6012483
Paging Multiple Users in Cellular Network: Yellow Page and Conference Call Problems
Mobile users are roaming in a zone of cells in a cellular network system. The probabilities of each user residing in each cell are known, and all probabilities are independent. The task is to find any one, or all, of the users, by paging the cells in a predetermined number of rounds. In each round, any subset of the cells can be paged. When a cell is paged, the list of users in it is returned. The paging process terminates when the required user(s) are found. The objective is to minimize the expected number of paged cells. Finding any one user is known as the yellow page problem, and finding all users is known as the conference call problem. The conference call problem has been proved NP-hard, and a polynomial time approximation scheme exists. We study both problems in a unified framework. We introduce three methods for computing the paging cost. We give a hierarchical classification of users. For certain classes of users, we either provide polynomial time optimal solutions, or provide relatively efficient exponential time solutions. We design a family of twelve fast greedy heuristics that generate competitive paging strategies. We implement optimal algorithms and non-optimal heuristics. We test the performance of our greedy heuristics on many patterns of input data with different parameters. We select the best heuristics for both problems based on our simulation. We evaluate their performances on randomly generated Zipf and uniform data and on real user data.
15303871
When to Reap and When to Sow - Lowering Peak Usage with Realistic Batteries
In some energy markets, large clients are charged for both total energy usage and peak energy usage, which is based on the maximum single energy request over the billing period. The problem of minimizing peak charges was recently introduced as an online problem in [4], which gave optimally competitive algorithms. In this problem, a battery (previously assumed to be perfectly efficient) is used to store energy for later use. In this paper, we extend the problem to the more realistic setting of lossy batteries, which lose to conversion inefficiency a constant fraction of any amount charged (e.g. 33%). For this setting, we provide efficient and optimal offline algorithms as well as possibly competitive online algorithms. Second, we give factor-revealing LPs, which provide some quasi-empirical evidence for competitiveness. Finally, we evaluate these and other, heuristic algorithms on real and synthetic data.
9775694
Paging Mobile Users Efficiently and Optimally
A mobile user is roaming in a zone composed of N cells in a cellular network system. When a call to the mobile user arrives, the system pages the mobile user in these cells since it never reports its location unless it leaves the zone. The N cells are associated with a probability vector (p1, ...,pN) where pi is the probability that the mobile user resides in the ith cell and all the probabilities are independent. A delay constraint paging strategy must find the mobile user within D (1 les D les N) paging rounds; in each round a subset of the N cells is paged. The goal is to minimize the expected number of paged cells until the mobile user is found. Solutions based on dynamic programming that yield optimal strategies are known. The running time of the known implementations is Theta(N2D). Our first contribution is to improve the running time to Theta(ND) by proving that the dynamic programming recursive formulation satisfies the Monge property, permitting us to use various dynamic programming speedup techniques. A Theta(N) heuristic solution is also known. Our second contribution is a heuristic whose running time is Theta(N log D). Our heuristic outperforms the known heuristic while running faster for D << N. We compare the non-optimal heuristics with the optimal solution demonstrating the tradeoff between optimality and running time efficiency of various solutions.
12104063
Heterogeneous Multi-Robot Localization in Unknown 3D Space
This paper presents a self-localization strategy for a team of heterogeneous mobile robots including ground mobile robots of various sizes and wall-climbing robots. These robots are equipped with various visual sensors, such as miniature webcams, omnidirectional cameras, and PTZ cameras. As the core of this work, a formation of four-robot team is constructed to operate in a 3D space, e.g., moving on ground, climbing on walls and clinging to ceilings. The four robots could dynamically localize themselves asynchronously by employing cooperative vision techniques. Three of them on the ground mutually view each other and determine their relative poses with 6 degrees of freedom (DOFs). A wall-climbing robot, which significantly extends the work space of the robot team to 3D, is at a vantage point (e.g., on the ceiling) such that it can see all the three teammates, thus determining its own location and orientation. The four-robot formation theory and algorithms are presented, and experimental results with both simulated and real image data are provided to demonstrate the feasibility of this formation. Two 3D localization and control strategies are designed for applications such as search and rescue and surveillance in 3D urban environments where robots must be deployed in a full 3D space
5393253
Self-localization of a heterogeneous multi-robot team in constrained 3D space
This paper presents a new approach to the intra- localization among a team of robots working in constrained 3D space of urban environments. As the base formation, a team of three ground robots and one wall-climbing robot are deployed on ground and on a wall or ceiling, respectively. The three ground robots localize themselves using an existing panoramic vision-based method. However, no existing method can uniquely determine the pose of the climbing robot based on the positions of three ground robots in its image and in the world coordinate systems; up to four valid solutions could exist using known algorithms, although only one is genuine. By carefully examining these methods, two new algorithms for uniquely locating the climbing robot are proposed. The first algorithm makes use of the straight line constraint of robot motion and can uniquely determine the pose of climbing robot by moving the climbing robot straightly for two small steps. The second algorithm is based on the principle of Bayesian filter and take advantage of the motion sensor readings to loose the straight line constraint. The algorithm could continuously determine the climbing robot's pose after the initial pose is obtained. Extensive simulations are conducted to validate the soundness and robustness of our algorithms. Preliminary experiments are also carried out to examine the feasibility in applying these algorithms in real robot applications.
16637089
Finding mobile data under delay constraints with searching costs
A token is hidden in one of several boxes and then the boxes are locked. The probability of placing the token in each of the boxes is known. A searcher is looking for the token by unlocking boxes where each box is associated with an unlocking cost. The searcher conducts its search in rounds and must find the token in a predetermined number of rounds. In each round, the searcher may unlock any set of locked boxes concurrently. The optimization goal is to minimize the expected cost of unlocking boxes until the token is found. The motivation and main application of this game is the task of paging a mobile user (token) who is roaming in a zone of cells (boxes) in a cellular network system. Here, the unlocking costs reflect cell congestions and the placing probabilities represent the likelihood of the user residing in particular cells. Another application is the task of finding some data (token) that may be known to one of the sensors (boxes) of a sensor network. Here, the unlocking costs reflect the energy consumption of querying sensors and the placing probabilities represent the likelihood of the data being found in particular sensors. In general, we call mobile data any entity that has to be searched for.
 The special case, in which all the boxes have equal unlocking costs has been well studied in recent years and several optimal polynomial time solutions exist. To the best of our knowledge, this paper is the first to study the general problem in which each box may be associated with a different unlocking cost. We first present three special interesting and important cases for which optimal polynomial time algorithms exist: (i) There is no a priori knowledge about the location of the token and therefore all the placing probabilities are the same. (ii) There are no delay constraints so in each round only one box is unlocked. (iii) The token is atypical in the sense that it is more likely to be placed in boxes whose unlocking cost is low. Next, we consider the case of a typical token for which the unlocking cost of any box is proportional to the probability of placing the token in this box. We show that computing the optimal strategy is strongly NP-Hard for any number of unlocking rounds, we provide a PTAS algorithm, and analyze a greedy solution. We propose a natural dynamic programming heuristic that unlocks the boxes in a non-increasing order of the ratio probability over cost. For two rounds, we prove that this strategy is a 1.143-approximation solution for an arbitrary token and a 1.108-approximation for a typical token and that both bounds are tight. For an arbitrary token, we provide a more complicated PTAS
14333699
Clock Domain Crossing Fault Model and Coverage Metric for Validation of SoC Design
Multiple asynchronous clock domains have been increasingly employed in System-on-Chip (SoC) designs for different I/O interfaces. Functional validation is one of the most expensive tasks in the SoC design process. Simulation on register transfer level (RTL) is still the most widely used method. It is important to quantitatively measure the validation confidence and progress for clock domain crossing (CDC) designs. In this paper, we propose an efficient method for definition of CDC coverage, which can be used in RTL simulation for a multi-clock domain SoC design. First, we develop a CDC fault model to present the actual effect of metastability. Second, we use a temporal data flow graph (TDFG) to propagate the CDC faults to observable variables. Finally, CDC coverage is defined based on the CDC faults and their observability. Our experiments on a commercial IP demonstrate that this method is useful to find CDC errors early in the design cycles.