A Threshold Based Dynamic Routing for Jobs with QoS Ranking

Abstract: We consider a set of n heterogeneous servers which differ in processing time and Quality of Service (QoS). Jobs are divided into m levels with regard to their service ranks. We present a Threshold Policy (TP) depending on number of different jobs in the queues as a practical and flexible dynamic routing policy to control the QoS. Two performance measures are discussed: the QoS and the Average Waiting Time (AWT) in the queues. The TP is compared with both a static routing policy which maximizes the QoS level and the Minimum Expected Delay (MED) policy which minimizes the AWT. Numerical example validate that the proposed TP is more effective when both measures are considered. The TP balances the trade-off between QoS and AWT and therefore it is superior to the MED policy and any static routing which keeps the QoS in a certain level

A Survey on Scheduling in IEEE 802.16 Mesh Mode

Cataloged from PDF version of article.IEEE 802.16 standard (also known as WiMAX) defines the wireless broadband network technology which aims to solve the so called last mile problem via providing high bandwidth Internet even to the rural areas for which the cable deployment is very costly. The standard mainly focuses on the MAC and PHY layer issues, supporting two transmission modes: PMP (Point-to-Multipoint) and mesh modes. Mesh mode is an optional mode developed as an extension to PMP mode and it has the advantage of having an improving performance as more subscribers are added to the system using multi-hop routes. In 802.16 MAC protocol, mesh mode slot allocation and reservation mechanisms are left open which makes this topic a hot research area. Hence, the focus of this survey will mostly be on the mesh mode, and the proposed scheduling algorithms and performance evaluation methods

SRP-HEE: A Modified Stateless Routing Protocol based on Homomorphic Energy based Encryption for Wireless Sensor Network

Due to the wireless nature, the sensors node data are prone to location privacy of source and classification of the packet by unauthorized parties. Data encryption is one of the most effective ways to thwart unauthorized access to the data and trace information. Traditional wireless network security solutions are not viable for WSNs In this paper, a novel distributed forward aware factor based heuristics towards generating greedy routing using stateless routing is SRP-HEE for wireless sensor network. The model employs the homomorphic Energy based encryption technique. Energy based Encryption model is devoted as homomorphic mechanism due to their less computational complexity. Additionally, privacy constraint becoming a critical issue in the wireless sensor networks (WSNs) because sensor nodes are generally prone to attacks which deplete energy quickly as it is exposed to mobile sink frequently for data transmission. Through inclusion of the Forward aware factor on the Greedy routing strategies, it is possible to eliminate the attacking node which is depleting the energy of the source node. Heuristic conditions are used for optimizing the sampling rate and battery level for tackling the battery capacity constraints of the wireless sensor nodes. The Node characteristics of the propagating node have been analysed utilizing kalman filter and linear regression. The cooperative caching of the network information will enable to handle the fault condition by changing the privacy level of the network. The Simulation results demonstrate that SRP-HEE model outperforms existing technique on basis of Latency, Packet Delivery Ratio, Network Overhead, and Energy Utilization of nodes

Multi-Objective Routing Optimization for Multiple Level Priority and Preemption in Multi-Tiered Networks

This thesis explores techniques for improving the Quality of Service (QoS) driven routing of IP traffic in a Network Centric Military Communications System within an HC3 (High Capacity Communications Capability) tiered topology. In this specialized network various routing algorithms, including traditional, QoS-constrained search-based, and heuristic approaches, were evaluated. An automatic system for the probabilistic generation of appropriate networks and traffic was created for Monte Carlo simulation of the systems and testing of the various routing algorithms. A new algorithm we propose, based upon a hiercharical decomposition of routes about the minimum distance routes, is described and tested. These results provide both insight into this problem and demonstrate the possibility of highly optimized solutions without exhaustive search

Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

Machine Learning

Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience