A typical E-commerce system that is deployed on the Internet has multiple layers that include Web users, Web servers, application servers, and a database server. As the system use and user request frequency increase, Web/application servers can be scaled up by replication. A load balancing proxy can be used to route user requests to individual machines that perform the same functionality. <br><br>To address the increasing workload while avoiding replicating the database server, various dynamic caching policies have been proposed to reduce the database workload in E-commerce systems. However, the nature of the changes seen by the database server as a result of dynamic caching remains unknown. A good understanding of this change is fundamental for tuning a database server to get better performance. <br><br> In this study, the TPC-W (a transactional Web E-commerce benchmark) workloads on a database server are characterized under two different dynamic caching mechanisms, which are generalized and implemented as query-result cache and table cache. The characterization focuses on response time, CPU computation, buffer pool references, disk I/O references, and workload classification. <br><br>This thesis combines a variety of analysis techniques: simulation, real time measurement and data mining. The experimental results in this thesis reveal some interesting effects that the dynamic caching has on the database server workload characteristics. The main observations include: (a) dynamic cache can considerably reduce the CPU usage of the database server and the number of database page references when it is heavily loaded; (b) dynamic cache can also reduce the database reference locality, but to a smaller degree than that reported in file servers. The data classification results in this thesis show that with dynamic cache, the database server sees TPC-W profiles more like on-line transaction processing workloads.

Mobile devices have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. However, the most significant step in the evolution of mobile devices was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity such as email, web browsers and maybe most importantly smart/rich clients. Being able to host smart clients allows the users of mobile devices to seamlessly access the Information Technology (IT) resources of their organizations. <p>One increasingly popular way of enabling access to IT resources is by using Web Services (WS). This trend has been aided by the rapid availability of WS packages/tools, most notably the efforts of the Apache group and Integrated Development Environment (IDE) vendors. But the widespread use of WS raises questions for users of mobile devices such as laptops or PDAs; how and if they can participate in WS. Unlike their wired counterparts (desktop computers and servers) they rely on a wireless network that is characterized by low bandwidth and unreliable connectivity.<p>The aim of this thesis is to enable mobile devices to host Web Services consumers. It introduces a Model-Driven Dual Caching (MDDC) approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth.

To build a shared-memory programming model for FPGAs, a fast and highly parallel method of accessing the shared-memory is required. This thesis presents a first look at how to implement a coherent caching system in an FPGA. The coherent caching system consists of multiple distributed caches that implement the write-once coherence protocol, allowing efficient access to system memory while simplifying the user programming model. Several test applications are used to verify functionality, and assess performance of the current system. Results show that with a processor-based system, some applications could benefit from improvements to the coherence system, but for many applications, the current system is sufficient. However, the current coherent caching system is not sufficient for most hardware core based systems, because the faster memory accesses quickly saturate shared system resources. As well, the performance of distributed-memory systems currently surpasses that of the coherent caching system. Performance results are promising, and given the potential for improvements, future work on this system is warranted.

Information delivery via the web has become very popular. Along with a growing user population, systems increasingly are supporting content that changes frequently, personalised information, and differentiation and choice. This thesis is concerned with the design and evaluation of resource management strategies for such systems. An architecture that provides scalability through caching proxies is considered. When a cached page is updated at the server, the cached copy may become stale if the server is not able to transmit the update to the proxies immediately. From the perspective of the server, resources are required to transmit updates for cached pages and to process requests for pages that are not cached. Analytic results on how the available resources should be managed in order to minimise staleness-related cost are presented. An efficient algorithm that the server can use to determine the set of pages that should be cached and a policy for transmitting updates for these pages are also presented. We then apply these results to page fragments, a technique that can provide increased efficiency for delivery of personalised pages.

This thesis discusses cache oblivious data structures. These are structures which have good caching characteristics without knowing Z, the size of the cache, or L, the length of a cache line. Since the structures do not require these details for good performance they are portable across caching systems. Another advantage of such structures isthat the caching results hold for every level of cache within a multilevel cache. Two simple data structures are studied; the array used for binary search and the linear list. As well as being cache oblivious, the structures presented in this thesis are space efficient, requiring little additional storage. We begin the discussion with a layout for a search tree within an array. This layout allows Searches to be performed in O(log n) time and in O(log n/log L) (the optimal number) cache misses. An algorithm for building this layout from a sorted array in linear time is given. One use for this layout is a heap-like implementation of the priority queue. This structure allows Inserts, Heapifies and ExtractMaxes in O(log n) time and O(log nlog L) cache misses. A priority queue using this layout can be builtfrom an unsorted array in linear time. Besides the n spaces required to hold the data, this structure uses a constant amount of additional storage. The cache oblivious linear list allows scans of the list taking Theta(n) time and incurring Theta(n/L) (the optimal number) cache misses. The running time of insertions and deletions is not constant, however it is sub-polynomial. This structure requires e*n additional storage, where e is any constant greater than zero.

Information delivery via the web has become very popular. Along with a growing user population, systems increasingly are supporting content that changes frequently, personalised information, and differentiation and choice. This thesis is concerned with the design and evaluation of resource management strategies for such systems. An architecture that provides scalability through caching proxies is considered. When a cached page is updated at the server, the cached copy may become stale if the server is not able to transmit the update to the proxies immediately. From the perspective of the server, resources are required to transmit updates for cached pages and to process requests for pages that are not cached. Analytic results on how the available resources should be managed in order to minimise staleness-related cost are presented. An efficient algorithm that the server can use to determine the set of pages that should be cached and a policy for transmitting updates for these pages are also presented. We then apply these results to page fragments, a technique that can provide increased efficiency for delivery of personalised pages.

This thesis discusses cache oblivious data structures. These are structures which have good caching characteristics without knowing Z, the size of the cache, or L, the length of a cache line. Since the structures do not require these details for good performance they are portable across caching systems. Another advantage of such structures isthat the caching results hold for every level of cache within a multilevel cache. Two simple data structures are studied; the array used for binary search and the linear list. As well as being cache oblivious, the structures presented in this thesis are space efficient, requiring little additional storage. We begin the discussion with a layout for a search tree within an array. This layout allows Searches to be performed in O(log n) time and in O(log n/log L) (the optimal number) cache misses. An algorithm for building this layout from a sorted array in linear time is given. One use for this layout is a heap-like implementation of the priority queue. This structure allows Inserts, Heapifies and ExtractMaxes in O(log n) time and O(log nlog L) cache misses. A priority queue using this layout can be builtfrom an unsorted array in linear time. Besides the n spaces required to hold the data, this structure uses a constant amount of additional storage. The cache oblivious linear list allows scans of the list taking Theta(n) time and incurring Theta(n/L) (the optimal number) cache misses. The running time of insertions and deletions is not constant, however it is sub-polynomial. This structure requires e*n additional storage, where e is any constant greater than zero.

This thesis is concerned with caching algorithms. We investigate three variations of the caching problem: web caching in the Torng framework, relative competitiveness and caching with request reordering. <br /><br /> In the first variation we define different cost models involving page sizes and page costs. We also present the Torng cost framework introduced by Torng in [29]. Next we analyze the competitive ratio of online deterministic marking algorithms in the BIT cost model combined with the Torng framework. We show that given some specific restrictions on the set of possible request sequences, any marking algorithm is 2-competitive. <br /><br /> The second variation consists in using the relative competitiveness ratio on an access graph as a complexity measure. We use the concept of access graphs introduced by Borodin [11] to define our own concept of relative competitive ratio. We demonstrate results regarding the relative competitiveness of two cache eviction policies in both the basic and the Torng framework combined with the CLASSICAL cost model. <br /><br /> The third variation is caching with request reordering. Two reordering models are defined. We prove some important results about the value of a move and number of orderings, then demonstrate results about the approximation factor and competitive ratio of offline and online reordering schemes, respectively.

A typical E-commerce system that is deployed on the Internet has multiple layers that include Web users, Web servers, application servers, and a database server. As the system use and user request frequency increase, Web/application servers can be scaled up by replication. A load balancing proxy can be used to route user requests to individual machines that perform the same functionality. <br><br>To address the increasing workload while avoiding replicating the database server, various dynamic caching policies have been proposed to reduce the database workload in E-commerce systems. However, the nature of the changes seen by the database server as a result of dynamic caching remains unknown. A good understanding of this change is fundamental for tuning a database server to get better performance. <br><br> In this study, the TPC-W (a transactional Web E-commerce benchmark) workloads on a database server are characterized under two different dynamic caching mechanisms, which are generalized and implemented as query-result cache and table cache. The characterization focuses on response time, CPU computation, buffer pool references, disk I/O references, and workload classification. <br><br>This thesis combines a variety of analysis techniques: simulation, real time measurement and data mining. The experimental results in this thesis reveal some interesting effects that the dynamic caching has on the database server workload characteristics. The main observations include: (a) dynamic cache can considerably reduce the CPU usage of the database server and the number of database page references when it is heavily loaded; (b) dynamic cache can also reduce the database reference locality, but to a smaller degree than that reported in file servers. The data classification results in this thesis show that with dynamic cache, the database server sees TPC-W profiles more like on-line transaction processing workloads.

Mobile devices have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. However, the most significant step in the evolution of mobile devices was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity such as email, web browsers and maybe most importantly smart/rich clients. Being able to host smart clients allows the users of mobile devices to seamlessly access the Information Technology (IT) resources of their organizations. <p>One increasingly popular way of enabling access to IT resources is by using Web Services (WS). This trend has been aided by the rapid availability of WS packages/tools, most notably the efforts of the Apache group and Integrated Development Environment (IDE) vendors. But the widespread use of WS raises questions for users of mobile devices such as laptops or PDAs; how and if they can participate in WS. Unlike their wired counterparts (desktop computers and servers) they rely on a wireless network that is characterized by low bandwidth and unreliable connectivity.<p>The aim of this thesis is to enable mobile devices to host Web Services consumers. It introduces a Model-Driven Dual Caching (MDDC) approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth.