SOA selection and replication based on QoS

Puntheeranurak, Sutheera; Chanpen, Aekkawit

doi:10.1109/tencon.2014.7022290

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…In the third experiment, we consider the effect of dereplication method on load balancing where 16 storage nodes have hotspot data. In particular, no request is generated during time intervals [3,5], [6,8], [9,11], [12,14], and [15,17] hours. The simulation results are illustrated in Figure 4.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…To avoid excessive replication because of the burstiness of arriving requests, ARM constrains the allowable number of copies for each storage node according to their loads using (5). The value color denotes the color layer of storage node , and denotes the set of copy limits in each level where = { 1 , 2 , 3 , .…”

Section: Active Replica Managementmentioning

confidence: 99%

“…As for data reliability, if one node fails, users expect other alternative nodes to work instead [4,5]. As a result, users can access their data all the time.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Load Balancing Using Active Replica Management in a Storage System

Yang

2016

Mathematical Problems in Engineering

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Many algorithms can uniformly distribute data to storage nodes in a storage system. However, it cannot avoid load imbalance because data has different popularity. To resolve this issue, we propose a novel dynamic replication scheme, namely, Active Replica Management (ARM). ARM actively establishes optimal number of copies for hotspot data according to data access behaviors and then efficiently distributes copies to other storage nodes based on current amount of copies related to hotspot data. To improve storage utilization, ARM automatically and gradually dereplicates the useless copies of hotspot data when they become nonhotspot data. ARM resolves load imbalance by allocating dynamic copies to adequate storage nodes, and hence it can prevent partial storage nodes from overburdening. Simulation results demonstrate that ARM is an efficient scheme with excellent performance on load balancing, significantly closer to Optimal Load Balancing (OLB). In addition, ARM’s performance outperforms both Static Load Balancing (SLB) and No Replica schemes.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Active Replica Managementmentioning

confidence: 99%

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Efficient Load Balancing Using Active Replica Management in a Storage System

Yang

2016

Mathematical Problems in Engineering

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“…Based on this, recognizing the capabilities of the hosting environment and effectively matching those for the wanted service configuration are required to enable hosting services with strict QoS requirements. A method [7,8] to gather context based data of service providers is given as input to the rule based system and appropriateness of every SP is obtained as output including recommended stipulations regarding their usage. Service Oriented Architecture (SOA) which comprises of many consumers meets with reliability and availability problem.…”

Section: Related Workmentioning

confidence: 99%

Service selection in service oriented architecture using probabilistic approach and asynchronous queues with interceptor validation

Chelliah¹,

Sathish²,

Subalakshmi³

2020

IJECE

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In service Oriented Architecture, many services are offered with similar functionality but with different service quality parameters. Thus the service selection using a deterministic approach causes conflicts and inefficient results. We use asynchronous queue to model the service inventory architecture avoiding unnecessary locking of resources and thus allowing a provision to consumers to get their required services without intervening and with temporally decoupled fashion. Actually this kind of service selection strategy is considered in regards with game theory to eliminate fluctuations of queue length. It offers a discrete random service which is equal to some request requested by consumers, it means service can be provided based on probability mass function as a substitute of deterministic decisions for selecting a proper service provider as of the consumers. Once the request is taken out from the queue, it is delivered to the interceptor that has validation and sanitization module. It thus reduces the peak queue length and reduces periodic fluctuations in the queue length.

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Efficient load balancing using active replica management

Yang

2016

2016 International Conference on Applied System Innovation (ICASI)

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SOA selection and replication based on QoS

Cited by 3 publications

References 13 publications

Efficient Load Balancing Using Active Replica Management in a Storage System

Efficient Load Balancing Using Active Replica Management in a Storage System

Service selection in service oriented architecture using probabilistic approach and asynchronous queues with interceptor validation

Efficient load balancing using active replica management

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