Timely Data Delivery in a Realistic Bus Network

Abstract—WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, minimizing the number of hops a packet can travel, and a recently-proposed heuristic based on bus frequencies. Our optimal algorithm outperforms all of them, but most of the times it essentially reduces to minimizing the expected traversal time. For values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to reach almost the performance of the costly flooding approach. I

The Effect of Various Sparsity Structures on Parallelism and Algorithms to Reveal Those Structures

Structured sparse matrices can greatly benefit parallel numerical methods in terms of parallel performance and convergence. In this chapter, we present combinatorial models for obtaining several different sparse matrix forms. There are four basic forms we focus on: singly-bordered block-diagonal form, doubly-bordered block-diagonal form, nonempty off-diagonal block minimization, and block diagonal with overlap form. For each of these forms, we first present the form in detail and describe what goals are sought within the form, and then examine the combinatorial models that attain the respective form while targeting the sought goals, and finally explain in which aspects the forms benefit certain parallel numerical methods and their relationship with the models. Our work focuses especially on graph and hypergraph partitioning models in obtaining the mentioned forms. Despite their relatively high preprocessing overhead compared to other heuristics, they have proven to model the given problem more accurately and this overhead can be often amortized due the fact that matrix structure does not change much during a typical numerical simulation. This chapter presents a number of models and their relationship with parallel numerical methods

Comparison of point counting and planimetry methods for the assessment of cerebellar volume in human using magnetic resonance imaging: a stereological study

The cerebellum is involved in motor learning and cognitive function in human. Many studies have been conducted to assess the cerebellar volume. To the best of our knowledge, there is no cerebellar volume study evaluating the efficiency and the accuracy of point-counting and planimetry methods of the Cavalieri principle in the literature. In this study, the volume of cerebellum was estimated in 53 Turkish young volunteers (26 males and 27 females), aged between 20 and 25 who are free of any neurological symptoms and signs, using serial magnetic resonance (MR) images. The cerebellar volumes of subjects were determined on MR images using the point-counting and planimetry methods. The mean results of planimetry method were 116.69 +/- 10.1 and 114.41 +/- 9.3 cm(3) males and females, respectively. The mean results of point-counting method were 116.34 +/- 10.6 and 113.48 +/- 8.8 cm(3) in males and females, respectively. Our results revealed that female subjects had less cerebellar volumes compared with males, although there was no statistical significant difference between genders (P > 0.05). Total cerebellar volumes obtained by two different methods were not statistically different (P = 0.189) and they were correlated well to each other (r = 0.935). We found that the point-counting method takes less time than the planimetric method (mean 8 +/- 3.6 vs. 15 +/- 5.5 min). Thus, while planimetric and stereological approaches yield very similar results, the stereological method has the advantage of greater speed and, therefore, efficiency.The cerebellum is involved in motor learning and cognitive function in human. Many studies have been conducted to assess the cerebellar volume. To the best of our knowledge, there is no cerebellar volume study evaluating the efficiency and the accuracy of point-counting and planimetry methods of the Cavalieri principle in the literature. In this study, the volume of cerebellum was estimated in 53 Turkish young volunteers (26 males and 27 females), aged between 20 and 25 who are free of any neurological symptoms and signs, using serial magnetic resonance (MR) images. The cerebellar volumes of subjects were determined on MR images using the point-counting and planimetry methods. The mean results of planimetry method were 116.69 ± 10.1 and 114.41 ± 9.3 cm3 in males and females, respectively. The mean results of point-counting method were 116.34 ± 10.6 and 113.48 ± 8.8 cm3 in males and females, respectively. Our results revealed that female subjects had less cerebellar volumes compared with males, although there was no statistical significant difference between genders (P > 0.05). Total cerebellar volumes obtained by two different methods were not statistically different (P = 0.189) and they were correlated well to each other (r = 0.935). We found that the point-counting method takes less time than the planimetric method (mean 8 ± 3.6 vs. 15 ± 5.5 min). Thus, while planimetric and stereological approaches yield very similar results, the stereological method has the advantage of greater speed and, therefore, efficiency