Johannes Ulrich Herrmann

Using Multi-valued Decision Diagrams to Solve the Expected Hop Count Problem

The Expected Hop Count (EHC) of a computer communication network has so far been computed for network models that consider only device or link failure, but not both. We introduce an Augmented Ordered Multi-valued Decision Diagram (OMDD-A) to obtain the EHC of a network in which both devices and links may fail. The OMDD-A approach can compute the EHC of a 2´100 grid network with 299 paths, which is unsolvable using existing techniques. We show that OMDD-A generates significantly fewer nodes than the corresponding ordered binary decision diagram, leading to large reductions in processing time.

A memory efficient algorithm for network reliability

We combine the Augmented Ordered Binary Decision Diagram (OBDD-A) with the use of boundary sets to create a method for computing the exact K-terminal or all-terminal reliability of an undirected network with failed edges and perfect vertices. We present the results of implementing this algorithm and show that the execution time is comparable with the state of the art and the space requirement is greatly reduced. Indeed the space remains constant when networks increase in size but maintain their structure and maximum boundary set size; with the same amount of memory used for computing a 3×12 and a 3×1000 grid network.

Improving Reliability Calculation with Augmented Binary Decision Diagrams

The Augmented Ordered Binary Decision Diagram (OBDD-A) has been shown to be extremely efficient for reliability calculations, especially when combined with the Boundary Set method of partition representation. The existing OBDD-A follows the Boundary Set method closely, requiring the calculation of partition numbers large enough to exceed the capacity of native storage types in languages such as C++. By omitting the use of partition numbers the execution speed of the algorithm is increased, while the low memory usage of an OBDD-A is maintained. We compare the new OBDD-A to the existing version on a number of networks, showing that processing time for large networks increases significantly.

A database optimization model with quantitative benchmark

Query optimization and indexing have an immense impact on database optimization. This has been considered in many different perspectives which provide several different solutions in each case. The purpose of this paper is to primarily provide a comprehensive review and discussion of the core problems through the research on query optimization technology and indexing, based on a number of optimization techniques commonly used in the general approach of a query. A new database optimization model is designed and experiments show that this model can significantly reduce the amount of query execution time to improve the optimization efficiency. Regardless of research on the database optimization model, significant work has been done to comparatively evaluate three scenarios; non-optimized query, optimized query without following any optimization standard, and optimized query via proposed optimization model using the same experimental methodology. Further, this paper describes a benchmark that was developed specifically for the purpose of measuring the quantitative evaluations of the proposed database optimization model.

An algorithm for labeling topological maps to represent point of interest for vision impaired navigation

Navigation in indoor environments is highly challenging for both vision impaired and sighted people, particularly in unknown environments visited for the first time. Several solutions have been implemented and proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, each solution involves a significant deployment effort or describes objects in a manner that is unfamiliar or incomprehensible to an individual with severe blindness. This paper presents a model of adding informational point of interest to the typical indoor topological map; with particular attention to the semantic labels of the different type of indoor places and proposes a simple way to include the tags to build the topological map. Using this POI and the semantic information, the system determines the users path, locates possible obstacles on that route, and offers navigation information to assist vision impaired navigation.

Digital Channel Capacity Calculation Using Augmented Ordered Binary Decision Diagrams

Digital channel capacity of a network is an important factor in network design. Recent solutions use the Markov chain to model and compute the capacity of only a specific wireless network with multiple relays and multiple hops (MR-MH), and thus cannot be used for networks in general. Further, the solutions assume that all communication link failure probabilities are equal and that state transitional probabilities are known. This paper proposes a general solution for computing the capacity. Our solution first converts the problem of computing the channel capacity of such networks into a network reliability problem. Then, it applies the Augmented Ordered Binary Decision Diagram (OBDD-A) method to compute the reliability, and hence the channel capacity. The OBDD-A does not require the aforementioned assumptions, and can be applied to a wide range of networks. Since the OBDD-A has been shown to have linear time complexity and constant space complexity for families of networks with constant inter-connectivity (such as MR-MH) the proposed solution is extremely efficient. The application of our method is verified by simulations.

A looking-out portal (LOP) approach to enhance qualitative aspects of bandwidth utilisation in academic networks

Campuses of educational institutions periodically need to increase network bandwidth to keep up with increased demand and this decision is based on the quantitative aspects of the network bandwidth utilisation. The qualitative utilisation of the bandwidth is seldom looked into. Improving the qualitative utilisation of the bandwidth may not even necessitate a network upgrade. Although blacklist-based access control techniques help to a certain degree, the findings of this research indicate otherwise. A multi-tier, whitelist-based, looking-out portal (LOP) approach is presented that promises to improve the qualitative utilisation of the network while positively impacting pertinent resource identification and location of sources on the internet. The authors draw on their years of experience serving as students and staff in various campuses of universities and colleges in various countries while making recommendations.