14224064
PeterNet: an emergent technology based radio access network architecture for next generation cellular wireless systems
For next generation wireless cellular networks, the radio access network (RAN) component is destined to evolve into a high-capacity, flexible and reconfigurable network architecture supporting smaller cell sites and newer technologies. Based on the well-known Petersen graph, in this paper we propose a RAN architecture, named PeterNet, that interconnects the network elements in a mesh topology. Focusing on optical wireless as the underlying transmission technology, we analyze our architecture on two key indices - carrier-class network reliability (99.999%) and infrastructure cost - providing comparative performance analysis with existing tree/star and regular grid networks. Furthermore, we generalize our architecture to what we call, the GPeterNet, which allows dynamic reconfiguration and redesign of the access network while leveraging the underlying salient features.
14429447
iSimBioSys: a discrete event simulation platform for 'in silico' study of biological systems
With the availability of huge databases cataloguing the various molecular "parts" of complex biological systems, researchers from multiple disciplines have focused on developing modeling and simulation tools for studying the variability of cellular behavior at a system level - encompassing the dynamics arising from many species of interacting molecules. In this work, we present a system engineering approach to model biological processes. In this approach, a biological process is modeled as a collection of interacting functions driven in time by a set of discrete events. We focus on the discrete event simulation platform, called "iSimBioSys", which we have developed for studying the dynamics of cellular processes in silico. As a test-bed for studying our approach we model the two component PhoPQ system, responsible for the expression of several virulence genes in Salmonella Typhimurium. We analyzed the effect of extra cellular magnesium on the behavioral dynamics of this pathway using our framework and compared the results with an experimental system. We also analyze the performance of iSimBioSys, based on the model biological system, in terms of system usage and response.
1283500
GaMa: an evolutionary algorithmic approach for the design of mesh-based radio access networks
Wireless mesh based access networks are destined to play a pivotal role in next generation broadband systems. With the proliferation of mesh networks, a key issue for network designers is the design of an optimal mesh topology which minimizes cost while maintaining carrier-class features. In this paper, we formulate the design of an optimal mesh, taking network deployment cost, topological properties and carrier-grade reliability into account. Next, we present a genetic algorithm based algorithm (GaMa) for mesh topology design. We show that GaMa is capable of determining a generic mesh topology with carrier-class network features. The performance of the algorithm is compared with existing mesh topologies and gives improved results without the constraints of maintaining a regular topology
972043
Stochastic Modeling of Cytoplasmic Reactions in Complex Biological Systems
The use of “in silico” stochastic event based modeling can identify the dynamic interactions of different processes in a complex biological system. This requires the computation of the time taken by different events in the system based on their biological functions. One such important event is the reactions between the molecules inside the cytoplasm of a cell. We present a mathematical formulation for the estimation of the reaction time between two molecules within a cell based on the system state. We derive expressions for the average and second moment of the time for reaction to be used by our stochastic event-based simulation. Unlike rate equations, the proposed model does not require the assumption of concentration stability for multiple molecule reactions.
9120365
A self-stabilizing algorithm for the maximum flow problem
Summary. The maximum flow problem is a fundamental problem in graph theory and combinatorial optimization with a variety of important applications. Known distributed algorithms for this problem do not tolerate faults or adjust to dynamic changes in network topology. This paper presents a distributed self-stabilizing algorithm for the maximum flow problem. Starting from an arbitrary state, the algorithm computes the maximum flow in an acyclic network in finitely many steps. Since the algorithm is self-stabilizing, it is inherently tolerant to transient faults. It can automatically adjust to topology changes and to changes in other parameters of the problem. The paper presents results obtained by extensively experimenting with the algorithm. Two main observations based on these results are (1) the algorithm requires fewer than n2 moves for almost all test cases and (2) the algorithm consistently performs at least as well as a distributed implementation of the well-known Goldberg-Tarjan algorithm for almost all test cases. The paper ends with the conjecture that the algorithm correctly computes a maximum flow even in networks that contain cycles.
46734639
A Framework of Safe Stabilization
Classical stabilizing systems do not take into consideration safety issues. This paper examines two different safety models for stabilizing distributed systems, and studies the cost of enforcing safety requirements in the context of various kinds of failures.
6555367
Selecting Error Correcting Codes to Minimize Power in Memory Checker Circuits
The approach proposed in this paper reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory ECC. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting code. The non-linear power optimization problem is solved using two methods, genetic algorithms and simulated annealing. Both the methods are applied to two SEC-DED codes: standard Hamming codes and odd-column-weight Hsiao codes. Experiments on actual memory traces of Spec and MediaBench benchmarks indicate that considering power along with area and delay when selecting the parity check matrix can result in power reductions of up to 27% for Hsiao codes and up to 41% for Hamming codes. Experiments are also performed to motivate the choice of parameters of the non-linear optimization algorithms, using sensitivity analysis of the low-power solutions to the choice of the different parameters of each algorithm.
5608135
Low-power weighted pseudo-random BIST using special scan cells
In this paper, a technique for weighted pseudo-random built-in self-test (BIST) of VLSI circuits is proposed, which uses special scan cells and a new weight selection algorithm to achieve low power dissipation. It is based on weighted pseudo-random scan testing in which only 3 weight values are used - 2 fixed values (0 or 1) and 1 random value (0.5). A new weight selection algorithm is used to select a set of weights that achieves high fault coverage while reducing power. The idea is to minimize power by careful selection of the set of scan cells having fixed values (0 or 1) in order to reduce switching activity. To implement this in hardware, a new scan cell design is proposed that can do scan and capture in the normal mode as well as fixed-bit mode. The new scan cell hardware increases the area of a typical circuit by less than 4%, but reduces power by as much as 96%, as indicated in experiments performed on benchmark circuits.
25755124
An Algorithm for Computing a Convex and Simple Path of Bounded Curvature in a Simple Polygon

AbstractAbstract. In this paper we study the collision-free path planning problem for a point robot, whose path is of bounded curvature(i.e., constrained to have curvature at most 1), moving in the plane inside an n -sided simple polygon P . Given two points sand tinside Pand two directions of travel, one at sand one at t , the problem is to compute a convex and simple path of bounded curvature inside Pfrom sto tconsisting of straight-line segments and circular arcs such that (i) the radius of each circular arc is at least 1, (ii) each segment on the path is the tangent between the two consecutive circular arcs on the path, (iii) the given initial direction at sis tangent to the path at sand (iv) the given final direction at tis tangent to the path at t . We propose an O(n4)time algorithm for this problem. Using the notion of complete visibility, Pis pruned to another polygon P'such that any convex and simple path from sto tinside Palso remains inside P' . Then our algorithm constructs the locus of center of a circle of unit radius translating along the boundary of P'and, using this locus, the algorithm constructs a convex and simple path of bounded curvature. Our algorithm is based on the relationship between the Euclidean shortest path, link paths and paths of bounded curvature, and uses several properties derived here on convex and simple paths of bounded curvature. We also show that the path computed by our algorithm can be transformed in O(n)time to a minimalconvex and simple path of bounded curvature. Using this transformation and two necessary conditions proposed here for the shortest convex and simple path of bounded curvature, a minimalbounded curvature path is located in O(n4)time whose length, except in special situations involving arcs of length greater than π , is at most twice the length of a shortest convex and simple path of bounded curvature.
