published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

Wireless sensor network localization opens the door to many location based applications. In this thesis, some solutions obtained from localization algorithms are investigated. There are two categories of problem on localization. Range-based methods are applied to the situation in which information on the distances between each pair of nodes is available. Algorithms are developed to estimate the location of each sensor in the network. Usually, the distance between each pair of nodes is estimated by the signal strength received between them, and this information is very noisy. Range-free methods, which are also called connectivity-based methods, assume that the distances between any two nodes are unknown but the connectivity information between them is known. If the distance between any two nodes in the network is within a communication range, connectivity between these two nodes is said to be established. In a range-based scenario, with the information of inter-sensor distance measurements as well as the absolute locations of the anchors, the objective is to obtain the location of all the unknown nodes. Two new localization methods based on gradient descent are shown in the thesis. The gradient descent methods would minimize the difference between the measured distances and the distances obtained from the estimated locations. From a comparison with other well-known localization methods, the two newly developed gradient descent algorithms can reach better accuracy at the expense of computational complexity. This is not surprising as the proposed algorithms are iterative in nature. For range-free scenario, a new model utilizing all the information derived from connectivity-based sensor network localization is introduced. Unlike other algorithms which only utilize the information on connections, this model makes use of both information on connections and disconnections between any pair of nodes. The connectivity information between any pair of nodes is modeled as convex and non-convex constraints. The localization problem is solved by an optimization algorithm to obtain a solution that would satisfy all the constraints established in the problem. The simulation has shown that better accuracy is obtained when compared with algorithms developed by other researchers. Another solution for the range-free scenario is obtained with the use of a two-objective evolutionary algorithm called Pareto Archived Evolution Strategy (PAES). In an evolutionary algorithm, the aim is to search for a solution that would satisfy all the convex and non-convex constraints of the problem. The number of wrong connections and the summation of corresponding distances are set as the two objectives. A starting point on the location of the unknown nodes is obtained using a solution from the result of all convex constraints. The final solution can reach the most suitable configuration of the unknown nodes as all the information on the constraints (convex and non-convex) related to connectivity have been used. From the simulation results, a relationship between the communication range and accuracy is obtained. In this thesis, another evolutionary algorithm has been examined to obtain a solution for our problem. The solution is based on a modified differential evolution algorithm with heuristic procedures peculiar to our domain of application. The characteristics of the sensor network localization are thoroughly investigated and utilized to produce corresponding treatment to search for the reasonable node locations. The modified differential evolution algorithm uses a new crossover step that is based on the characteristics of the problem. With the combination of some heuristics, the solution search can move the node to jump out of local minimums more easily, and give better accuracy than current algorithms. In the last part of the thesis, a novel two-level range connectivity-based sensor network localization problem is proposed, which would enrich the connectivity information. In this new problem, the information of the connectivity between any pair of nodes is either strong, weak or zero. Again, a two-objective evolutionary algorithm is used to search for a solution that would satisfy all the convex and non-convex constraints of the problem. Based on simulations on a range of situations, a suitable range value for the second range is found. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

In typical location-based services (LBS), moving objects (e.g., GPS-enabled mobile phones) report their locations through a wireless network. An LBS server can use the location information to answer various types of continuous queries, e.g., \Give me the ID of a battalion which is the closest to a military base within the next hour." Due to hardware limitations, location data reported by the moving objects are often uncertain. In this paper, we study efficient methods for the execution of Continuous Possible Nearest Neighbor Query (CPoNNQ) that accesses imprecise location data. A CPoNNQ is a standing query (which is active during a period of time) such that, at any time point, all moving objects that have non-zero probabilities of being the nearest neighbor of a given query point are reported. To handle the continuous nature of a CPoNNQ, a simple solution is to require moving objects to continuously report their locations to the LBS server, which evaluates the query at every time step. To save communication bandwidth and mobile devices' batteries, we develop two filter-based protocols for CPoNNQ evaluation. Our protocols install filter bounds" on moving objects, which suppress unnecessary location reporting and communication between the server and the moving objects. Through extensive experiments, we show that our protocols can effectively reduce communication and energy costs while maintaining a high query quality. / published_or_final_version / Computer Science / Master / Master of Philosophy

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Consumer acceptance of buying goods and services online via the Internet is growing, although e-ecommerce has been mostly a mirror of traditional methods of pricing transactions – fixed price or auctions. The proliferation of personal mobile devices with pervasive Internet access and localization capability means a richer set of pricing parameters can be used. Allowing buyers and sellers to more explicitly price requests and filter offers, including information about time and place, allows for better transaction results for both parties. This paper examines the impacts of including the time and place of performance of a service as part of the price. A system for implementation is proposed, a simulation of the system is evaluated, and the results presented. / text

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Γίνετε ανασκόπηση των πιο σημαντικών προβλημάτων της Ανάλυσης Χωροθέτησης. Παρατίθονται συγκρίσεις των προβλημάτων της Ανάλυσης Χωροθέτησης με τους Αλγορίθμους Ομαδοποίησης. Ακολούθως αναγράφεται μια αριθμητική εφαρμογή μιας σύγκρισης. / This project is a review of the more important algorithms of the Locational Analysis. The main theme is the comparison of the algorithms of Location Analysis against the algorithms of Clustering.

In this master paper are analyzed services which are offered in GSM network. There is review of offered possibilities and its resources. There have been created model which imitates mass following service in mobile network. There have been made research by this created tool which quantitatively evaluates general quantity of update and paging procedures depending on size of location area and type of subscriber. There have been noticed some tendencies which depend on: paging period, size of location area and the ratio of transfered mesages by location updating and by paging procedures.