A Socio-inspired CALM Approach to Channel Assignment Performance Prediction and WMN Capacity Estimation

A significant amount of research literature is dedicated to interference mitigation in Wireless Mesh Networks (WMNs), with a special emphasis on designing channel allocation (CA) schemes which alleviate the impact of interference on WMN performance. But having countless CA schemes at one's disposal makes the task of choosing a suitable CA for a given WMN extremely tedious and time consuming. In this work, we propose a new interference estimation and CA performance prediction algorithm called CALM, which is inspired by social theory. We borrow the sociological idea of a "sui generis" social reality, and apply it to WMNs with significant success. To achieve this, we devise a novel Sociological Idea Borrowing Mechanism that facilitates easy operationalization of sociological concepts in other domains. Further, we formulate a heuristic Mixed Integer Programming (MIP) model called NETCAP which makes use of link quality estimates generated by CALM to offer a reliable framework for network capacity prediction. We demonstrate the efficacy of CALM by evaluating its theoretical estimates against experimental data obtained through exhaustive simulations on ns-3 802.11g environment, for a comprehensive CA test-set of forty CA schemes. We compare CALM with three existing interference estimation metrics, and demonstrate that it is consistently more reliable. CALM boasts of accuracy of over 90% in performance testing, and in stress testing too it achieves an accuracy of 88%, while the accuracy of other metrics drops to under 75%. It reduces errors in CA performance prediction by as much as 75% when compared to other metrics. Finally, we validate the expected network capacity estimates generated by NETCAP, and show that they are quite accurate, deviating by as low as 6.4% on an average when compared to experimentally recorded results in performance testing

Mechanism Design Theory in Control Engineering: A Tutorial and Overview of Applications in Communication, Power Grid, Transportation, and Security Systems

This article provides an introduction to the theory of mechanism design and its application to engineering problems. Our aim is to provide the fundamental principles of the theory of mechanism design for control engineers and theorists along with the state-of-the-art methods in engineering applications. We start our exposition with a brief overview of game theory highlighting the key notions that are necessary to introduce mechanism design, and then we offer a comprehensive discussion of the principles in mechanism design. Finally, we explore four key applications of mechanism design in engineering, i.e., communication networks, power grids, transportation, and security systems

CompuP2P: a light-weight architecture for Internet computing

Internet computing is emerging as an important new paradigm in which resource intensive computing is integrated over Internet-scale networks. Over these large networks, different users and organizations have potential to share their computing resources, and computations can take place in a distributed fashion. In such an environment, a framework is needed in which the resource providers are given incentives to share their resources. In this research we propose CompuP2P, which is a light-weight architecture for enabling Internet computing. It uses peer-to-peer networks for sharing of computing resources. CompuP2P creates dynamic markets of network accessible computing resources, such as processing power, memory storage, disk space, etc., in a completely distributed, scalable, and fault-tolerant manner. We discuss the system architecture, functionality, and applications of the proposed CompuP2P architecture. We have implemented a Java based prototype of CompuP2P. We ran several algorithms with coarse grained parallelism on CompuP2P. Our results show that the system is light-weight and can provide almost a perfect speedup for applications that contain several independent compute-intensive tasks

Application centric load balancing for distributed systems using genetic algorithm scheduling

This thesis proposes a GA based scheduling algorithm for a heterogeneous distributed computing environment. It uses the application centric load balancing system. The proposed system removes all those network delay assumptions and considers the allocation problem for both computing resources and network resources. It addresses the generalized workload i.e. direct acyclic graph (DAG) kind of workload that is composed of sub jobs with internal dependencies. Rather than allocate applications simply according to their arrival time, we introduce GA scheduling strategy into our load balancing system to find the proper applications allocating schedule, which uses the available resources more efficiently. With introduction of GA scheduling into both application level and process level, certain improvements on the practicability, accuracy and performance are expected. Instead of using constant GA parameters, our proposed algorithm dynamically adjusts the key parameters, such as crossover rate and mutation rate, adapting them to the quality of generations. Later, we will implement more new ideas, such as gender assignment, fertility rate and aging into our GA algorithm to achieve better performance. \u27Keywords.\u27 Load balancing, network delay, workload simulator, Adaptive Genetic Algorithm scheduling etc

Evaluation and metrics framework

In this paper a metrics framework for evaluating different scenarios in the CATNETS project is defined. The aim is to use this framework to compare the catallactic scenario against the central auctioneer. --Grid Computing

A model for travel mode switching

Transportation policy research assesses the effect of policy changes such as the imposition of a parking charge or the augmentation of passenger rail service, on individual travel behavior. Over the last few decades, Conditional Lo it Model has been strongly advocated among discrete choice models for transportation policy study due to its ease of estimation and realistic outcomes. This dissertation analyzes the necessity of the entry of constraints in the indirect utility function. These functions are used in discrete choice models and form the basis for travel demand modeling. This dissertation proposes a hypothesis that the explicit entry of constraints in the systematic utility term will improve the specification of logit model because the constraints have significant effect on individual mode switching. A new model for incorporating constraints is developed based upon the hypothesis. Simulation and empirical study are combined to analyze the validity of this model\u27s structure. The empirical evidence shows that explicit entry of constraints can effectively correct the errors caused by missing or ignoring of constraints in the indirect utility term