Hierarchical Routing over Dynamic Wireless Networks

Wireless network topologies change over time and maintaining routes requires frequent updates. Updates are costly in terms of consuming throughput available for data transmission, which is precious in wireless networks. In this paper, we ask whether there exist low-overhead schemes that produce low-stretch routes. This is studied by using the underlying geometric properties of the connectivity graph in wireless networks.Comment: 29 pages, 19 figures, a shorter version was published in the proceedings of the 2008 ACM Sigmetrics conferenc

Optimal quantization for compressive sensing under message passing reconstruction

Abstract—We consider the optimal quantization of compressive sensing measurements along with estimation from quantized samples using generalized approximate message passing (GAMP). GAMP is an iterative reconstruction scheme inspired by the belief propagation algorithm on bipartite graphs which generalizes approximate message passing (AMP) for arbitrary measurement channels. Its asymptotic error performance can be accurately predicted and tracked through the state evolution formalism. We utilize these results to design mean-square optimal scalar quantizers for GAMP signal reconstruction and empirically demonstrate the superior error performance of the resulting quantizers. I

Hitting probabilities for non-linear systems of stochastic waves

We consider a $d$-dimensional random field $u = \{u(t,x)\}$ that solves a non-linear system of stochastic wave equations in spatial dimensions $k \in \{1,2,3\}$, driven by a spatially homogeneous Gaussian noise that is white in time. We mainly consider the case where the spatial covariance is given by a Riesz kernel with exponent $\beta$. Using Malliavin calculus, we establish upper and lower bounds on the probabilities that the random field visits a deterministic subset of \IR^d, in terms, respectively, of Hausdorff measure and Newtonian capacity of this set. The dimension that appears in the Hausdorff measure is close to optimal, and shows that when $d(2-\beta) > 2(k+1)$, points are polar for $u$. Conversely, in low dimensions $d$, points are not polar. There is however an interval in which the question of polarity of points remains open.Comment: 85 page

Network correlated data gathering with explicit communication: NP-completeness and algorithms

We consider the problem of correlated data gathering by a network with a sink node and a tree-based communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. For source coding of correlated data, we consider a joint entropy-based coding model with explicit communication where coding is simple and the transmission structure optimization is difficult. We first formulate the optimization problem definition in the general case and then we study further a network setting where the entropy conditioning at nodes does not depend on the amount of side information, but only on its availability. We prove that even in this simple case, the optimization problem is NP-hard. We propose some efficient, scalable, and distributed heuristic approximation algorithms for solving this problem and show by numerical simulations that the total transmission cost can be significantly improved over direct transmission or the shortest path tree. We also present an approximation algorithm that provides a tree transmission structure with total cost within a constant factor from the optimal

The Question of Ownership in a Sharing Economy

Abstrac

modelling fluid-poroelastic media interaction

The interaction between a fluid and a poroelastic structure is a complex problem that couples the Navier-Stokes equations with the Biot system. The finite element approximation of this problem is involved due to the fact that both subproblems are indefinite. In this work, we first design residual-based stabilization techniques for the Biot system, motivated by the variational multiscale approach. Then, we state the monolithic Navier-Stokes/Biot system with the appropriate transmission conditions at the interface. For the solution of the coupled system, we adopt both monolithic solvers and heterogeneous domain decomposition strategies. Different domain decomposition methods are considered and their convergence 1 is analyzed for a simplified problem. We compare the efficiency of all the methods on a test problem that exhibits a large added-mass effect, as it happens in hemodynamics applications.

The Case For Heterogeneous HTAP

ABSTRACT Modern database engines balance the demanding requirements of mixed, hybrid transactional and analytical processing (HTAP) workloads by relying on i) global shared memory, ii) system-wide cache coherence, and iii) massive parallelism. Thus, database engines are typically deployed on multi-socket multi-cores, which have been the only platform to support all three aspects. Two recent trends, however, indicate that these hardware assumptions will be invalidated in the near future. First, hardware vendors have started exploring alternate non-cache-coherent shared-memory multi-core designs due to escalating complexity in maintaining coherence across hundreds of cores. Second, as GPGPUs overcome programmability, performance, and interfacing limitations, they are being increasingly adopted by emerging servers to expose heterogeneous parallelism. It is thus necessary to revisit database engine design because current engines can neither deal with the lack of cache coherence nor exploit heterogeneous parallelism. In this paper, we make the case for Heterogeneous-HTAP (H 2 TAP), a new architecture explicitly targeted at emerging hardware. H 2 TAP engines store data in shared memory to maximize data freshness, pair workloads with ideal processor types to exploit heterogeneity, and use message passing with explicit processor cache management to circumvent the lack of cache coherence. Using Caldera, a prototype H 2 TAP engine, we show that the H 2 TAP architecture can be realized in practice and can offer performance competitive with specialized OLTP and OLAP engines