In this paper, we propose a novel Unipolar CMOS device in which the transport carriers are electron only. And we achieve good inverter output waveform and logic circuit applications by simulation. Duo to all n-channel (NMOS) structures are used, we call this proposed CMOS as a Unipolar CMOS. A new basic theory of utilizing the punch through effect is demonstrated to enhance the tPLH in our proposed Unipolar CMOS. The average delay time compared with the classical CMOS circuit can be improved 23% for high-performance applications. For our proposed Unipolar CMOS, all n-channel MOS are used to eliminate the N- and P-well processes and ignore the difference between the carrier mobility. In addition, the common electrodes are also exploited, hence, the layout area can be reduced to about 75%, which leads to significantly increase the packing density of CMOS circuits in the same chip.

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This paper studies the integrated mobile ad-hoc networks (MANETs) and Internet network which the Mobile IP and AODV routing protocols are integrated to offer MANET nodes to set up multi-hop routes to the Internet. Gateways act as bridges for forwarding data packets between integrated MANETs and the Internet. Mobile nodes in MANETs must discover available gateways to gain access to the Internet. This study presents an adaptive gateway discovery scheme that balances efficiency and overhead by limiting the flooding scope of gateway advertisement messages. The proposed scheme dynamically adjusts the ADV_TTL according to the average delay time of network. The simulation results showed that the proposed scheme obtains the shortest average delay time while keeping the network a relatively lower overhead.

Different applications of communication networks have different requirements that depend on the type of application. We consider the problem of differentiating between delay-sensitive applications based on their average delay requirements, as may be of interest in signalling networks. We consider packets of different classes that are to be transmitted on the same link with different average delay requirements, to reside in separate queues with the arrival statistics for the queues being specified. This statistical multiplexer has to schedule packets from different queues in so that the average delays of the queues approach the specified target delays as quickly as possible. For simplicity, we initially consider a discrete-time model with two queues and a single work-conserving server, with independent Bernoulli packet arrivals and unit packet service times. With arrival rates specified, achieving mean queue lengths in a ratio which corresponds to the ratio of target mean delays is a means of achieving individual target mean delays. We formulate the problem in the framework of Markov decision theory. We study two scheduling policies called Queue Length Balancing and Delay Balancing respectively, and show through numerical computation that the expectation of magnitude of relative error in θ (1/m) and θ (1/√m) respectively, and that the expectation of the magnitude of relative error in weighted average delays decays as θ (1/√m) and θ (1/m) respectively, where m is the averaging interval length. We then consider the model for an arbitrary number of queues each with i.i.d. batch arrivals, and analyse the errors in the average delays of individual queues. We assume that the fifth moment of busy period is finite for this model. We show that the expectation of the absolute value of error in average queue length for at least one of the queues decays at least as slowly as θ (1/√m), and that the mean squared error in queue length for at least one of the queues decays at least as slowly as θ (1/m). We show that the expectation of the absolute value of error in approximating Little’s law for finite horizon is 0 (1/m). Hence, we show that the mean squared error in delay for at least one of the queues decays at least slowly as θ (1/m). We also show that if the variance of error in delay decays for each queue, then the expectation of the absolute value of error in delay for at least one of the queues decays at least as slowly as θ (1/√m).

One of the most significant urban transport problems is traffic congestion. All major cities both in developed and developing countries are facing the problem due to increasing travel demand caused by increasing urbanization and the attendant economic and population growth. Recognizing the growing burden of traffic congestion, community leaders and transportation planners in Addis Ababa are still actively promoting large-scale road constructions to alleviate traffic congestion. Although Intelligent Transportation Systems(ITS) applications seem to have the potential to improve signalization performance, highly congested intersections in Addis Ababa are still controlled by a timed signal and manual operation. Moreover, these pre-timed signal controls are functioning sub-optimally as they are not being regularly monitored and updated to cope with varying traffic demands. Even though the benefits are well known theoretically, at the time of writing of this thesis, Adaptive Traffic Signal Controllers (ATSC) haven’t been deployed in Ethiopia and no research has been conducted to demonstrate and quantify their effectiveness. This master’s research thesis, therefore, intends to fill the identified gap, by undertaking a microscopic traffic simulation investigation, to evaluate the benefits of adopting a Traffic-responsive Urban Control (TUC) strategy and optimizing traffic signal timings. For the purpose of this study, an oversaturated three-intersection test corridor located in the heart of Addis Ababa city is modeled in VISSIM using real-world traffic data. After validating the calibrated model, the corridor was evaluated with the existing pre-timed, TRANSYT optimized pre-timed plan and TUC strategy. Multiple simulation runs were then made for each scenario alternatives and various measures of effectiveness were considered in the evaluation process. Simulation evaluation has demonstrated an average delay reduction of 24.17% when the existing pre-timed alternative is compared to TRANSYT optimized plan and 35% when compared to the TUC strategy. Overall evaluation results indicate that deploying the TUC strategy and optimizing the aging pre-timed signal plans exhibits a significant flow improvement. It is expected that the result of the thesis work will be an input for future comprehensive policy development processes.

In this thesis, we study the tradeoff of average delay with average service cost and average utility for both continuous time and discrete time single server queueing models without and with admission control. The continuous time and discrete time queueing models that we consider are motivated by cross-layer models for point-to-point links with random packet arrivals and fading at slow and fast time scales. Our studies are motivated by the need to optimally tradeoff the average delay of the packets (a network layer performance measure) with the average service cost of transmitting the packets, e.g. the average power required for transmission (a physical layer performance measure) under a lower bound constraint on the average throughput, in various point-to-point communication scenarios. The tradeoff problems are studied for a class of monotone and stationary scheduling policies and under the assumption that the service cost rate and utility rate are respectively convex and concave functions of the service rate and arrival rate. We also consider the problem of optimally trading off the average delay and average error rate of randomly arriving message symbols which are transmitted over a noisy point-to-point link, in which case the service cost function is non-convex. The solutions to the tradeoff problems that we address in the thesis are asymptotic in nature, and are similar in spirit to the Berry-Gallager asymptotic bounds. It is intuitive that to keep a queue stable under a lower bound constraint on the average utility a minimum number of customers have to be served per unit time. This in turn implies that queue stability requires a minimum average service cost expenditure. In the thesis we obtain an asymptotic characterization of the minimum average delay for monotone stationary policies subject to an upper bound constraint on the average service cost and a lower bound constraint on the average utility, in the asymptotic regime where the average service cost constraint is made arbitrarily close to the above minimum average service cost. In the thesis, we obtain asymptotic lower bounds on the minimum average delay for the cases for which lower bounds were previously not known. The asymptotic characterization of the minimum average delay for monotone stationary policies, for both continuous time and discrete time models, is obtained via geometric bounds on the stationary probability of the queue length, in the above asymptotic regime. The restriction to monotone stationary policies enables us to obtain an intuitive explanation for the behaviour of the asymptotic lower bounds using the above geometric bounds on the stationary probability distribution of the queue length. The geometric bounds on the stationary probability of the queue length also lead to a partial asymptotic characterization of the structure of any optimal monotone stationary policy, in the above asymptotic regime, which was not available in previous work. Furthermore, the geometric bounds on the stationary probability can be extended to analyse the tradeoff problem in other scenarios, such as for other continuous time queueing models, multiple user communication models, queueing models with service time control, and queueing models with general holding costs. Usually, queueing models with integer valued queue evolution, are approximated by queueing models with real valued queue evolution and strictly convex service cost functions for analytical tractability. Using the asymptotic bounds, we show that for some cases the average delay does not grow to infinity in the asymptotic regime, although the approximate model suggests that the average delay does grow to infinity. In other cases where the average delay does grow to infinity in the asymptotic regime, our results illustrate that the tradeoff behaviour of the approximate model is different from that of the original integer valued queueing model unless the service cost function is modelled as the piecewise linear lower convex envelope of the service cost function for the original model.

Vehicular ad hoc networks (VANETs) are a subclass of mobile ad hoc networks (MANETs) in which the mobile nodes are vehicles; these vehicles are autonomous systems connected by wireless communication on a peer-to-peer basis. They are self-organized, self-configured and self-controlled infrastructure-less networks. This kind of network has the advantage of being able to be set-up and deployed anywhere and anytime because it has no infrastructure set-up and no central administration. Distributing information between these vehicles over long ranges in such networks, however, is a very challenging task, since sharing information always has a risk attached to it especially when the information is confidential. The disclosure of such information to anyone else other than the intended parties could be extremely damaging, particularly in military applications where controlling the dissemination of messages is essential. This thesis therefore provides a review of the issue of security in VANET and MANET; it also surveys existing solutions for dissemination control. It highlights a particular area not adequately addressed until now: controlling information flow in VANETs. This thesis contributes a policy-based framework to control the dissemination of messages communicated between nodes in order to ensure that message remains confidential not only during transmission, but also after it has been communicated to another peer, and to keep the message contents private to an originator-defined subset of nodes in the VANET. This thesis presents a novel framework to control data dissemination in vehicle ad hoc networks in which policies are attached to messages as they are sent between peers. This is done by automatically attaching policies along with messages to specify how the information can be used by the receiver, so as to prevent disclosure of the messages other than consistent with the requirements of the originator. These requirements are represented as a set of policy rules that explicitly instructs recipients how the information contained in messages can be disseminated to other nodes in order to avoid unintended disclosure. This thesis describes the data dissemination policy language used in this work; and further describes the policy rules in order to be a suitable and understandable language for the framework to ensure the confidentiality requirement of the originator. This thesis also contributes a policy conflict resolution that allows the originator to be asked for up-to-date policies and preferences. The framework was evaluated using the Network Simulator (NS-2) to provide and check whether the privacy and confidentiality of the originators’ messages were met. A policy-based agent protocol and a new packet structure were implemented in this work to manage and enforce the policies attached to packets at every node in the VANET. Some case studies are presented in this thesis to show how data dissemination can be controlled based on the policy of the originator. The results of these case studies show the feasibility of our research to control the data dissemination between nodes in VANETs. NS-2 is also used to test the performance of the proposed policy-based agent protocol and demonstrate its effectiveness using various network performance metrics (average delay and overhead).