Carrier Aggregation in Multi-Beam High Throughput Satellite Systems

Carrier Aggregation (CA) is an integral part of current terrestrial networks. Its ability to enhance the peak data rate, to efficiently utilize the limited available spectrum resources and to satisfy the demand for data-hungry applications has drawn large attention from different wireless network communities. Given the benefits of CA in the terrestrial wireless environment, it is of great interest to analyze and evaluate the potential impact of CA in the satellite domain. In this paper, we study CA in multibeam high throughput satellite systems. We consider both inter-transponder and intra-transponder CA at the satellite payload level of the communication stack, and we address the problem of carrier-user assignment assuming that multiple users can be multiplexed in each carrier. The transmission parameters of different carriers are generated considering the transmission characteristics of carriers in different transponders. In particular, we propose a flexible carrier allocation approach for a CA-enabled multibeam satellite system targeting a proportionally fair user demand satisfaction. Simulation results and analysis shed some light on this rather unexplored scenario and demonstrate the feasibility of the CA in satellite communication systems

Market-based transmission congestion management using extended optimal power flow techniques

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 5/9/2001This thesis describes research into the problem of transmission congestion management. The causes, remedies, pricing methods, and other issues of transmission congestion are briefly reviewed. This research is to develop market-based approaches to cope with transmission congestion in real-time, short-run and long-run efficiently, economically and fairly. Extended OPF techniques have been playing key roles in many aspects of electricity markets. The Primal-Dual Interior Point Linear Programming and Quadratic Programming are applied to solve various optimization problems of congestion management proposed in the thesis. A coordinated real-time optimal dispatch method for unbundled electricity markets is proposed for system balancing and congestion management. With this method, almost all the possible resources in different electricity markets, including operating reserves and bilateral transactions, can be used to eliminate the real-time congestion according to their bids into the balancing market. Spot pricing theory is applied to real-time congestion pricing. Under the same framework, a Lagrangian Relaxation based region decomposition OPF algorithm is presented to deal with the problems of real-time active power congestion management across multiple regions. The inter/intra-regional congestion can be relieved without exchanging any information between regional ISOs but the Lagrangian Multipliers. In day-ahead spot market, a new optimal dispatch method is proposed for congestion and price risk management, particularly for bilateral transaction curtailment. Individual revenue adequacy constraints, which include payments from financial instruments, are involved in the original dispatch problem. An iterative procedure is applied to solve this special optimization problem with both primal and dual variables involved in its constraints. An optimal Financial Transmission Rights (FTR) auction model is presented as an approach to the long-term congestion management. Two types of series F ACTS devices are incorporated into this auction problem using the Power Injection Model to maximize the auction revenue. Some new treatment has been done on TCSC's operating limits to keep the auction problem linear

Energy-Aware Scheduling for Streaming Applications

Streaming applications have become increasingly important and widespread,with application domains ranging from embedded devices to server systems.Traditionally, researchers have been focusing on improving the performanceof streaming applications to achieve high throughput and low response time.However, increasingly more attention is being shifted topower/performance trade-offbecause power consumption has become a limiting factor on system designas integrated circuits enter the realm of nanometer technology.This work addresses the problem of scheduling a streaming application(represented by a task graph)with the goal of minimizing its energy consumptionwhile satisfying its two quality of service (QoS) requirements,namely, throughput and response time.The available power management mechanisms are dynamic voltage scaling (DVS),which has been shown to be effective in reducing dynamic power consumption, andvary-on/vary-off, which turns processors on and off to save static power consumption.Scheduling algorithms are proposed for different computing platforms (uniprocessor and multiprocessor systems),different characteristics of workload (deterministic and stochastic workload),and different types of task graphs (singleton and general task graphs).Both continuous and discrete processor power models are considered.The highlights are a unified approach for obtaining optimal (or provably close to optimal)uniprocessor DVS schemes for various DVS strategies anda novel multiprocessor scheduling algorithm that exploits the differencebetween the two QoS requirements to perform processor allocation,task mapping, and task speedscheduling simultaneously

Dual Data Rate Network-on-Chip Architectures

Networks-on-Chip (NoCs) are becoming increasing important for the performance of modern multi-core systems-on-chip. The performance of current NoCs is limited, among others, by two factors: their limited clock frequency and long router pipeline. The clock frequency of a network defines the limits of its saturation throughput. However, for high throughput routers, clock is constrained by the control logic (for virtual channel and switch allocation) whereas the datapath (crossbar switch and links) possesses significant slack. This slack in the datapath wastes network throughput potential. Secondly, routers require flits to go through a large number of pipeline stages increasing packet latency at low traffic loads. These stages include router resource allocation, switch traversal (ST) and link traversal (LT). The allocation stages are used to manage contention among flits attempting to simultaneously access switch and links, and the ST stage is needed to change the routing dimension. In some cases, these stages are not needed and then requiring flits to go through them increases packet latency. The aim of this thesis is to improve NoC performance, in terms of network throughput, by removing the slack in the router datapath, and in terms of average packet latency, by enabling incoming flits to bypass, when possible, allocation and ST stages. More precisely, this thesis introduces Dual Data-Rate (DDR) NoC architectures which exploit the slack present in the NoC datapath to operate it at DDR. This requires a clock with period twice the datapath delay and removes the control logic from the critical path. DDR datapaths enable throughput higher than existing single data-rate (SDR) networks where the clock period is defined by the control logic. Additionally, this thesis supplements DDR NoC architectures with varying levels of pipeline stage bypassing capabilities to reduce low-load packet latency. In order to avoid complex logic required for bypassing from all inputs to all outputs, this thesis implements and evaluates a simplified bypassing approach. DDR NoC routers support bypassing of the allocation stage for flits propagating an in-network straight hop (i.e. East to West, North to South and vice versa) and when entering or exiting the network. Disabling bypassing during XY-turns limits its benefits, but, for most routing algorithms under low traffic loads, flits encounter at most one XY-turn on their way to the destination. Bypassing allocation stage enables incoming flits to directly initiate ST, when required conditions are met, and propagate at one cycle per hop. Furthermore, DDR NoC routers allow flits to bypass the ST stage when propagating a straight hop from the head of a specific input VC. Restricting ST bypassing from a specific VC further simplifies check logic to have clock period defined by datapath delays. Bypassing ST requires dedicated bypass paths from non-local input ports to opposite output ports. It enables flits to propagate half a cycle per hop. This thesis shows that compared to current state-of-the-art SDR NoCs, operating router’s datapath at DDR improves throughput by up to 20%. Adding to a DDR NoC an allocation bypassing mechanism for straight hops reduces its packet latency by up to 45%, while maintaining the DDR throughput advantage. Enhancing allocation bypassing to include flits entering and exiting the network further reduces latency by another 24%. Finally, adding ST bypassing further reduces latency by another 32%. Overall, DDR NoCs offer up to 40% lower latency and about 20% higher throughput compared to the SDR networks

Dynamic Resource Management of Network-on-Chip Platforms for Multi-stream Video Processing

This thesis considers resource management in the context of parallel multiple video stream decoding, on multicore/many-core platforms. Such platforms have tens or hundreds of on-chip processing elements which are connected via a Network-on-Chip (NoC). Inefficient task allocation configurations can negatively affect the communication cost and resource contention in the platform, leading to predictability and performance issues. Efficient resource management for large-scale complex workloads is considered a challenging research problem; especially when applications such as video streaming and decoding have dynamic and unpredictable workload characteristics. For these type of applications, runtime heuristic-based task mapping techniques are required. As the application and platform size increase, decentralised resource management techniques are more desirable to overcome the reliability and performance bottlenecks in centralised management. In this work, several heuristic-based runtime resource management techniques, targeting real-time video decoding workloads are proposed. Firstly, two admission control approaches are proposed; one fully deterministic and highly predictable; the other is heuristic-based, which balances predictability and performance. Secondly, a pair of runtime task mapping schemes are presented, which make use of limited known application properties, communication cost and blocking-aware heuristics. Combined with the proposed deterministic admission controller, these techniques can provide strict timing guarantees for hard real-time streams whilst improving resource usage. The third contribution in this thesis is a distributed, bio-inspired, low-overhead, task re-allocation technique, which is used to further improve the timeliness and workload distribution of admitted soft real-time streams. Finally, this thesis explores parallelisation and resource management issues, surrounding soft real-time video streams that have been encoded using complex encoding tools and modern codecs such as High Efficiency Video Coding (HEVC). Properties of real streams and decoding trace data are analysed, to statistically model and generate synthetic HEVC video decoding workloads. These workloads are shown to have complex and varying task dependency structures and resource requirements. To address these challenges, two novel runtime task clustering and mapping techniques for Tile-parallel HEVC decoding are proposed. These strategies consider the workload communication to computation ratio and stream-specific characteristics to balance predictability improvement and communication energy reduction. Lastly, several task to memory controller port assignment schemes are explored to alleviate performance bottlenecks, resulting from memory traffic contention

A survey on scheduling and mapping techniques in 3D Network-on-chip

Network-on-Chips (NoCs) have been widely employed in the design of multiprocessor system-on-chips (MPSoCs) as a scalable communication solution. NoCs enable communications between on-chip Intellectual Property (IP) cores and allow those cores to achieve higher performance by outsourcing their communication tasks. Mapping and Scheduling methodologies are key elements in assigning application tasks, allocating the tasks to the IPs, and organising communication among them to achieve some specified objectives. The goal of this paper is to present a detailed state-of-the-art of research in the field of mapping and scheduling of applications on 3D NoC, classifying the works based on several dimensions and giving some potential research directions