In farming operation, machinery represents a major cost; therefore, good fleet management can have a great impact on the producer’s profit, especially considering the increasing costs of fuel and production inputs in recent years. One of the tasks to be accomplished in order to improve fleet management is planning the path that the machine should take to cover the field while working. Information such as distance traveled, time and fuel consumption as well as agricultural inputs wasted due to off-target-application areas are crucial in the path planning process. Parameters such as field boundary size and geometry, machine total width as well as control width resolution present a great impact on the information necessary for path planning. Researchers around the world have proposed methods that approach specific aspects related to path planning, the majority addressing machine field efficiency per-se, which a function of total time spent in the field as well as effective working time. However, wasted inputs due to off-target-application areas in the maneuvering regions, especially in oddly shaped agricultural fields might be as important as field efficiency when it comes down to the total operation cost. Thus, the main purpose of this research was to develop a path planning method that accounts for not only machinery field efficiency, but also the supply inputs. This research was accomplished in a threefold approach where in the first step an algorithm for computing off-target application area was developed, implemented and validated resulting in a computational tool that can be used to evaluate potential savings when using automatic section control on agricultural fields of complex field boundary. This tool allowed accomplishment of the second step, which was an investigation and better understanding of field size and shape as well as machine width of the effects on off-target application areas resulting in an empirical method for such estimations based on object shape descriptors. Finally, a path planning algorithm was developed and evaluated taking into consideration the aspects of machine field efficiency as well as off-target application areas.

The aim of this thesis is to conduct performance investigation of a combined system of Network Coding (NC) technique with Ant-Colony (ACO) routing protocol. This research analyses the impact of several workload characteristics, on system performance. Network coding is a significant key development of information transmission and processing. Network coding enhances the performance of multicast by employing encoding operations at intermediate nodes. Two steps should realize while using network coding in multicast communication: determining appropriate transmission paths from source to multi-receivers and using the suitable coding scheme. Intermediate nodes would combine several packets and relay them as a single packet. Although network coding can make a network achieve the maximum multicast rate, it always brings additional overheads. It is necessary to minimize unneeded overhead by using an optimization technique. On other hand, Ant Colony Optimization can be transformed into useful technique that seeks imitate the ant’s behaviour in finding the shortest path to its destination using quantities of pheromone that is left by former ants as guidance, so by using the same concept of the communication network environment, shorter paths can be formulated. The simulation results show that the resultant system considerably improves the performance of the network, by combining Ant Colony Optimization with network coding. 25% improvement in the bandwidth consumption can be achieved in comparison with conventional routing protocols. Additionally simulation results indicate that the proposed algorithm can decrease the computation time of system by a factor of 20%.

A mobile wireless ad hoc network (MANET) consists of a group of mobile nodes communicating wirelessly with no fixed infrastructure. Each node acts as source or receiver, and all play a role in path discovery and packet routing. MANETs are growing in popularity due to multiple usage models, ease of deployment and recent advances in hardware with which to implement them. MANETs are a natural environment for multicasting, or group communication, where one source transmits data packets through the network to multiple receivers. Proposed applications for MANET group communication ranges from personal network apps, impromptu small scale business meetings and gatherings, to conference, academic or sports complex presentations for large crowds reflect the wide range of conditions such a protocol must handle. Other applications such as covert military operations, search and rescue, disaster recovery and emergency response operations reflect the "mission critical" nature of many ad hoc applications. Reliable data delivery is important for all categories, but vital for this last one. It is a feature that a MANET group communication protocol must provide. Routing protocols for MANETs are challenged with establishing and maintaining data routes through the network in the face of mobility, bandwidth constraints and power limitations. Multicast communication presents additional challenges to protocols. In this dissertation we study reliability in multicast MANET routing protocols. Several on-demand multicast protocols are discussed and their performance compared. Then a new reliability protocol, R-ODMRP is presented that runs on top of ODMRP, a well documented "best effort" protocol with high reliability. This protocol is evaluated against ODMRP in a standard network simulator, ns-2. Next, reliable multicast MANET protocols are discussed and compared. We then present a second new protocol, Reyes, also a reliable on-demand multicast communication protocol. Reyes is implemented in the ns-2 simulator and compared against the current standards for reliability, flooding and ODMRP. R-ODMRP is used as a comparison point as well. Performance results are comprehensively described for latency, bandwidth and reliable data delivery. The simulations show Reyes to greatly outperform the other protocols in terms of reliability, while also outperforming R-ODMRP in terms of latency and bandwidth overhead.

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In this thesis, we focus on the design of the fault-tolerant routing algorithm for the (n, k)-star graph. We apply the idea of collecting the limited global information used for routing on the n-star graph to the (n, k)-star graph. First, we build the probabilistic safety vector (PSV) with modified cycle patterns. Then, our routing algorithm decides the fault-free routing path with the help of PSV. In order to improve the routing performance with more faulty nodes, we dynamically assign the threshold for our routing algorithm. The performance is judged by the average length of routing paths. Compared with distance first search and safety level, we get the best performance in the simulations.

.Wireless Sensor Networks importance is rapidly increasing and becoming a vital element in the process of gathering information in almost every scientific and practical aspect, but since the sensor node is usually a small device and has a battery with very limited life, power consumption is turning out to be the main drawback of this significant technology thus a lot of work and researches is going on to find new ways to reduce the power needed to operate those sensors. One of the main power consuming functionality of this technology is the wireless transmission of the data that the sensors collect across the fields [5][6]. In order to overcome this restriction, many proposals have been made to create an optimal algorithm that can guide the way each sensor node transmit it's data in order to reduce the power needed for the transmission process. This research focuses on creating a simplified scheduling algorithm that can break up the transmission waves into chains of nodes, so that each node transmits the data that has been collected to the best available node around, and so on till the information is propagated to the main server that collects all the information and analyze them.This newly proposed algorithm takes many attributes into considerations, but the main ones are the geographical information and the load that each senor node carries. A simulation model has been created to verify the effectiveness of the algorithm and to compare how close the results to the ideal network configuration are.

A wireless sensor network (WSN) is made of tiny sensor nodes usually deployed in high density within a targeted area to monitor a phenomenon of interest such as temperature, vibration or humidity. The WSNs can be employed in various applications (e.g., Structural monitoring, agriculture, environment monitoring, machine health monitoring, military, and health). For each application area there are different technical issues and remedies. Various challenges need to be considered while setting up a WSN, including limited computing, memory and energy resources, wireless channel errors and network scalability. One way of addressing these problems is by implementing a routing protocol that efficiently uses these limited resources and hence reduces errors, improves scalability and increases the network lifetime. The topology of any network is important and wireless sensor networks (WSNs) are no exception. In order to effectively model an energy-efficient routing algorithm, the topology of the WSN must be factored in. However, little work has been done on routing for WSNs with regular patterned topologies, except for the shortest path first (SPF) routing algorithms. The issue with the SPF algorithm is that it requires global location information of the nodes from the sensor network, which proves to be a drain on the network resources. In this thesis a novel algorithm namely, BRALB (Biased Random Algorithm for Load Balancing) is proposed to overcome the issues faced in routing data within WSNs with regular topologies such as square-base topology and triangle-based topology. It is based on random walk and probability. The proposed algorithm uses probability theory to build a repository of information containing the estimate of energy resources in each node, in order to route packets based on the energy resources in each node and thus does not require any global information from the network. It is shown in this thesis by statistical analysis and simulations that BRALB uses the same energy as the shortest path first routing as long as the data packets are comparable in size to the inquiry packets used between neighbours. It is also shown to balance the load (i.e. the packets to be sent) efficiently among the nodes in the network. In most of the WSN applications the messages sent to the base station are very small in size. Therefore BRALB is viable and can be used in sensor networks employed in such applications. However, one of the constraints of BRALB is that it is not very scalable; this is a genuine concern as most WSNs deployment is large scale. In order to remedy this problem, C-BRALB (Clustered Biased Random Algorithm for Load Balancing) has been proposed as an extension of BRALB with clustering mechanism. The same clustering technique used in Improved Directed Diffusion (IDD) has been adopted for C-BRALB. The routing mechanism in C-BRALB is based on energy biased random walk. This algorithm also does not require any global information apart from the initial flooding initiated by the sink to create the clusters. It uses probability theory to acquire all the information it needs to route packets based on energy resources in each cluster head node. It is shown in this thesis by using both simulations and statistical analysis that C-BRALB is an efficient routing algorithm in applications where the message to be sent is comparable to the inquiry message among the neighbours. It is also shown to balance the load (i.e. the packets to be sent) among the neighbouring cluster head nodes.

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No / Localized Quality of Service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information and the staleness of such information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localized view of the network QoS state . In this paper we introduce a credit based routing algorithm (cbr) which is a simple yet effective localized QoS routing algorithm. We compare its performance against the localized proportional sticky routing (psr) algorithm same time complexity. using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that our algorithm outperforms the psr algorithm with the same time complexity.