This thesis proposes a new algorithm for multi-constrained Quality of Service Optimal Path Routing in the context of military applications. The objective of our routing algorithm is to manage network traffic according to quality of service requirements of connection requests using military metrics. The algorithm is mainly based on communication priority. The QoS metrics such as bandwidth, delay and packet loss ratio are considered as basic metrics on path finding. If there is no suitable path for the request, some existing connections with lower priorities may be broken to make space for a higher priority level connection request. In this case, priority and bandwidth are used as decisive metrics in cost computation

Wireless sensor networks are ad hoc networks of tiny battery powered sensor nodes that can organize themselves to form self-organized networks and collect information regarding temperature, light, and pressure in an area. Though the applications of sensor networks are very promising, sensor nodes are limited in their capability due to many factors. The main limitation of these battery powered nodes is energy. Sensor networks are expected to work for long periods of time once deployed and it becomes important to conserve the battery life of the nodes to extend network lifetime. This work examines non-uniform grid-based routing protocol as an effort to minimize energy consumption in the network and extend network lifetime. The entire test area is divided into non-uniformly shaped grids. Fixed source and sink nodes with unlimited energy are placed in the network. Sensor nodes with full battery life are deployed uniformly and randomly in the field. The source node floods the network with only the coordinator node active in each grid and the other nodes sleeping. The sink node traces the same route back to the source node through the same coordinators. This process continues till a coordinator node runs out of energy, when new coordinator nodes are elected to participate in routing. Thus the network stays alive till the link between the source and sink nodes is lost, i.e., the network is partitioned. This work explores the efficiency of the non-uniform grid-based routing protocol for different node densities and the non-uniform grid structure that best extends network lifetime.

Wireless mesh networks (WMN) is a new promising wireless technology which uses already available hardware and software components. This thesis proposes a routing algorithm for military applications. More specifically, a specialized scenario consisting of a network of flying Unmanned Aerial Vehicles (UAVs) executing reconnaissance missions is investigated. The proposed routing algorithm is hybrid in nature and uses both reactive and proactive routing characteristics to transmit information. Through simulations run on a specially built stand alone simulator, based on Java, packet overhead, delivery ratio and latency metrics were monitored with respect to varying number of nodes, node density and mobility. The results showed that the high overhead leads to high delivery ratio while latency tends to increase as the network grows larger. All the metrics revealed sensitivity in high mobility conditions.

Efficient energy use is primarily for any sensor networks to function for a longer time period. There have been many efficient schemes with various progress levels proposed by many researchers. Yet, there still more improvements are needed. This thesis is an attempt to make wireless sensor networks with further efficient on energy usage in the network with respect to rate of delivery of the messages. In sensor network architecture radio, sensing and actuators have influence over the power consumption in the entire network. While listening as well as transmitting, energy is consumed by the radio. However, if by reducing listening times or by reducing the number of messages transmitting would reduce the energy consumption. But, in real time scenario with critical information sensing network leads to information loss. To overcome this an adaptive routing technique should be considered. So, that it focuses on saving energy in a much more sophisticated way without reducing the performance of the sensing network transmitting and receiving functionalities. This thesis tackles on parts of the energy efficiency problem in a wireless sensor network and improving delivery rate of messages. To achieve this a routing technique is proposed. In this method, switching between two routing paths are considered and the switching decision taken by the server based on messages delivered comparative previous time intervals. The goal is to get maximum network life time without degrading the number of messages at the server. In this work some conventional routing methods are considered for implementing an approach. This approach is by implementing a shortest path, Gradient based energy routing algorithm and an observer component to control switching between paths. Further, controlled switching done by observer compared to normal initial switch rule. Evaluations are done in a simulation environment and results show improvement in network lifetime in a much more balanced way.

Recent advances in VLSI technology, and wireless communication have enabled the development of tiny, low-cost sensor nodes that communicate over short distances. These sensor nodes, which consist of sensing, data processing, and wireless communication capabilities, suggest the idea of sensor networks based on collaborative effort of a large number of sensor nodes. Sensor networks hold the promise for numerous applications such as intrusion detection, weather monitoring, security and tactical surveillance, distributed computing, and disaster management. Several new protocols and algorithms have been proposed in the recent past in order to realize these applications. In this thesis, we consider the problem of routing in Wireless Sensor Networks (WSNs). Routing is a challenging problem in WSNs due to the inherent characteristics which distinguish these networks from the others. Several routing algorithms have been proposed for WSNs, each considering a specific network performance objective such as long network lifetime (ChangandTassiulas,2004), end-to-end delay guarantees (T.Heetal,2003), and data fusion (RazvanCristescuetal,2005) etc. In this thesis, we utilize the Potential-based Routing Paradigm to develop routing algorithms for different performance objectives of interest in WSNs. The basic idea behind the proposed approach is to assign a scalar called the potential to every sensor node in the network. Data is then forwarded to the neighbor with highest potential. Potentials cause the data to flow along certain paths. By defining potential fields appropriately, one can cause data to flow along preferred paths, so that the given performance objective is achieved. We have demonstrated the usefulness of this approach by considering three performance objectives, and defining potentials appropriately in each case. The performance objectives that we have considered are (i) maximizing the time to network partition, (ii) maximizing the packet delivery ratio, and (iii) Data fusion. In an operational sensor network, sensor nodes’ energy levels gradually deplete, leading eventually to network partition. A natural objective is to route packets in such a way that the time to network partition is maximized. We have developed a potential function for this objective. We analyzed simple network cases and used the insight to develop a potential function applicable to any network. Simulation results showed that considerable improvements in time to network partition can be obtained compared to popular approaches such as maximum lifetime routing, and shortest hop count routing. In the next step, we designed a potential function that leads to routes with high packet delivery ratios. We proposed a “channel-state aware” potential definition for a simple 2-relay network and performed a Markov-chain based analysis to obtain the packet delivery ratio. Considerable improvement was observed compared to a channel-state-oblivious policy. This motivated us to define a channel-state-dependent potential function for a general network. Simulation results showed that for a relatively slowly changing wireless network, our approach can provide up to 20% better performance than the commonly-used shortest-hop-count routing. Finally, we considered the problem of correlated data gathering in sensor networks. The routing approach followed in literature is to construct a spanning tree rooted at the sink. Every node in the tree aggregates its data with the data from its children in order to reduce the number of transmitted bits. Due to this fact, the total energy cost of the data collection task is a function of the underlying tree structure. Noting that potential based routing schemes also result in a tree structure, we present a potential definition that results in the minimum energy cost tree under some special conditions. Specifically, we consider a scenario in which sensor nodes’ measurements are quantized to K values. The task at the sink is to construct a histogram of measurements of all sensor nodes. Sensor nodes do not directly send their measurements to sink. Instead, they construct a temporary histogram using the data from its children and forward it to its parent node in the tree. We present a potential definition that results in the minimum energy cost tree under some conditions on sensor nodes’ measurements. We include both the transmission energy cost as well as the energy cost associated with the aggregation process.

The exponential growth of Internet applications has created new challenges for the control and administration of large-scale networks, which consist of heterogeneous elements under dynamically changing traffic conditions. These emerging applications need guaranteed service levels, beyond those supported by best-effort networks, to deliver the intended services to the end user. Several models have been proposed for a Quality of Service (QoS) framework that can provide the means to transport these services. It is desirable to find efficient routing strategies that can meet the strict routing requirements of these applications. QoS routing is considered as one of the major components of the QoS framework in communication networks. In QoS routing, paths are selected based upon the knowledge of resource availability at network nodes and the QoS requirements of traffic. Several QoS routing schemes have been proposed that differ in the way they gather information about the network state and the way they select paths based on this information. The biggest downside of current QoS routing schemes is the frequent maintenance and distribution of global state information across the network, which imposes huge communication and processing overheads. Consequently, scalability is a major issue in designing efficient QoS routing algorithms, due to the high costs of the associated overheads. Moreover, inaccuracy and staleness of global state information is another problem that is caused by relatively long update intervals, which can significantly deteriorate routing performance. Localized QoS routing, where source nodes take routing decisions based solely on statistics collected locally, was proposed relatively recently as a viable alternative to global QoS routing. It has shown promising results in achieving good routing performance, while at the same time eliminating many scalability related problems. In localized QoS routing each source-destination pair needs to determine a set of candidate paths from which a path will be selected to route incoming flows. The goal of this thesis is to enhance the scalability of QoS routing by investigating and developing new models and algorithms based on the localized QoS routing approach. For this thesis, we have extensively studied the localized QoS routing approach and demonstrated that it can achieve a higher routing performance with lower overheads than global QoS routing schemes. Existing localized routing algorithms, Proportional Sticky Routing (PSR) and Credit-Based Routing (CBR), use the blocking probability of candidate paths as the criterion for selecting routing paths based on either flow proportions or a crediting mechanism, respectively. Routing based on the blocking probability of candidate paths may not always reflect the most accurate state of the network. This has motivated the search for alternative localized routing algorithms and to this end we have made the following contributions. First, three localized bandwidth-constrained QoS routing algorithms have been proposed, two are based on a source routing strategy and the third is based on a distributed routing strategy. All algorithms utilize the quality of links rather than the quality of paths in order to make routing decisions. Second, a dynamic precautionary mechanism was used with the proposed algorithms to prevent candidate paths from reaching critical quality levels. Third, a localized delay-constrained QoS routing algorithm was proposed to provide routing with an end-to-end delay guarantee. We compared the performance of the proposed localized QoS routing algorithms with other localized and global QoS routing algorithms under different network topologies and different traffic conditions. Simulation results show that the proposed algorithms outperform the other algorithms in terms of routing performance, resource balancing and have superior computational complexity and scalability features.

Almost everywhere, routing plays an important role in everyday life. This thesis consists of three parts, each studying different applications where routing decisions are coordinated with other decisions. A common denominator in all applications is that an intelligent utilization of a fleet of vehicles is crucial for the performance of the system. In the first part, routing and inventorymanagement decisions are coordinated, in the second part, routing decisions concerning different modes of transportation are coordinated with inventory management, and in the third part, location decision and routing are coordinated. In the first part, an application concerning waste management is presented. Many industries generate garbage, and instead of handling the waste disposal themselves, other companies, specialized in garbage collection, handle the disposal. Each industry rents containers from a company to be used for waste, and the garbage collection companies handle the collection. The industries buy a service including one or more containers at the industry and the garbage collection companies are obliged to make sure that the containers never become overfull. The idea is that the industries buy this service and in return, the garbage collection company can plan the collection so that the overall cost and the number of overfull containers is minimized. Two models for the problem facing the garbage collection company are proposed. The first is solved using a Lagrangean relaxation approach on a flow based model, and the second is solved using Benders decomposition on a column based model. The second part investigates a distribution chain management problem taken from the Swedish pulp industry. Given fixed production plans at the mills, and fixed customer demands, the problem is to minimize the distribution cost. Unlike many other models for marine distribution chains, the customers are not located at the harbors. This means that the model proposed also incorporates the distribution planning from the harbors to the customers. All customers are not served from the harbors; some are served directly from the mills using trucks and trains to distribute the pulp, and these decisions are also included. The problem is modeled as a mixed integer linear program and solved using a branch and price scheme. Due to the complexity of the problem, the solution strategy is divided into two phases, where the first emphasizes the generation of schedules for the vessels operated by the company, while the second deals with the chartering of vessels on the spot market. In the third part, routing is combined with location decisions in the location-routing problem. Special emphasis is given to strategic management where decision makers must make location, capacity and routing decisions over a long planning period. The studied application comes fromstrategic schoolmanagement, where the location and capacity of the schools as well as their catchment areas are under consideration. The problem is modeled as a mixed integer linear program. The computational study shows the importance of incorporating a routing component allowing multiple visits, as well as the danger of having a too short planning period.

A mobile ad-hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the support of any established infrastructure or centralized administration. There are many potential applications based the techniques of MANETs, such as disaster rescue, personal area networking, wireless conference, military applications, etc. MANETs face a number of challenges for designing a scalable routing protocol due to their natural characteristics. Guaranteeing delivery and the capability to handle dynamic connectivity are the most important issues for routing protocols in MANETs. In this dissertation, we will propose four algorithms that address different aspects of routing problems in MANETs. Firstly, in position based routing protocols to design a scalable location management scheme is inherently difficult. Enhanced Scalable Location management Service (EnSLS) is proposed to improve the scalability of existing location management services, and a mathematical model is proposed to compare the performance of the classical location service, GLS, and our protocol, EnSLS. The analytical model shows that EnSLS has better scalability compared with that of GLS. Secondly, virtual backbone routing can reduce communication overhead and speedup the routing process compared with many existing on-demand routing protocols for routing detection. In many studies, Minimum Connected Dominating Set (MCDS) is used to approximate virtual backbones in a unit-disk graph. However finding a MCDS is an NP-hard problem. In the dissertation, we develop two new pure localized protocols for calculating the CDS. One emphasizes forming a small size initial near-optimal CDS via marking process, and the other uses an iterative synchronized method to avoid illegal simultaneously removal of dominating nodes. Our new protocols largely reduce the number of nodes in CDS compared with existing methods. We show the efficiency of our approach through both theoretical analysis and simulation experiments. Finally, using multiple redundant paths for routing is a promising solution. However, selecting an optimal path set is an NP hard problem. We propose the Genetic Fuzzy Multi-path Routing Protocol (GFMRP), which is a multi-path routing protocol based on fuzzy set theory and evolutionary computing.

Satellite systems have the advantage of global coverage and offer a solution for providing broadband access to end users. Local terrestrial networks and terminals can be connected to the rest of the world over Low Earth Orbit (LEO) satellite networks simply by installing small satellite interfaces. With these properties, satellite systems play a crucial role in the global Internet to support real-time and non-real-time applications. Routing in satellite networks, and the integration of satellite networks and the terrestrial Internet are the key issues to support these services. Furthermore, the developments in space technologies enable the realization of deep-space missions such as Mars exploration. The Interplanetary Internet is envisioned to provide communication services for scientific data delivery and navigation services for the explorer spacecrafts and orbiters of future deep-space missions. The unique characteristics posed by deep-space communications call for different research approaches from those in terrestrial networks. The objective of this research is to develop advanced architectures and efficient routing protocols for satellite and space networks to support applications with different traffic types and heterogeneous quality-of-service (QoS) requirements. Specifically, a new QoS-based routing algorithm (QRA) is proposed as a connection-oriented routing scheme to support real-time multimedia applications in satellite networks. Next, the satellite grouping and routing protocol (SGRP) is presented as a unicast routing protocol in a two-layer satellite IP network architecture. The border gateway protocol - satellite version (BGP-S) is then proposed as a unified routing protocol to accomplish the integration of the terrestrial and satellite IP networks at the network layer. Finally, a new routing framework, called the space backbone routing (SBR), is introduced for routing through different autonomous regions in the Interplanetary Internet. SBR provides a self-contained and scalable solution to support different traffic types through the Interplanetary Internet.

Routing in sensor networks is a challenging issue due to inherent constraints such as power, memory, and CPU processing capabilities. In this thesis, we assume an All to All communication mode in an N × N grid sensor network. We explore routing algorithms which load balance the network without compromising the shortest paths constrain. We analyzed the Servetto method and studied two routing strategies, namely Horizontal-Vertical routing and Zigzag routing. The problem is divided into two scenarios, one being the static case (without failed nodes), and the other being the dynamic case (with failed nodes). In static network case, we derived mathematical formulae representing the maximum and minimum loads on a sensor grid, when specific routing strategies are employed. We show improvement in performance in load balancing of the grid by using Horizontal-Vertical method instead of the existing Servetto method. In the dynamic network scenario, we compare the performance of routing strategies with respect to probability of failure of nodes in the grid network. We derived the formulae for the success-ratio, in specific strategies, when nodes fail with a probability of p in a predefined source-destination pair communication. We show that the Servetto method does not perform well in both scenarios. In addition, Hybrid strategy proposed does not perform well compared to the studied strategies. We support the derived formulae and the performance of the routing strategies with extensive simulations.