The limited energy and computing power of small smart devices restricts their ability to support a wide range of applications, especially those needing quick responses. Mobile edge computing offers a potential solution by providing computing resources at the network access points that can be shared by the devices. This enables the devices to offload some of their computational tasks to the access points. To make this work well for multiple devices, we need to judiciously allocate the available communication and computing resources among the devices. The main focus of this thesis is on (near) optimal resource allocation in a K-user offloading system that employs the time division multiple access (TDMA) scheme. In this thesis, we develop effective algorithms for the resource allocation problem that aim to minimize the overall (cost of the) energy that the devices consume in completing their computational tasks within the specified deadlines while respecting the devices' constraints. This problem is tackled for tasks that cannot be divided and hence the system must make a binary decision as to whether or not a task should be offloaded. This implies the need to develop an effective decision-making algorithm to identify a suitable group of devices for offloading. This thesis commences by developing efficient communication resource algorithms that incorporate the impact of integer finite block length in low-latency computational offloading systems with reserved computing resources. In particular, it addresses the challenge of minimizing total energy consumption in a binary offloading scenario involving K users. The approach considers different approximations of the fundamental rate limit in the finite block length regime, departing from the conventional asymptotic rate limits developed by Shannon. Two such alternatives, namely the normal approximation and the SNR-gap approximation, are explored. A decomposition approach is employed, dividing the problem into an inner component that seeks an optimal solution for the communication resource allocation within a defined set of offloading devices, and an outer component aimed at identifying a suitable set of offloading devices. Given the finiteness of the block length and its integer nature, various relaxation techniques are employed to determine an appropriate communication resource allocation. These include incremental and independent roundings, alongside an extended search that utilizes randomization-based methods in both rounding schemes. The findings reveal that incremental randomized rounding, when applied to the normal approximation of the rate limits, enhances system performance in terms of reducing the energy consumption of the offloading users. Furthermore, customized pruned greedy search techniques for selecting the offloading devices efficiently generate good decisions. Indeed, the proposed approach outperforms a number of existing approaches. In the second contribution, we develop efficient algorithms that address the challenge of jointly allocating both computation and communication resources in a binary offloading system. We employ a similar decomposition methodology as in the previous work to perform the decision-making, but this is now done along with joint computation and communication resource allocation. For the inner resource allocation problem, we divide the problem into two components: determining the allocation of computation resources and the optimal allocation of communication resources for the given allocation of computation resources. The allocation of the computation resources implicitly determines a suitable order for data transmission, which facilitates the subsequent optimal allocation of the communication resources. In this thesis, we introduce two heuristic approaches for allocating the computation resources. These approaches sequentially maximize the allowable transmission time for the devices in sequence, starting from the largest leading to a reduction in total offloading energy. We demonstrate that the proposed heuristics substantially lower the computational burden associated with solving the joint computation--communication resource allocation problem while maintaining a low total energy. In particular, its use results in substantially lower energy consumption than other simple heuristics. Additionally, the heuristics narrow the energy gap in comparison to a fictitious scenario in which each task has access to the whole computation resource without the need for sharing. / Thesis / Master of Applied Science (MASc)

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.

No description available.

No description available.

No description available.

No description available.

No description available.

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)