Project management has become a key component for improving organizational performance and is applied in many business areas and industries. Resource-constrained stochastic project networks are quite common. Managing such projects to maximize resource utilization and reduce project duration simultaneously is difficult. Resource loading, assignment rules, and priorities significantly affect project performance, especially in shared-resource, multi-project environments. This thesis provides an approach for using discrete-event simulation to analyze the behavior and performance of project networks that use resource pools. A method to translate project networks into simulation models is developed. The translator is used to convert and evaluate a benchmark test set of resource constrained stochastic project networks. The effect of factors like project network complexity, resource availability and allocation strategies on project performance is analyzed using a completely randomized design with factorial arrangement of the aforementioned factors. The conversion process and results from the analysis are discussed.

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Motivated by current applications in multihop transmission and ad hoc networks, the classical three-node relay channel consisting of a source-destination pair and a relay has received significant attention. One of the crucial aspects of the relay channel is the design of proper relaying protocols, i.e., how the relay should take part into transmission. The thesis addresses this problem and provides a partial answer to that. In this thesis, we propose and study two novel relaying protocols. The first one is based on constellation rearrangement (CR) and is suitable for higher-order modulation schemes. With CR, the relay uses a bit-symbol mapping that is different from the one used by the source. We find the optimal bit-symbol mappings for both the source and the relay and the associated optimal detectors, and show that the improvement over conventional relaying with Gray mapping at the source and the relay can amount to a power gain of several dB. This performance improvement comes at no additional power or bandwidth expense, and at virtually no increase in complexity. The second one is a half-duplex decode-and-forward (DF) relaying scheme based on partial repetition (PR) coding at the relay. With PR, if the relay decodes the received message successfully, it re-encodes the message using the same channel code as the one used at the source, but retransmits only a fraction of the codeword. We analyze the proposed scheme and optimize the cooperation level (i.e., the fraction of the message that the relay should transmit). We compare our scheme with conventional repetition in which the relay retransmits the entire decoded message, and with parallel coding, and additionally with dynamic DF. The finite SNR analysis reveals that the proposed partial repetition can provide a gain of several dB over conventional repetition. Surprisingly, the proposed scheme is able to achieve the same performance as that of parallel coding for some relay network configurations, but at a much lower complexity. Additionally, the thesis treats the problem of resource allocation for collaborative transmit diversity using DF protocols with different type of CSI feedback at the source. One interesting observation that emerges is that the joint powerbandwidth allocation only provides marginal gain over the relaying protocols with optimal bandwidth allocation. / QC 20101119

Due to the scarcity of wireless resources, efficient resource allocation is essential to the success of cellular systems. With the proliferation of bandwidth-hungry multimedia applications with diverse traffic characteristics and quality of service requirements, the resource management is becoming particularly challenging. In this thesis, we address some of the key link-layer resource allocation mechanisms that affect the performance of video streaming in cellular systems: bit-rate allocation, opportunistic scheduling, and statistical multiplexing. The bit-rate allocation problem involves the distortion-optimal assignment of source, channel, and pilot data rates under link capacity constraints. We derive an analytical model that captures the video distortion as a function of these data rates and, based on it, we study various bit-rate allocation strategies. The opportunistic scheduling problem addresses the throughput-optimal assignment of time-slots among users with diverse channel conditions under certain fairness constraints. We focus on two aspects of the opportunistic scheduling: the performance of delay-constrained streaming applications and possible extensions of the opportunistic concepts to multicast scenarios. Finally, the statistical multiplexing is a resource-efficient method for smoothing out the extreme burstiness of video streams. We study possible statistical multiplexing gains of H.264 video streams in the context of E-MBMS architecture. / QC 20101126

<p>In this thesis we study the handoff problem of mobile stations (MSs) jointly with the resource management at the access points (APs) for wireless mesh networks (WMNs), where the APs can dynamically adjust the transmission power and time to each of the associated MSs. Two objectives are considered, one is to balance the energy consumption of the APs, and the other is to achieve fair throughput among the MSs. Since the global optimum solutions are difficult to obtain, we propose heuristic schemes for achieving each of the objectives. The objective of balancing AP energy consumption is achieved in two steps. The optimum transmission power and rate is solved at each AP so that to minimize the energy consumption of the AP, assuming the MS-AP association is given. Two handoff schemes are then designed to find which MSs should be associated to which APs during each scheduling interval (SI). The schemes are based on energy consumption information exchanged among neighboring APs. The real-time energy balancing (REB) scheme tries to balance the energy consumption of the APs in each SI, while the long term energy balancing (LEB) scheme balances the AP energy consumption over a longer term. Our results indicate that the network lifetime can be significantly extended using the proposed handoff schemes, compared to the simple distance-based handoff scheme, and using LEB can achieve balanced AP energy consumption with a small number of handoffs. The second part of the thesis is to consider the MS handoff and AP resource allocations in order to achieve fair throughput among the MSs. An optimization problem is formulated and solved at each AP to achieve long term proportional fairness of the throughput among the MSs, assuming the MS-AP association is known. Two handoff schemes are proposed, one is utility-based, and the other is number-based, in order to determine which MSs should be associated to which APs. Our results show that both the schemes are good at achieving fair throughput among the MSs, and the schemes are not sensitive to MS moving speed or group mobility patterns. The number-based scheme is simpler than the utility-based one in terms of implementation.</p> / Master of Applied Science (MASc)

The limited energy and computational resources in small-scale smart devices impede the expansion of the range of applications that those devices can support, especially to applications with tight latency constraints. Mobile edge computing is a promising framework that provides shared computational resources in the access points in the network and provides devices in that network with the opportunity to offload (a portion of) their computational tasks to the access points. To effectively capture that opportunity in an offloading system with multiple devices, the available communication and computation resources must be efficiently allocated. The main focus of this thesis is on the optimal allocation of communication resources in a K-user offloading system. The resource allocation problem that is considered in this thesis captures minimizing the total energy consumption of users while the requirements of the users, and their computational tasks, are met. That problem is addressed for two of the most widely-considered classes of computational tasks in the literature, namely, indivisible tasks (binary offloading) and divisible tasks (partial offloading). This thesis begins with an exploration of the impact of the choice of multiple access scheme that is employed by the system on the total energy consumption of the users. In particular, the problem of minimizing the total energy consumption of a two-user binary offloading system is tackled under various multiple access schemes, namely time division multiple access (TDMA), sequential decoding without time sharing, independent decoding, and multiple access schemes that can exploit the full capabilities of the channel, which are referred to as full multiple access schemes (FullMA) in this thesis. Using a decomposition-based approach, closed-form solutions to the resource allocation problem are obtained. Those expressions show that by exploiting the full capabilities of the channel, a FullMA scheme can significantly reduce the total energy consumption of the users as compared to the other schemes. The closed-form expressions also show that when the channel gains of the two users are equal, the TDMA scheme can achieve the optimal energy consumption. For the case of partial offloading, an analogous analysis leads to a reduced-dimension design problem and an extension to the optimally result for TDMA. In the next step of the development, the insights obtained from the decomposition-based analysis of the two-user case are used to tackle the communication resource allocation problem for a K-user offloading system in which the users are assumed to be served over a single time slot. Based on their performance in the two-user case, FullMA and TDMA schemes are considered. The mixed-integer optimization problem that arises in the binary offloading case is addressed by employing a decomposition approach with a closed-form expression obtained for the optimal resource allocation for given offloading decisions, and a tailored pruned greedy search algorithm developed herein for the offloading decisions. By exploiting the maximum allowable latency of each individual user, the proposed algorithm is able to significantly reduce the energy consumption of the users in comparison to the existing algorithms in the literature that assume equal latency constraints for all users. Furthermore, with the closed-form optimal solution to the resource allocation problem obtained for given offloading decisions, the proposed algorithm has a significantly lower computational cost compared to the existing algorithms. In the partial offloading case, a quasi-closed- form solution is obtained for the resource allocation problem. Finally, a time-slotted signalling structure is proposed as an optimal transmission structure for a generic K-user offloading system. Furthermore, an optimal times-lotted structure that requires only K time slots is developed for a K-user offloading system that employs a FullMA scheme. The proposed time-slotted structure not only exploits the maximum latency constraint of each user, it also exploits the differences between the latency constraints of the users by taking advantage of the interference reduction that arises when a user finishes offloading. The proposed time-slotted FullMA signalling structure significantly reduces the energy consumption of the users compared to some existing methods that employ the TDMA scheme, and compared to those with FullMA, but sub-optimal single-time-slot signalling structures. Moreover, the computational cost of the proposed time-slotted algorithm is significantly lower than that of the existing algorithms in the literature. / Dissertation / Doctor of Philosophy (PhD) / The rapid increase in the number of smart devices in wireless communication networks, and the expansion in the range of computationally-intensive and latency sensitive applications that those devices are required to support, have highlighted their resource limitations in terms of energy, power, central processing unit (CPU), and memory. Mobile edge computing is a framework that provides shared computational resources at the access points of wireless networks and gives such devices the opportunity to offload (a portion of) their applications to be executed at the access points. In order to fully exploit such an opportunity when multiple devices seek to offload their applications, the available communication and computation resources must be efficiently allocated amongst those devices. The ultimate goal of this thesis is to obtain the optimal communication resource allocation in a K-user offloading system while different constraints on the devices and on the applications are satis ed. To that end, this thesis shows that the minimum energy consumption is obtained when the system exploits the full capabilities of the channel, the maximum allowable latency of each user, and the differences between the latency constraints of each user. Accordingly, this thesis proposes an optimized signalling structure and, based on that structure, low-complexity algorithms that achieve an energy-optimal resource allocation in a K-user offloading system.