A QoS-Aware Heuristic Algorithm for Replica Placement

Wang, Hsiangkai; Liu, Pangfeng; Wu, Jan‐Jan

doi:10.1109/icgrid.2006.311003

Cited by 36 publications

(29 citation statements)

References 22 publications

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“…Waxman model [31] is used to generate the multi-cloud topology. The available link bandwidth is computed using a uniform distribution with the range [0.622, 2.5] (Gbps).…”

Section: A) Testbed Environmentmentioning

confidence: 99%

On the Dynamic Maintenance of Data Replicas based on Access Patterns in A Multi-Cloud Environment

Shorfuzzaman

2017

ijacsa

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Abstract-Cloudcomputing provides services and infrastructures to enable end-users to access, modify and share massive geographically distributed data. There are increasing interests in developing data-intensive (big data) applications in this computing environment that need to access huge datasets. Accessing such data in an efficient way is deterred with factors such as dynamic changes in resource availability, provision of diverse service quality by different cloud providers. Data replication has already been proven to be an effective technique to overcome these challenges. Replication offers reduced response time in data access, higher data availability and improved system load balancing. Once the replicas are created in a multi-cloud environment, it is of utmost importance to continuously support maintenance of these replicas dynamically. This is to ensure that replicas are located in optimal data center locations to minimize replication cost and to meet specific user and system requirements. First, this paper proposes a novel approach to distributed placement of static replicas in appropriate data center locations. Secondly, motivated by the fact that a multi-cloud environment is highly dynamic, the paper presents a dynamic replica maintenance technique that reallocates replicas to new data center locations upon significant performance degradation. The evaluation results demonstrate the effectiveness of the presented dynamic maintenance technique with static placement decisions in a multi-cloud environment.

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“…Waxman model [31] is used to generate the multi-cloud topology. The available link bandwidth is computed using a uniform distribution with the range [0.622, 2.5] (Gbps).…”

Section: A) Testbed Environmentmentioning

confidence: 99%

On the Dynamic Maintenance of Data Replicas based on Access Patterns in A Multi-Cloud Environment

Shorfuzzaman

2017

ijacsa

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“…When the clients do not know where the replicas are (replicablind policy), the graph is simplified to a tree (fixed routing scheme) with the Closest policy, and in this case again it is possible to find an optimal dynamic programming algorithm. In [10], Wang et al deal with the QoS aware replica placement problem on grid systems. In their general graph model, QoS is a parameter of communication cost.…”

Section: Introductionmentioning

confidence: 99%

Impact of QoS on Replica Placement in Tree Networks

Benoît

Rehn

Robert

2007

Computational Science – ICCS 2007

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Abstract. This paper discusses and compares several policies to place replicas in tree networks, subject to server capacity and QoS constraints. The client requests are known beforehand, while the number and location of the servers are to be determined. We study three strategies. The first two strategies assign each client to a unique server while the third allows requests of a client to be processed by multiple servers. The main contribution of this paper is to assess the impact of QoS constraints on the total replication cost. In this paper, we establish the NP-completeness of the problem on homogeneous networks when the requests of a given client can be processed by multiple servers. We provide several efficient polynomial heuristic algorithms for NP-complete instances of the problem.

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“…Intermediate nodes can be either routers for network communications or I/O servers that store file replicas. We assume that, initially, only one copy (i.e., the master copy) of a file exists at the root site, as in [9,10,11,12,13]. Let T i be the sub-tree rooted at node i.…”

Section: The System Modelmentioning

confidence: 99%

“…In this paper we use a hierarchical Grid model, one of the most common architectures in current use [7,9,10,11,12,13]. Consider Fig.…”

Section: The System Modelmentioning

confidence: 99%

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Optimizing Server Placement for QoS Requirements in Hierarchical Grid Environments

Wang

Hsu

Liu

et al.

Advances in Grid and Pervasive Computing

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Abstract. This paper focuses on two problems related to QoS-aware I/O server placement in hierarchical Grid environments. Given a hierarchical network with requests from clients, the network latencies of links, constraints on servers' capabilities and the service quality requirement, the solution to the minimum server placement problem attempts to place the minimum number of servers that meet both the constrains on servers' capabilities and the service quality requirement. As our model considers both the different capabilities of servers and the network latencies, it is more general than similar works in the literatures. Instead of using a heuristic approach, we propose an optimal algorithm based on dynamic programming to solve the problem. We also consider the optimal service quality problem, which tries to place a given number of servers appropriately so that the maximum expected response time is minimized. We prove that an optimal server placement can be achieved by combining the dynamic programming algorithm with a binary search on the service quality requirement. The simulation results clearly show the improvement in the number of servers and the maximum expected response time.

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A QoS-Aware Heuristic Algorithm for Replica Placement

Cited by 36 publications

References 22 publications

On the Dynamic Maintenance of Data Replicas based on Access Patterns in A Multi-Cloud Environment

On the Dynamic Maintenance of Data Replicas based on Access Patterns in A Multi-Cloud Environment

Impact of QoS on Replica Placement in Tree Networks

Optimizing Server Placement for QoS Requirements in Hierarchical Grid Environments

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