information on all data elements that they store, including the format, system, and granularity. Their perception of a data archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the hardware, software, labor, and resource requirements. We also identify possible revenue opportunities. A few implementation options for the archive system are summarized in this report; namely: 1. System hosted by a partnering agency 2. System contracted to a university 3. System contracted to a national laboratory 4. System outsourced to a service provider The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe