Distributed algorithms for barrier coverage using relocatable sensors

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within \(\varTheta (n^2)\) steps with the barrier fully covered, while the constant-memory algorithm is shown to take \(\varTheta (n)\) steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires \(\varOmega (n)\) steps on some inputs, our second algorithm is asymptotically optimal.     

The next generation models for crops and agro-ecosystems

Growth in population, decrease in arable land area, and change in climate are endangering our food security. Precision agriculture has the potential to increase crop productivity thorough tailored agricultural practices for different growing areas. Many models of crops and agro-ecosystems capable of predicting interaction between plants and environments have been developed for precision agriculture. Currently, there are several representative categories of crop and agro-ecosystem models, including the de Wi...     

Path Hitting in Acyclic Graphs

An instance of the path hitting problem consists of two families of paths, and ℋ, in a common undirected graph, where each path in ℋ is associated with a non-negative cost. We refer to and ℋ as the sets of demand and hitting paths, respectively. When p∈ℋ and share at least one mutual edge, we say that p hits q. The objective is to find a minimum cost subset of ℋ whose members collectively hit those of . In this paper we provide constant factor approximation algorithms for path hitting, confined to instances in which the underlying graph is a tree, a spider, or a star. Although such restricted settings may appear to be very simple, we demonstrate that they still capture some of the most basic covering problems in graphs. Our approach combines several novel ideas: We extend the algorithm of Garg, Vazirani and Yannakakis (Algorithmica, 18:3–20, 1997) for approximate multicuts and multicommodity flows in trees to prove new integrality properties; we present a reduction that involves multiple calls to this extended algorithm; and we introduce a polynomial-time solvable variant of the edge cover problem, which may be of independent interest. An extended abstract of this paper appeared in Proceedings of the 14th Annual European Symposium on Algorithms, 2006. This work is part of D. Segev’s Ph.D. thesis prepared at Tel-Aviv University under the supervision of Prof. Refael Hassin.     

The parallel complexity of scheduling with precedence constraints

We study the problem of parallel computation of a schedule for a system of n unit-length tasks on m identical machines, when the tasks are related by a set of precedence constraints. We present NC algorithms for computing an optimal schedule in the case where m, the number of available machines, does not vary with time and the precedence constraints are represented by a collection of outtrees. The algorithms run on an exclusive read, exclusive write (EREW) PRAM. Their complexities are O(log n) and O((log n)²) parallel time using O(n²) and O(n) processors, respectively. The schedule computed by our algorithms is a height-priority schedule. As a complementary result we show that it is very unlikely that computing such a schedule is in NC when any of the above conditions is significantly relaxed. We prove that the problem is P-complete under logspace reductions when the precedence constraints are a collection of intrees and outtrees, or for a collection of outtrees when the number of available machines is allowed to increase with time. The time span of a height-priority schedule for an arbitrary precedence constraints graph is at most 2 − 1/(m − 1) times longer than the optimal (N. E Chen and C. L. Liu, Proc. 1974 Sagamore Computer Conference on Parallel Processing, T. Fend (Ed.), Springer-Verlag, Berlin, 1975, pp. 1–16). Whereas it is P-complete to produce the classical height-priority schedules even for very restricted precedence constraints graphs, we present a simple NC parallel algorithm which produces a different schedule that is only 2 − 1/m times the optimal.     

Environment as a first class abstraction in multiagent systems

The current practice in multiagent systems typically associates the environment with resources that are external to agents and their communication infrastructure. Advanced uses of the environment include infrastructures for indirect coordination, such as digital pheromones, or support for governed interaction in electronic institutions. Yet, in general, the notion of environment is not well defined. Functionalities of the environment are often dealt with implicitly or in an ad hoc manner. This is not only poor engineering practice, it also hinders engineers to exploit the full potential of the environment in multiagent systems. In this paper, we put forward the environment as an explicit part of multiagent systems.We give a definition stating that the environment in a multiagent system is a first-class abstraction with dual roles: (1) the environment provides the surrounding conditions for agents to exist, which implies that the environment is an essential part of every multiagent system, and (2) the environment provides an exploitable design abstraction for building multiagent system applications. We discuss the responsibilities of such an environment in multiagent systems and we present a reference model for the environment that can serve as a basis for environment engineering. To illustrate the power of the environment as a design abstraction, we show how the environment is successfully exploited in a real world application. Considering the environment as a first-class abstraction in multiagent systems opens up new horizons for research and development in multiagent systems.     

Hierarchical edge bundles: visualization of adjacency relations in hierarchical data

A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a B-spline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations     

Towards a re-programmable DNA computer

Microreactors lend themselves to a relatively simple implementation of DNA computing. Not only is the design of the DNA library critical for the success of the system but also the architecture of the microfluidic structure. Microreactors can be configured as Boolean operators. This paper will show that biomolecular computing can be performed with elementary building blocks, analogous to electronic logic gates. These logical operations will be performed using negative selection. Furthermore, an alternative bead barrier is introduced which can render the computer re-programmable and shows an principle architecture for selection and analysis.     

Flows in micro fluidic networks: From theory to experiment

When complex flow structures are designed, such as in DNA computing, it is essential to be able to predict the flow pattern of the solutions in the fluidic network. A model based on the resistance of the channels and flow velocities of the inlets can eliminated re-iterative design steps. We have constructed a symbolic model using Mathematica ® to determine the desired flow pattern based on the equations of Ohm and Kirchoff. The values from this simulation were used in a flow simulation program and then tested in a microflow network. Results show that the simulation and calculation match very well, while the experiments in the fluidic network show a flow pattern as predicted by the model.     

Outlier Respecting Points Approximation

In this paper, we consider a generalized problem formulation of computing a functional curve to approximate a point set in the plane with outliers. The goal is to seek a solution that not only optimizes its original objectives, but also somehow accommodates the impact of the outliers. Based on a new model of accommodating outliers, we present efficient geometric algorithms for various versions of this problem (e.g., the approximating functions are step functions or piecewise linear functions, the points are unweighted or weighted, etc). All our results are first known. Our new model and techniques for handling outliers may be useful to other applications as well.     

Maintaining Privacy on a Line

Consider a situation where people have to choose among a sequence of n linearly ordered positions to perform some task requiring a certain amount of privacy. Which position should one choose so as to maximize one’s privacy, i.e., minimize the chances that one of your neighboring positions becomes occupied by a later arrival? In this paper, we attempt to answer this question under a variety of models for the behavior of the later arrivals. Our results suggest that for the most part one should probably choose one of the extreme positions (with some interesting exceptions). We also suggest a number of variations on the problem that lead to many open problems.