Load Balancing of Distributed Servers in Distributed File Systems

Singh, Ravideep; Gupta, Pradeep Kumar; Gupta, Punit; Malekian, Reza; Maharaj, B. T.; Andriukaitis, Darius; Valinevicius, Algimantas; Bogatinoska, Dijana Capeska; Karadimce, Aleksandar

doi:10.1007/978-3-319-25733-4_4

Cited by 3 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(i) Class A: s j is in U [1,100] (ii) Class B: s j is in U [10,300] (iii) Class C: s j is in U[500, 1500] (iv) Class D:…”

Section: Resultsmentioning

confidence: 99%

“…Our objective is to minimize TC g given in equation (1). Based on the standard three-field notation in [20], the studied problem is denoted by P‖TC g .…”

Section: Approximate Solutionsmentioning

confidence: 99%

“…Some research works related to the balancing process can be cited. Singh et al [1] proposed a dynamic load balancing algorithm of strongly connected servers, which takes into account these servers capability of parallel processing and their request queuing capacity in order to classify the overloaded servers and the least loaded servers, and once a server gets overloaded, its load is migrated to the least loaded one. In [2], Hung et al introduced an enhancement of the max-min scheduling algorithm by decreasing the completion time of the clients' requests; this algorithm uses a "supervised machine learning" that clusters utilization percent of virtual machines and clusters size of requests, and then the virtual machine which has the least utilization percent is appointed to the largest cluster requests.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dispatching-Rule Variants Algorithms for Used Spaces of Storage Supports

Alquhayz

Jemmali

Otoom

2020

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

The paper is regarding the fair distribution of several files having different sizes to several storage supports. With the existence of several storage supports and different files, we search for a method that makes an appropriate backup. The appropriate backup guarantees a fair distribution of the big data (files). Fairness is related to the used spaces of storage support distribution. The problem is how to find a fair method that stores all files on the available storage supports, where each file is characterized by its size. We propose in this paper some fairness methods that seek to minimize the gap between used spaces of all storage supports. In this paper, several algorithms are developed to solve the proposed problem, and the experimental study shows the performance of these developed algorithms.

show abstract

“…(i) Class A: s j is in U [1,100] (ii) Class B: s j is in U [10,300] (iii) Class C: s j is in U[500, 1500] (iv) Class D:…”

Section: Resultsmentioning

confidence: 99%

“…Our objective is to minimize TC g given in equation (1). Based on the standard three-field notation in [20], the studied problem is denoted by P‖TC g .…”

Section: Approximate Solutionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dispatching-Rule Variants Algorithms for Used Spaces of Storage Supports

Alquhayz

Jemmali

Otoom

2020

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…In [13], authors examined the problem of load balancing in distributed le systems. They also analyzed the impact of dierent factors on load balancing.…”

Section: Related Workmentioning

confidence: 99%

Efficient Storage Approach for Big Data Analytics: An Iterative-Probabilistic Method for Dynamic Resource Allocation of Big Satellite Images

et al. 2023

View full text Add to dashboard Cite

Satellite images play a crucial role in ecology as they provide rich information about the Earth's surface. The deep analysis of satellite images presents a vast challenge due to the sheer size of the data that needs to be managed. Sophisticated storage solutions are required to handle the ever-increasing velocity of incoming data and to deal with potential latency or data loss. Storage balancing ensures ecient allocation and distribution of storage capacity across a system, which involves monitoring, analyzing, and adjusting how data is stored to optimize performance, minimize downtime, and maximize cost savings. Additionally, storage balancing helps avoid data bottlenecks by automatically redistributing data across multiple resources. While many solutions have been proposed to balance storage, no polynomial solution is available. This paper addresses the issue of transmitting a considerable amount of satellite images across the network to various storage supports. The challenge is to nd an eective way to schedule these satellite images to the storage supports that lead to equitable results in distribution. Many heuristics and enhancement methods are proposed to solve this problem. The eectiveness of the algorithms presented in this paper was tested and analyzed through extensive testing. The experimental study shows that the proposed heuristics outperform those developed in the literature. Indeed, in 73.8% of cases, the best-proposed algorithm, the best iterative-selection satellite images algorithm (BIS), reached the best solution compared to the best algorithm in the literature and the other proposed algorithms. The BIS algorithm obtained an average gap of 0.147 in an average running time of 1.0654 s.

show abstract

“…Problems mentioned above are solved by using ECC (Elliptic Curve Cryptography) as in [15]. A new method that balances the load of storage servers and effectively utilizes the server capabilitiesis suggested in [16]. Gupta and Biswas in [17], [18] offer homomorphic encryption scheme for cloud security with use of ECC.…”

Section: Introductionmentioning

confidence: 99%

Storage and Communication Security in Cloud Computing Using a Homomorphic Encryption Scheme Based Weil Pairing

Dogan¹,

Altindiş²

2020

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

With introduction of smart things into our lives, cloud computing is used in many different areas and changes the communication method. However, cloud computing should guarantee the complete security assurance in terms of privacy protection, confidentiality, and integrity. In this paper, a Homomorphic Encryption Scheme based on Elliptic Curve Cryptography (HES-ECC) is proposed for secure data transfer and storage. The scheme stores the data in the cloud after encrypting them. While calculations, such as addition or multiplication, are applied to encrypted data on cloud, these calculations are transmitted to the original data without any decryption process. Thus, the cloud server has only ability of accessing the encrypted data for performing the required computations and for fulfilling requested actions by the user. Hence, storage and transmission security of data are ensured. The proposed public key HES-ECC is designed using modified Weil-pairing for encryption and additional homomorphic property. HES-ECC also uses bilinear pairing for multiplicative homomorphic property. Security of encryption scheme and its homomorphic aspects are based on the hardness of Elliptic Curve Discrete Logarithm Problem (ECDLP), Weil Diffie-Hellman Problem (WDHP), and Bilinear Diffie-Helman Problem (BDHP).

show abstract

Load Balancing of Distributed Servers in Distributed File Systems

Cited by 3 publications

References 7 publications

Dispatching-Rule Variants Algorithms for Used Spaces of Storage Supports

Dispatching-Rule Variants Algorithms for Used Spaces of Storage Supports

Efficient Storage Approach for Big Data Analytics: An Iterative-Probabilistic Method for Dynamic Resource Allocation of Big Satellite Images

Storage and Communication Security in Cloud Computing Using a Homomorphic Encryption Scheme Based Weil Pairing

Contact Info

Product

Resources

About