An enhanced dynamic replica creation and eviction mechanism in data grid federation environment

Data Grid Federation system is an infrastructure that connects several grid systems, which facilitates sharing of large amount of data, as well as storage and computing resources. The existing mechanisms on data replication focus on finding file values based on the number of files access in deciding which file to replicate, and place new replicas on locations that provide minimum read cost. DRCEM finds file values based on logical dependencies in deciding which file to replicate, and allocates new replicas on locations that provide minimum replica placement cost. This thesis presents an enhanced data replication strategy known as Dynamic Replica Creation and Eviction Mechanism (DRCEM) that utilizes the usage of data grid resources, by allocating appropriate replica sites around the federation. The proposed mechanism uses three schemes: 1) Dynamic Replica Evaluation and Creation Scheme, 2) Replica Placement Scheme, and 3) Dynamic Replica Eviction Scheme. DRCEM was evaluated using OptorSim network simulator based on four performance metrics: 1) Jobs Completion Times, 2) Effective Network Usage, 3) Storage Element Usage, and 4) Computing Element Usage. DRCEM outperforms ELALW and DRCM mechanisms by 30% and 26%, in terms of Jobs Completion Times. In addition, DRCEM consumes less storage compared to ELALW and DRCM by 42% and 40%. However, DRCEM shows lower performance compared to existing mechanisms regarding Computing Element Usage, due to additional computations of files logical dependencies. Results revealed better jobs completion times with lower resource consumption than existing approaches. This research produces three replication schemes embodied in one mechanism that enhances the performance of Data Grid Federation environment. This has contributed to the enhancement of the existing mechanism, which is capable of deciding to either create or evict more than one file during a particular time. Furthermore, files logical dependencies were integrated into the replica creation scheme to evaluate data files more accurately

A novel cost-based replica server placement for optimal service quality in cloud-based content delivery network

Replica server placement is one of the crucial concerns for a given geographic diversity associated with placement problems in content delivery network (CDN). After reviewing the existing literatures, it is noted that studies are more for solving placement problem in conventional CDN and not much over cloud-based CDN architectures, which some few studies are reported towards replica selection are much in its nascent stages of development. Moreover, such models are not benchmarked or practically assessed to prove its effectiveness. Hence, the proposed study introduces a novel design of computational framework associated with cloud-based CDN which can facilitate cost-effective replica server management for enhanced service delivery. Implemented using analytical research methodology, the simulated study outcome shows that proposed scheme offers reduced cost, reduced resource dependencies, reduced latency, and faster processing time in contrast to existing models of replica server placement

Implementation of Sub-Grid-Federation Model for Performance Improvement in Federated Data Grid

In this work, a new model for federation data grid system called Sub-Grid-Federation was designed to improve access latency by accessing data from the nearest possible sites. The strategy in optimising data access was based on the process of searching into the area identified as ‘Network Core Area’ (NCA). The performance of access latency in Sub-Grid-Federation was tested based on the mathematical proving and simulated using OptorSim simulator. Four case studies were carried out and tested in Optimal Downloading Replication Strategy (ODRS) and the Sub-Grid-Federation. The results show that Sub-Grid-Federation is 20% better in terms of access latency and 21% better in terms of reducing remotes sites access compared to ODRS. The results indicate that the Sub-Grid-Federation is a better alternative for the implementation of collaboration and data sharing in data grid system.                                                                                    Keywords: Data grid, replication, scheduling, access latenc

Cost and Performance-Based Resource Selection Scheme for Asynchronous Replicated System in Utility-Based Computing Environment

A resource selection problem for asynchronous replicated systems in utility-based computing environment is addressed in this paper. The needs for a special attention on this problem lies on the fact that most of the existing replication scheme in this computing system whether implicitly support synchronous replication and/or only consider read-only job. The problem is undoubtedly complex to be solved as two main issues need to be concerned simultaneously, i.e. 1) the difficulty on predicting the performance of the resources in terms of job response time, and 2) an efficient mechanism must be employed in order to measure the trade-off between the performance and the monetary cost incurred on resources so that minimum cost is preserved while providing low job response time. Therefore, a simple yet efficient algorithm that deals with the complexity of resource selection problem in utility-based computing systems is proposed in this paper. The problem is formulated as a Multi Criteria Decision Making (MCDM) problem. The advantages of the algorithm are two-folds. On one fold, it hides the complexity of resource selection process without neglecting important components that affect job response time. The difficulty on estimating job response time is captured by representing them in terms of different QoS criteria levels at each resource. On the other fold, this representation further relaxed the complexity in measuring the trade-offs between the performance and the monetary cost incurred on resources. The experiments proved that our proposed resource selection scheme achieves an appealing result with good system performance and low monetary cost as compared to existing algorithms

Technical analysis of content placement algorithms for content delivery network in cloud

Content placement algorithm is an integral part of the cloud-based content de-livery network. They are responsible for selecting a precise content to be re-posited over the surrogate servers distributed over a geographical region. Although various works are being already carried out in this sector, there are loopholes connected to most of the work, which doesn't have much disclosure. It is already known that quality of service, quality of experience, and the cost is always an essential objective targeting to be improved in existing work. Still, there are various other aspects and underlying reasons which are equally important from the design aspect. Therefore, this paper contributes towards reviewing the existing approaches of content placement algorithm over cloud-based content delivery network targeting to explore open-end re-search issues

Content-aware resource allocation model for IPTV delivery networks

Nowadays, with the evolution of digital video broadcasting, as well as, the advent of high speed broadband networks, a new era of TV services has emerged known as IPTV. IPTV is a system that employs the high speed broadband networks to deliver TV services to the subscribers. From the service provider viewpoint, the challenge in IPTV systems is how to build delivery networks that exploits the resources efficiently and reduces the service cost, as well. However, designing such delivery networks affected by many factors including choosing the suitable network architecture, load balancing, resources waste, and cost reduction. Furthermore, IPTV contents characteristics, particularly; size, popularity, and interactivity play an important role in balancing the load and avoiding the resources waste for delivery networks. In this paper, we investigate the problem of resource allocation for IPTV delivery networks over the recent architecture, peer-service area architecture. The Genetic Algorithm as an optimization tool has been used to find the optimal provisioning parameters including storage, bandwidth, and CPU consumption. The experiments have been conducted on two data sets with different popularity distributions. The experiments have been conducted on two popularity distributions. The experimental results showed the impact of content status on the resource allocation process

Flexible and dynamic replication control for interdependent distributed real-time embedded systems

Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system’s performance. This paper proposes heuristics to dynamically determine which components to replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The activation of passive replicas is coordinated through a fast convergence protocol that reduces the complexity of the needed interactions among nodes until a new collective global service solution is determined

Geography Aware Virtual Machine Migrations and Replications for Distributed Cloud Data Centers

Cloud computing provides access to computing resources for a fee. Client applications and services can be hosted in clouds. Cloud computing typically uses a network of data centers that are geographically dispersed. The distance between clients and applications is impacted by geographical distance. The geographical distribution of client requests can be random and difficult to predict. This suggests a need to reconsider the placement of services at run-time through migration. This thesis describes a framework based on software-defined networking (SDN) principles. It demonstrates algorithms that are periodically executed and determine candidate services to migrate and replicate as well as target data centers to migrate to and replicate to and an evaluation. The evaluation shows that effectiveness of the algorithms