Minimizing Cost of K-Replica in Hierarchical Data Grid Environment

Mansouri, Yaser; Azad, Saeed Talatian; Chamkori, Alireza

doi:10.1109/aina.2014.130

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…The problem of placing content replicas over geographically distributed datacenters and its impact on various network parameters, such as cost, power consumption, QoS or security has been investigated in [17]- [25]. Replica placement approaches aimed at minimizing the bandwidth and storage cost for content distribution networks can be found in [17], [19]. The work in [20] focuses on replica placement to reduce the total power consumption of the network, while the study in [21] aims at enhancing content availability in datacenter networks.…”

Section: Related Workmentioning

confidence: 99%

Manycast, Anycast, and Replica Placement in Optical Inter-Datacenter Networks

Muhammad¹,

Skorin-Kapov²,

Furdek³

2017

J. Opt. Commun. Netw.

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The expanding adoption of cloud-based services in recent years puts stringent requirements on datacenters (DCs) and their interconnection networks. Optical interdatacenter networks represent the only viable option for satisfying the huge bandwidth required to replicate and update content for cloud-based services across geographically dispersed datacenters. In addition to content replication and synchronization, optical inter-datacenter networks must also support communication between datacenters and endusers. The resulting new traffic patterns and the enormous traffic volumes call for new capacity-efficient approaches for inter-datacenter network design that incorporate both transport and datacenter resource planning. This paper introduces an integrated approach to optimally place content replicas across DCs by concurrently solving the routing and wavelength assignment (RWA) problem for both inter-DC content replication and synchronization traffic following the manycast routing paradigm, and enduser driven user-to-DC communication following the anycast routing paradigm, with the objective to reduce the overall network capacity usage. To attain this goal, the Manycast, Anycast and Replica Placement (MARP) problem is formulated as an integer linear program (ILP), to find optimal solutions for smaller problem instances. Due to the problem complexity, a scalable and efficient heuristic algorithm is developed to solve larger network scenarios. Simulation results demonstrate that the proposed integrated MARP strategy can significantly reduce the network capacity usage when compared to benchmarking replica placement and RWA schemes aimed at minimizing the resources consumed by either of the two types of traffic independently.

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Section: Related Workmentioning

confidence: 99%

Manycast, Anycast, and Replica Placement in Optical Inter-Datacenter Networks

Muhammad¹,

Skorin-Kapov²,

Furdek³

2017

J. Opt. Commun. Netw.

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“…a certain number of replicas. Dynamically adjusting the optimal number of replicas with economic consideration presents new research challenges [38]. Finding optimal number of replicas puts emphasis on replica placement as well.…”

Section: Open Problems In Dynamic Replication Strategiesmentioning

confidence: 99%

Dynamic replication strategies in data grid systems: a survey

et al. 2015

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In data grid systems, data replication aims to increase availability, fault tolerance, load balancing and scalability while reducing bandwidth consumption, and job execution time. Several classification schemes for data replication were proposed in the literature, (i) static vs. dynamic, (ii) centralized vs. decentralized, (iii) push vs. pull, and (iv) objective function based. Dynamic data replication is a form of data replication that is performed with respect to the changing conditions of the grid environment. In this paper, we present a survey of recent dynamic data replication strategies. We study and classify these strategies by taking the target data grid architecture as the sole classifier. We discuss the key points of the studied strategies and provide feature comparison of them according to important metrics. Furthermore, the impact of data grid architecture on dynamic replication performance is investigated in a simulation study. Finally, some important issues and open research problems in the area are pointed out. B Uras Tos

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“…We also propsed algorithm to place k replicas in data grid tree network [11], [12]. Kalpakis et al [13] discussed the replica placement problem when a general objective function takes into account read, write, and storage costs and uses a minimum spanning tree to propagate updates among the replicas.…”

Section: Related Workmentioning

confidence: 99%

Cost Optimization of Replicas in Tree Network of Data Grid with QoS and Bandwidth Constraints

Chamkoori¹,

Heidari²,

Parhizgar³

2017

ijacsa

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Abstract-Data Grid provides resources for data-intensive scientific applications that need to access a huge amount of data around the world. Since data grid is built on a wide-area network, its latency prohibits efficient access to data. This latency can be decreased by data replication in the vicinity of users who request data. Data replication can also improve data availability and decreases network bandwidth usage. It can be influenced by two imperative constraints: Quality of Service (QoS) that is locally owned by a user and bandwidth constraint that globally affects on link that might be shared by multiple users. Guaranteeing both constraints and also minimizing replication cost consisting communication and storage costs is a challenging task. To address this problem, the authors propose to use a dynamic algorithm called Optimal Placement of Replicas to minimize replication cost and coupled with meeting both mentioned constraints. It is also designed as heuristic algorithms that are competitive with optimal algorithm in performance metrics such as replication cost, network bandwidth usage and data availability. Extensive simulations show that the Optimal algorithm saves 10% cost compared to heuristic algorithms and provides local responsiveness for half of the user requests.

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Minimizing Cost of K-Replica in Hierarchical Data Grid Environment

Cited by 6 publications

References 20 publications

Manycast, Anycast, and Replica Placement in Optical Inter-Datacenter Networks

Manycast, Anycast, and Replica Placement in Optical Inter-Datacenter Networks

Dynamic replication strategies in data grid systems: a survey

Cost Optimization of Replicas in Tree Network of Data Grid with QoS and Bandwidth Constraints

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