A mobile ad hoc network (MANET) consists of a group of autonomous mobile nodes with no infrastructure support. In this research, we develop a distributed intrusion detection and response system for MANET, and we believe it presents a second line of defense that cannot be replaced by prevention schemes. We based our detection framework on the study of attack taxonomy. We then propose a set of detection methods suitable of detecting different attack categories. Our approaches are based on protocol specification analysis with categorical and statistical measures. Node-based approaches may be too restrictive in scenarios where attack patterns cannot be observed by any isolated node. Therefore, we have developed cooperative detection approaches for a more effective detection model. One approach is to form IDS clusters by grouping nearby nodes, and information can be exchanged within clusters. The cluster-based scheme is more efficient in terms of power consumption and resource utilization, it is also proved resilient against common security compromises without changing the decentralized assumption. We further address two response techniques, traceback and filtering. Existing traceback systems are not suitable for MANET because they rely on incompatible assumptions such as trustworthy routers and static route topology. Our solution, instead, adapts to dynamic topology with no infrastructure requirement. Our solution is also resilient in the face of arbitrary number of collaborative adversaries. We also develop smart filtering schemes to maximize the dropping rate of attack packets while minimizing the dropping rate of normal packets with real-time guarantee. To validate our research, we present case study using both ns-2 simulation and MobiEmu emulation platform with three ad hoc routing protocols: AODV, DSR and OLSR. We implemented various representative attacks based on the attack taxonomy. Our experiments show very promising results using node-based and cluster-based approaches.

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, and mine reconnaissance. The enabling technology for these applications is acoustic wireless networking. UnderWater Acoustic Sensor Networks (UW-ASNs) consist of sensors and Autonomous Underwater Vehicles (AUVs) deployed to perform collaborative monitoring tasks. The objective of this research is to explore fundamental key aspects of underwater acoustic communications, propose communication architectures for UW-ASNs, and develop efficient sensor communication protocols tailored for the underwater environment. Specifically, different deployment strategies for UW-ASNs are studied, and statistical deployment analysis for different architectures is provided. Moreover, a model characterizing the underwater acoustic channel utilization efficiency is introduced. The model allows setting the optimal packet size for underwater communications. Two distributed routing algorithms are proposed for delay-insensitive and delay-sensitive applications. The proposed routing solutions allow each node to select its next hop, with the objective of minimizing the energy consumption taking the different application requirements into account. In addition, a resilient routing solution to guarantee survivability of the network to node and link failures in long-term monitoring missions is developed. Moreover, a distributed Medium Access Control (MAC) protocol for UW-ASNs is proposed. It is a transmitter-based code division multiple access scheme that incorporates a novel closed-loop distributed algorithm to set the optimal transmit power and code length. It aims at achieving high network throughput, low channel access delay, and low energy consumption. Finally, an efficient cross-layer communication solution tailored for multimedia traffic (i.e., video and audio streams, still images, and scalar sensor data) is introduced.

Compared to conventional Steiner tree signal net routing, non-tree topology is often superior in many aspects including timing performance, tolerance to open faults and variations. In nano-scale VLSI designs, interconnect delay is a performance bottleneck and variation effects are increasingly problematic. Therefore the advantages of non-tree topology are particularly appealing for timing critical net routings in nano-scale VLSI designs. We propose Steiner network construction heuristics which can generate either tree or non-tree of signal net with different slack wirelength tradeoffs, and handle both long path and short path constraints. Extensive experiments in different scenarios show that our heuristics usually improve timing slack by hundreds of pico seconds compared to traditional tree approaches while increasing only slightly in wirelength. These results show that our algorithm is a very promising approach for timing critical net routings.

In this dissertation, we studied methods for improving efficiency and effectiveness of multipath routing in computer networks. We showed that multipath routing can improve network performance for failure recovery, load balancing, Quality of Service (QoS), and energy consumption. We presented a method for reducing the overhead of computing dynamic path metrics, one of the obstacles for implementing dynamic multipath routing in real world networks. In the first part, we proposed a method for building disjoint multipaths that could be used for local failure recovery as well as for multipath routing. Proactive failure recovery schemes have been recently proposed for continuous service of delay-sensitive applications during failure transients at the cost of extra infrastructural support in the form of routing table entries, extra addresses, etc. These extra infrastructure supports could be exploited to build alternative disjoint paths in those frameworks, while keeping the lengths of the alternative paths close to those of the primary paths. The evaluations showed that it was possible to extend the proactive failure recovery schemes to provide support for nearly-disjoint paths which could be employed in multipath routing for load balancing and QoS. In the second part, we proposed a method for reducing overhead of measuring dynamic link state information for multipath routing, specifically path delays used in Wardrop routing. Even when dynamic routing could be shown to offer convergence properties without oscillations, it has not been widely adopted. One of reasons was that the expected cost of keeping the link metrics updated at various nodes in the network. We proposed threshold-based updates to propagate the link state only when the currently measured link state differs from the last updated state consider- ably. Threshold-based updates were shown through analysis and simulations to offer bounded guarantees on path quality while significantly reducing the cost of propagating the dynamic link metric information. The simulation studies indicated that threshold based updates can reduce the number of link updates by up to 90-95% in some cases. In the third part, we proposed methods of using multipath routing for reducing energy consumption in computer networks. Two different approaches have been advocated earlier, from traffic engineering and topology control to hardware-based approaches. We proposed solutions at two different time scales. On a finer time granularity, we employed a method of forwarding through alternate paths to enable longer sleep schedules of links. The proposed schemes achieved more energy saving by increasing the usage of active links and the down time of sleeping links as well as avoiding too frequent link state changes. To the best of our knowledge, this was the first technique combining a routing scheme with hardware scheme to save energy consumption in networks. In our evaluation, alternative forwarding reduced energy consumption by 10% on top of a hardware-based sleeping scheme. On a longer time granularity, we proposed a technique that combined multipath routing with topology control. The proposed scheme achieved increased energy savings by maximizing the link utilization on a reduced topology where the number of active nodes and links are minimized. The proposed technique reduced energy consumption by an additional 17% over previous schemes with single/shortest path routing.

Reconfigurable computing systems require supports from powerful computer aided design tools to help users developing the interactions between software programs and hardware circuits. The placement and routing support for reconfigurable processing units is also the key to the efficiency of the computing system. In this thesis, we implemented the placement and routing tool for the FMRPU (Fine-grain Multi-context Reconfigurable Processing Unit). The routing resource among the Logic Arrays supports only 8-bit aligned data width, so the routing of the FMRPU can¡¦t completely imitate from the pattern used by LUT-based routing. Thus we proposed an operation-based design model which accepts a data flow graph that describes the operations of the circuit. After compressing the graph, the tool uses Simulated Annealing algorithm with either Maze Route or Center-of-Gravity Route to map the compressed graph into FMRPU. Through the placement and routing tool we implemented, we have successfully mapped several algorithms used in multi-media applications, such as FFT and DCT, into FMRPU.

In this study, inventory&ndash / routing system of a company operating in Fast Moving Consumer Goods (FMCG) industry is analyzed. The company has decided to redesign distribution system by locating regional warehouses between production plants and customers. The warehouses in the system are all allowed to hold stock without any capacity restriction. The customers are replenished by the warehouse to which they have been assigned. Customer stocks are continuously monitored by the warehouse and deliveries are to be scheduled. In this multi&ndash / item, two-echelon inventory&ndash / distribution system, main problem is synchronizing inventory and distribution decisions. An integrated Mixed Integer Programming optimization model for inventory and distribution planning is proposed with the aim of optimally coordinating inventory management and vehicle routing. The model determines the replenishment periods of items and amount of delivery to each customer / and constructs the delivery routes with the objective of cost minimization. The integrated model is coded in GAMS and solved by CPLEX. The integrated inventory-routing model is simulated with retrospective data of the company. Computational results on test problems are provided to show the effectiveness of the model developed in terms of the performance measures defined. Moreover, the feasible solution obtained for a period is compared to the realized inventory levels and distribution schedules. Computational results seem to indicate a substantial advantage of the integrated inventory-routing system over the existing distribution system.

In this study we discuss the Vehicle Routing Problem with multiple use of vehicles (VRPM). In this variant of the routing problem the vehicles may replenish at any time at the depot. We present a detailed review of existing literature and propose two mathematical models to solve the VRPM. For these two models and their several variants we provide computational results based on the test problems taken from the literature. We also discuss a case study in which we are simultaneously dealing with side constraints such as time windows, working hour limits, backhaul customers and a heterogeneous vehicle fleet.

In this thesis, a feedback-based contention avoidance technique based on weighted Dijkstra algorithm is proposed to address the contention avoidance problem for Optical Burst Switching networks. Optical Burst Switching (OBS) has been proposed as a promising technique to support high-bandwidth, bursty data traffic in the next-generation optical Internet. Nevertheless, there are still some challenging issues that need to be solved to achieve an effective implementation of OBS. Contention problem occurs when two or more bursts are destined for the same wavelength. To solve this problem, various reactive contention resolution methods have been proposed in the literature. However, many of them are very vulnerable to network load and may suffer severe loss in case of heavy traffic. By proactively controlling the overall traffic, network is able to update itself in case of high congestion and by means of this method / contention avoidance can be achieved efficiently. The performance analysis of the proposed algorithm is presented through network simulation results provided by OMNET++ simulation environment. The simulation results show that the proposed contention avoidance technique significantly reduces the burst loss probability as compared to networks without any contention avoidance techniques.

The transportation phase of solid waste management is highly critical as it may constitute approximately 60 to 75 percent of the total cost. Therefore, even a small amount of improvement in the collection operation can result in a significant saving in the overall cost. Despite the fact that there exist a considerable amount of studies on Vehicle Routing Problem (VRP), a vast majority of the existing studies are not integrated with GIS and hence they do not consider the path constraints of real road networks for waste collection such as one-way roads and U-Turns. This study involves the development of computer software that optimizes the waste collection routes for solid waste transportation considering the path constraints and road gradients. In this study, two different routing models are proposed. The aim of the first model is to minimize the total distance travelled whereas that of the second model is to minimize the total fuel consumption that depends on the loading conditions of the truck and the road gradient. A comparison is made between these two approaches. It is expected that the two approaches generate routes having different characteristics. The obtained results are satisfactory. The distance optimization model generates routes that are shorter in length whereas the fuel consumption optimization model generates routes that are slightly higher in length but provides waste collection on steeply inclined roads with lower truck load. The resultant routes are demonstrated on a 3D terrain view.

This study aims to improve transportation held between six auction centers, Inter-Auction Transportation, of FloraHolland. FloraHolland serves ninety eight percent of the Dutch market and is the largest auction in floriculture industry. The company wants to give the best sale opportunities with the costs as low as possible and this is the main initiative of this study. In this line of thought, FloraHolland wants to have a improvement on its current routing and scheduling mechanism. Exact models do not work due to the complexity and the size of the problem. Therefore, we developed a two-stage approach specific to this study. With this approach, we split exact approach into two, a mathematical model followed by a heuristic. In the exact approach, trucks are routed and scheduled at the same time. On the other hand, our solution approach first determines most efficient routes to be followed with Cycle Assignment Model and then, with Scheduling Heuristic, trucks are assigned to the routes, so within day transportation is planned in detail. Overall, each stage of this approach works in harmony and brings good solutions in a short CPU time.