Automated Design of Optimal Medium Access Control Protocols for Wireless Networking

We present a framework for the automated design of optimal Medium Access Control (MAC) protocols for wireless networks.First, we describe a methodology that incorporates the impact of control information transfer into MAC protocol optimization. We apply this methodology to the problem of a synchronous broadcast MAC channel in order to generate the optimal protocol when the objective function is the average network throughput per time slot. We describe a recursive procedure for the symbolic generation of the optimization program for any choice of the objective function. We demonstrate that this methodology subsumes two structurally different types of protocols, namely, pure random access protocols and protocols with data advertisements, as special cases of the regimes where they are optimal. We examine the scaling of the optimal throughput and the computational complexity as a function of the number of nodes and the control lifetime.Second, we generate optimal MAC protocols based on a more general MAC model that incorporates multiple MAC neighborhoods as well as acknowledgments. In this model, both the advertisement and acknowledgment frames are automatically generated by an optimization program that is built based on symbolic Monte Carlo simulation. The design flow chain produces an optimal MAC protocol with respect to the desired objective function.Third, we formulate the automated optimal MAC protocol generation problem for dynamic topologies, as encountered in wireless ad hoc networks, under multiple neighborhoods and in the presence of acknowledgments. The probability distribution over the set of local topologies encountered in the global network serves as a model for which an optimization program may be formulated that takes the per-node average throughput as its objective function. Symbolic Monte Carlo simulation is used to generate the optimization program, which is subsequently solved via state-of-the-art nonlinear solvers. A quantitative comparison with the standard RTS/CTS protocol provides information on the value of side information on the probability distribution of local topologies, which RTS/CTS does not presume. Our investigations of computational complexity show that the time to generate the program dominates over the time to solve the resulting non-linear program, and that the complete program can be solved within a reasonable computational time.Fourth, we formulate the automated optimal MAC protocol generation problem under dynamic traffic conditions for multiple neighborhoods and in the presence of acknowledgments. We show that the problem can be formulated as a functional optimization program in which each design (a.k.a. decision) function of the program is the probability that a node takes an action given its knowledge state, as a function of the effective traffic demand at the current time at that node. In order to achieve a viable computational complexity for the functional optimization program, we discretize the effective traffic demands by virtue of which a look-up table is produced for each design function. Structurally different MAC protocols can be represented in this framework, and are generated automatically with respect to traffic demand. The symbolic Monte Carlo method is used to generate an approximate expression for the objective function as well as for the non-linear constraints, in a manner that trades off accuracy versus computational complexity. Symbolic simulation results are presented for a fixed network topology under the assumption of Poisson traffic. The objective is to minimize the average power consumption of a node subject to a minimum average throughput constraint that incorporates soft delay guarantees. Our research demonstrates that a MAC protocol that incorporates acknowledgments in a multi-hop setting under dynamic traffic can be generated automatically.This thesis opens the way for the design of an automated design flow chain for network protocols that are based only on local information, of which MAC protocols constitute an example. In the future, our framework can be integrated as a ``back end'' to Software Defined Networks (SDN's) which are envisioned to run on optimizable protocols as the ones described in this thesis

Energieeffiziente und rechtzeitige Ereignismeldung mittels drahtloser Sensornetze

This thesis investigates the suitability of state-of-the-art protocols for large-scale and long-term environmental event monitoring using wireless sensor networks based on the application scenario of early forest fire detection. By suitable combination of energy-efficient protocol mechanisms a novel communication protocol, referred to as cross-layer message-merging protocol (XLMMP), is developed. Qualitative and quantitative protocol analyses are carried out to confirm that XLMMP is particularly suitable for this application area. The quantitative analysis is mainly based on finite-source retrial queues with multiple unreliable servers. While this queueing model is widely applicable in various research areas even beyond communication networks, this thesis is the first to determine the distribution of the response time in this model. The model evaluation is mainly carried out using Markovian analysis and the method of phases. The obtained quantitative results show that XLMMP is a feasible basis to design scalable wireless sensor networks that (1) may comprise hundreds of thousands of tiny sensor nodes with reduced node complexity, (2) are suitable to monitor an area of tens of square kilometers, (3) achieve a lifetime of several years. The deduced quantifiable relationships between key network parameters — e.g., node size, node density, size of the monitored area, aspired lifetime, and the maximum end-to-end communication delay — enable application-specific optimization of the protocol

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications