Benchmark-based Page Replacement (BBPR) Strategy: A New Web Cache Page Replacement Strategy

World Wide Web caching is widely used through today's Internet. When correctly deployed, Web caching systems can lead to significant bandwidth savings, network load reduction, server load balancing, and higher content availability. A document replacement algorithm that can lower retrieval latency and yield high hit ratio is the key to the effectiveness of proxy caches. More than twenty cache algorithms have been employed in academic studies and in corporate communities as well. But there are some drawbacks in the existing replacement algorithms. To overcome these shortcomings, we developed a new page replacement strategy named as Benchmark-Based Page Replacement (BBPR) strategy, in which a HTTP benchmark is used as a tool to evaluate the current network load and the server load. By our simulation model, the BBPR strategy shows better performance than the LRU (Least Recently Used) method, which is the most commonly used algorithm. The tradeoff is a reduced hit ratio. Slow pages benefit from BBPR

Variable QoS from Shared Web Caches: User-Centered Design and Value-Sensitive Replacement

Due to differences in server capacity, external bandwidth and client demand, some Web servers value cache hits more than others. Assuming that a shared cache knows the extent to which different servers value hits, it may employ a value-sensitive replacement policy in order to generate maximum aggregate value for servers. we consider both the prediction and value aspects of this problem and introduce a novel value-sensitive LFU/LRU hybrid which biases the allocation of cache space toward documents whose origin servers value caching most highly. We compare our algorithm with others from the Web caching literature and discuss from an economic standpoint the problems associated with obtaining servers' private valuation information.http://deepblue.lib.umich.edu/bitstream/2027.42/50430/1/varp.pd

Resource Management in Multi-Access Edge Computing (MEC)

This PhD thesis investigates the effective ways of managing the resources of a Multi-Access Edge Computing Platform (MEC) in 5th Generation Mobile Communication (5G) networks. The main characteristics of MEC include distributed nature, proximity to users, and high availability. Based on these key features, solutions have been proposed for effective resource management. In this research, two aspects of resource management in MEC have been addressed. They are the computational resource and the caching resource which corresponds to the services provided by the MEC. MEC is a new 5G enabling technology proposed to reduce latency by bringing cloud computing capability closer to end-user Internet of Things (IoT) and mobile devices. MEC would support latency-critical user applications such as driverless cars and e-health. These applications will depend on resources and services provided by the MEC. However, MEC has limited computational and storage resources compared to the cloud. Therefore, it is important to ensure a reliable MEC network communication during resource provisioning by eradicating the chances of deadlock. Deadlock may occur due to a huge number of devices contending for a limited amount of resources if adequate measures are not put in place. It is crucial to eradicate deadlock while scheduling and provisioning resources on MEC to achieve a highly reliable and readily available system to support latency-critical applications. In this research, a deadlock avoidance resource provisioning algorithm has been proposed for industrial IoT devices using MEC platforms to ensure higher reliability of network interactions. The proposed scheme incorporates Banker’s resource-request algorithm using Software Defined Networking (SDN) to reduce communication overhead. Simulation and experimental results have shown that system deadlock can be prevented by applying the proposed algorithm which ultimately leads to a more reliable network interaction between mobile stations and MEC platforms. Additionally, this research explores the use of MEC as a caching platform as it is proclaimed as a key technology for reducing service processing delays in 5G networks. Caching on MEC decreases service latency and improve data content access by allowing direct content delivery through the edge without fetching data from the remote server. Caching on MEC is also deemed as an effective approach that guarantees more reachability due to proximity to endusers. In this regard, a novel hybrid content caching algorithm has been proposed for MEC platforms to increase their caching efficiency. The proposed algorithm is a unification of a modified Belady’s algorithm and a distributed cooperative caching algorithm to improve data access while reducing latency. A polynomial fit algorithm with Lagrange interpolation is employed to predict future request references for Belady’s algorithm. Experimental results show that the proposed algorithm obtains 4% more cache hits due to its selective caching approach when compared with case study algorithms. Results also show that the use of a cooperative algorithm can improve the total cache hits up to 80%. Furthermore, this thesis has also explored another predictive caching scheme to further improve caching efficiency. The motivation was to investigate another predictive caching approach as an improvement to the formal. A Predictive Collaborative Replacement (PCR) caching framework has been proposed as a result which consists of three schemes. Each of the schemes addresses a particular problem. The proactive predictive scheme has been proposed to address the problem of continuous change in cache popularity trends. The collaborative scheme addresses the problem of cache redundancy in the collaborative space. Finally, the replacement scheme is a solution to evict cold cache blocks and increase hit ratio. Simulation experiment has shown that the replacement scheme achieves 3% more cache hits than existing replacement algorithms such as Least Recently Used, Multi Queue and Frequency-based replacement. PCR algorithm has been tested using a real dataset (MovieLens20M dataset) and compared with an existing contemporary predictive algorithm. Results show that PCR performs better with a 25% increase in hit ratio and a 10% CPU utilization overhead

Optimization and Evaluation of Service Speed and Reliability in Modern Caching Applications

The performance of caching systems in general, and Internet caches in particular, is evaluated by means of the user-perceived service speed, reliability of downloaded content, and system scalability. In this dissertation, we focus on optimizing the speed of service, as well as on evaluating the reliability and quality of data sent to users. In order to optimize the service speed, we seek optimal replacement policies in the first part of the dissertation, as it is well known that download delays are a direct product of document availability at the cache; in demand-driven caches, the cache content is completely determined by the cache replacement policy. In the literature, many ad-hoc policies that utilize document sizes, retrieval latency, probability of references, and temporal locality of requests, have been proposed. However, the problem of finding optimal policies under these factors has not been pursued in any systematic manner. Here, we take a step in that direction: Still under the Independent Reference Model, we show that a simple Markov stationary policy minimizes the long-run average metric induced by non-uniform documents under optional cache replacement. We then use this result to propose a framework for operating caches under multiple performance metrics, by solving a constrained caching problem with a single constraint. The second part of the dissertation is devoted to studying data reliability and cache consistency issues: A cache object is termed consistent if it is identical to the master document at the origin server, at the time it is served to users. Cached objects become stale after the master is modified, and stale copies remain served to users until the cache is refreshed, subject to network transmit delays. However, the performance of Internet consistency algorithms is evaluated through the cache hit rate and network traffic load that do not inform on data staleness. To remedy this, we formalize a framework and the novel hit* rate measure, which captures consistent downloads from the cache. To demonstrate this new methodology, we calculate the hit and hit* rates produced by two TTL algorithms, under zero and non-zero delays, and evaluate the hit and hit* rates in applications

Optimization inWeb Caching: Cache Management, Capacity Planning, and Content Naming

Caching is fundamental to performance in distributed information retrieval systems such as the World Wide Web. This thesis introduces novel techniques for optimizing performance and cost-effectiveness in Web cache hierarchies. When requests are served by nearby caches rather than distant servers, server loads and network traffic decrease and transactions are faster. Cache system design and management, however, face extraordinary challenges in loosely-organized environments like the Web, where the many components involved in content creation, transport, and consumption are owned and administered by different entities. Such environments call for decentralized algorithms in which stakeholders act on local information and private preferences. In this thesis I consider problems of optimally designing new Web cache hierarchies and optimizing existing ones. The methods I introduce span the Web from point of content creation to point of consumption: I quantify the impact of content-naming practices on cache performance; present techniques for variable-quality-of-service cache management; describe how a decentralized algorithm can compute economically-optimal cache sizes in a branching two-level cache hierarchy; and introduce a new protocol extension that eliminates redundant data transfers and allows “dynamic” content to be cached consistently. To evaluate several of my new methods, I conducted trace-driven simulations on an unprecedented scale. This in turn required novel workload measurement methods and efficient new characterization and simulation techniques. The performance benefits of my proposed protocol extension are evaluated using two extraordinarily large and detailed workload traces collected in a traditional corporate network environment and an unconventional thin-client system. My empirical research follows a simple but powerful paradigm: measure on a large scale an important production environment’s exogenous workload; identify performance bounds inherent in the workload, independent of the system currently serving it; identify gaps between actual and potential performance in the environment under study; and finally devise ways to close these gaps through component modifications or through improved inter-component integration. This approach may be applicable to a wide range of Web services as they mature.Ph.D.Computer Science and EngineeringUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/90029/1/kelly-optimization_web_caching.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/90029/2/kelly-optimization_web_caching.ps.bz

Model-driven dual caching For nomadic service-oriented architecture clients

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. 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.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

Adaptive and secured resource management in distributed and Internet systems

The effectiveness of computer system resource management has been always determined by two major factors: (1) workload demands and management objectives, (2) the updates of the computer technology. These two factors are dynamically changing, and resource management systems must be timely adaptive to the changes. This dissertation attempts to address several important and related resource management issues.;We first study memory system utilization in centralized servers by improving memory performance of sorting algorithms, which provides fundamental understanding on memory system organizations and its performance optimizations for data-intensive workloads. to reduce different types of cache misses, we restructure the mergesort and quicksort algorithms by integrating tiling, padding, and buffering techniques and by repartitioning the data set. Our study shows substantial performance improvements from our new methods.;We have further extended the work to improve load sharing for utilizing global memory resources in distributed systems. Aiming at reducing the memory resource contention caused by page faults and I/O activities, we have developed and examined load sharing policies by considering effective usage of global memory in addition to CPU load balancing in both homogeneous and heterogeneous clusters.;Extending our research from clusters to Internet systems, we have further investigated memory and storage utilizations in Web caching systems. We have proposed several novel management schemes to restructure and decentralize the existing caching system by exploiting data locality at different levels of the global memory hierarchy and by effectively sharing data objects among the clients and their proxy caches.;Data integrity and communication anonymity issues are raised from our decentralized Web caching system design, which are also security concerns for general peer-to-peer systems. We propose an integrity protocol to ensure data integrity, and several protocols to achieve mutual communication anonymity between an information requester and a provider.;The potential impact and contributions of this dissertation are briefly stated as follows: (1) two major research topics identified in this dissertation are fundamentally important for the growth and development of information technology, and will continue to be demanding topics for a long term. (2) Our proposed cache-effective sorting methods bridge a serious gap between analytical complexity of algorithms and their execution complexity in practice due to the increasingly deep memory hierarchy in computer systems. This approach can also be used to improve memory performance at different levels of the memory hierarchy, such as I/O and file systems. (3) Our load sharing principle of giving a high priority to the requests of data accesses in memory and I/Os timely adapts the technology changes and effectively responds to the increasing demand of data-intensive applications. (4) Our proposed decentralized Web caching framework and its resource management schemes present a comprehensive case study to examine the P2P model. Our results and experiences can be used for related and further studies in distributed computing. (5) The proposed data integrity and communication anonymity protocols address limits and weaknesses of existing ones, and place a solid foundation for us to continue our work in this important area