In airline industry scheduling problems, the aircraft routing and the aircrew pairing problems are highly related to fueling and personnel costs. When performing aircraft routing and aircrew pairing, several objectives, such as the ground-turn around time, flow balance, transition time, number of deadheads, number of layovers, flying time, and flight duty period should be considered. It is difficult to optimize these conflicting objectives simultaneously. Many issues are yet to be solved as follows. 1. Most researches related to the aircraft routing and aircrew pairing problems use set partitioning or set covering models. Planners must (1) enumerate several possible subsets of flights, (2) assign costs, and (3) check feasibilities simultaneously. This is time-consuming since the numbers of whole subsets are exponential values to the problem size. 2. The number of enumerated subsets is usually too small to cover the whole solution space. Therefore, even if the optimal solution is found, it is just a local optimal solution of the enumerated subsets. 3. When using traditional optimization algorithms to find a combination of these subsets with minimal cost, it should be ensured that all flights should be covered exactly once. This causes the overheads of checking the number of coverage. 4. In traditional solution methods, the number of required aircrafts and crewmembers cannot be pre-specified since these numbers can only be obtained when the optimization algorithm is completed. 5. All enumerated subsets should be assigned cost values according to various objectives, such as transition time, number of deadheads, number of layovers, flying time, and flight duty period. The cost values are difficult to assign since it is highly dependent on domain knowledge, and usually nonlinear. Also, inappropriate cost values will cause bias in optimization, and ambiguity among all factors due to single objective formulation. Hence, to overcome these problems, we propose several enhancements in both formulation and the solution stages. In the formulation stage, we propose a novel permutation-based model with multiple objectives, which has the following features. 1. The proposed permutation-based model can save the overheads of pre-enumerating possible sub-solutions 2. The permutation-based model can cover the whole solution space. Hence, it has more chance to find out the global optimal solution. 3. The proposed permutation-based model can ensure that each flight can be covered exactly once to save the overheads of checking the number of coverage. 4. The proposed permutation-based model can provide a new way to pre-specify the number of aircrafts or group number of crewmembers. 5. Taking the advantage of multiobjective formulation, various objectives are considered separatively instead of assigning cost values. All objective can be considered individually even if they have different definitions of optimality or scales. In the solution stage, we apply the MOI-based MGA (MMGA) to solve the problems of aircraft routing and crew pairing. MMGA is originally proposed to solve numerical controller design problem. By using MMGA, designers can configure the ranges of solutions via adjusting an auxiliary vector of performance indices. To make MMGA more suitable for solving the aircraft routing and aircrew pairing problems, some enhancements are added, such as chromosome encoding scheme, repairing strategy, crossover, and mutation operations. This approach has following features. 1. In both aircraft routing and aircrew pairing problems, the permutation-based encoding scheme, which is the same as the formulation model, can ensure all flights be covered once. 2. Moreover, in the crew pairing problem, the sectional permutation-based encoding scheme, which divides the flights into three sections, such as earlier flights, later flights, and floating flights, can enhance MMGA to find out optimal solutions which satisfy the flight duty period objective. 3. Also, to overcome the large violations caused by random generation of candidate solutions, we use a repairing strategy, which repairs all generated solutions by reordering the sequences of flights according to departure times. 4. The sectional order-based crossover can have a more stable evolution than the widely-used partial mapped crossover. Also, it can make the newborn offspring keep the features of three sections defined in the encoding scheme. 5. Also, the sectional mutation can inherit the advantages of the widely-used reciprocal mutation and keep the features of three sections defined in the encoding scheme. In the aircraft routing problem, experiments show that MMGA can find out optimal flight schedules under the condition of sufficient aircrafts. On the other aspect, when the number of aircrafts is insufficient, planners can modify the obtained solutions by a little retiming process when the number of violations is small. In the aircrew pairing problem, experiments indicate the proposed approach can solve the aircrew pairing problem with minimal group number of crewmembers which is verified by a branch-and-bound approach. By using MMGA, the problems of aircraft routing and aircrew pairing can be solved efficiently and effectively. In other words, planners can solve these problems in a short time period instead of enumeration and feasibility checking by traditional methods. Via the proposed approach, planners can further consider more important issues, such as to suggest better schedules with lower cost and higher benefit.

Due to hierarchical sensor networks is capable to elimination extra sensing information and reduce extra communication load, it is remarkably important to increase scalability of network and prolong lifetime of network. In the paper, we focus on relay nodes of two-layered heterogeneous sensor networks. When relay nodes transmit data without scheduling, the collision probability must increase. It will cost too much for energy to re-transmission data and listening channel. To avoid extra energy consumption, we build a grid network according to RSS, and naming IP for every relay node on the grid network. Then, all leaf nodes join a certain cluster and naming IP according to RSS. Through the exclusive IP it schedule mission for TDMA. Only when relay node comes in specific slot, it wakes up to transmit or receive data, the remaining time to sleep and save power consumption. Besides, in order to balance energy consumption of backbone or non-backbone relay nodes and prolong lifetime of network, we proposal three routing protocol (DTS¡BREARBS¡BVIPOS). According to simulation results, VIPOS is the longest lifetime above them.

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Scheduling for clustered architectures involves spatial concerns (where to schedule) as well as temporal concerns (when to schedule). Various clustered VLIW configurations, connectivity types, and inter-cluster communication models present different performance trade-offs to a scheduler. The scheduler is responsible for resolving the conflicting requirements of exploiting the parallelism offered by the hardware and limiting the communication among clusters to achieve better performance. Earlier proposals for cluster scheduling fall into two main categories, viz., phase-decoupled scheduling and phase-coupled scheduling and they focus on clustered architectures which provide inter-cluster communication by an explicit inter-cluster copy operation. However, modern commercial clustered architectures provide snooping capabilities (apart from the support for inter-cluster communication using an explicit MV operation) by allowing some of the functional units to read operands from the register file of some of the other clusters without any extra delay. The phase-decoupled approach of scheduling suffers from the well known phase-ordering problem which becomes severe for such a machine model (with snooping) because communication and resource constraints are tightly coupled and thus are exposed only during scheduling. Tight integration of communication and resource constraints further requires taking into account the resource and communication requirements of other instructions ready to be scheduled in the current cycle while binding an instruction, in order to carry out effective binding. However, earlier proposals on integrated scheduling consider instructions and clusters for binding using a fixed order and thus they show different widely varying performance characteristics in terms of execution time and code size. Other shortcomings of earlier integrated algorithms (that lead to suboptimal cluster scheduling decisions) are due to non-consideration of future communication (that may arise due to a binding) and functional unit binding. In this thesis, we propose a pragmatic scheme and also a generic graph matching based framework for cluster scheduling based on a generic and realistic clustered machine model. The proposed scheme effectively utilizes the exact knowledge of available communication slots, functional units, and load on different clusters as well as future resource and communication requirements known only at schedule time to attain significant performance improvement without code size penalty over earlier algorithms. The proposed graph matching based framework for cluster scheduling resolves the phase-ordering and fixed-ordering problem associated with scheduling on clustered VLIW architectures. The framework provides a mechanism to exploit the slack of instructions by dynamically varying the freedom available in scheduling an instruction and hence the cost of scheduling an instruction using different alternatives to reduce the inter-cluster communication. An experimental evaluation of the proposed framework and some of the earlier proposals is presented in the context of a state-of-art commercial clustered architecture.

With multiprocessors and multicore processors becoming ubiquitous, focus has shifted from research on uniprocessors to that on multiprocessors. Results derived for the uniprocessor case unfortunately do not always directly extend to the multiprocessor case in a straightforward manner. This necessitates a paradigm shift in the approach used to design and analyse the behaviour of such processors. In the case of Real-time systems, that is, systems characterised by explicit timing constraints, analysis and performance guarantees are more important, as failure is unacceptable. Scheduling algorithms used in Real-time systems have to be carefully designed as the performance of the system depends critically on them. Efficient tests for determining if a set of tasks can be feasibly scheduled on such a computing system using a particular scheduling algorithm thus assumes importance. Traditionally, the ‘task utilization’ parameter has been used for devising such tests. Utilization based tests for Earliest Deadline First(EDF) and Rate Monotonic(RM) scheduling algorithms are known and are well understood for uniprocessor systems. In our work, we derive limits on similar bounds for the multiprocessor case. Our work diners from previous literature in that we explore the case when the individual processors constituting the multiprocessor need not be identical. Each processor in such a system is characterised by a capacity, or speed, and the time taken by a task to execute on a processor is inversely proportional to its speed. Such instances may arise during system upgradation, when faster processors may be added to the system, making it a non-identical multiprocessor, or during processor design, when the different cores on the chip may have different processing power to handle dynamic workloads. We derive results for the partitioned paradigm of multiprocessor scheduling, that is, when tasks are partitioned among the processors, and interprocessor migration after a part of execution is completed is not allowed. Results are derived for both fixed priority algorithms(RM)and dynamic priority algorithms (EDF) used on individual processors. A maximum and minimum limit on the bounds for a ‘greedy’ class of algorithms are established, since the actual value of the bound depends on the algorithm that allocates the tasks. We also derive the utilization bound of an algorithm whose bound is close to the upper limit in both cases. We find that an expression for the utilization bound can be obtained when EDF is used as the uniprocessor scheduling algorithm, but when RM is the uniprocessor scheduling algorithm,an O(mn) algorithm is required to find the utilization bound, where m is the number of tasks in the system and n is the number of processors. Knowledge of such bounds allows us to carry out very fast schedulability tests, although we have the limitation that the tests are sufficient but not necessary to ensure schedulability. We also compare the value of the bounds with those achievable in ‘equivalent’ identical multiprocessor systems and find that the performance guarantees provided by the non-identical multiprocessor system are far higher than those offered by the equivalent identical system.

Thesis (Ph. D.)--University of Missouri-Columbia, 1999. / Typescript. Vita. Includes bibliographical references (leaves 139-149). Also available on the Internet.

Thesis (Ph. D.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 68-70) and index.

Thesis (M.Ed.)--Memorial University of Newfoundland, 2001. / Bibliography: leaves 75-82.

Thesis (Ph. D.)--University of Missouri-Columbia, 1999. / Typescript. Vita. Includes bibliographical references (leaves 139-149). Also available on the Internet.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 79-85). Also available in electronic version. Access restricted to campus users.

Thesis (M.S.)--California Polytechnic State University, 2010. / Mode of access: Internet. Title from PDF title page; viewed on March 19, 2010. Major professor: Lois Brady. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "March 2010." Includes bibliographical references (p. 71).