Add to ORKGDuring the last decade, using parallel and distributed system has become general. In these systems, a huge size of data or computation is distributed among many systems to get better performance. Dividing data is one of the challenges in this type of systems. Divisible Load Theory (DLT) is one of the proposed methods for scheduling data distribution in parallel or distributed systems. Many researches have been done in this field and some applications have been introduced for it. A novice researcher in this field needs to know thing about DLT such as history, fundamental concepts, terminology, important parameters and DLT applications. In this article after history and terminology, previous researches have been categorized in some class ba...
In many data grid applications, data can be decomposed into multiple independent sub-datasets and di...
In many data grid applications, data can be decomposed into multiple independent sub datasets and d...
Cluster computing has emerged as a new paradigm for solving large-scale problems. To enhance QoS and...
Abstract. Divisible load theory is a methodology involving the linear and continuous modeling of par...
There is extensive literature concerning the divisible load theory. The divisible load theory is mai...
During the last decade, the use of parallel and distributed systems has become more common. In these...
International audienceDivisible Load Theory (DLT) is an established framework to study Divisible Loa...
There is extensive literature concerning the divisible load theory. The divisible load theory is mai...
Problem statement: In many data grid applications, data can be decomposed into multiple independent ...
The use of parallel and distributed systems has become very common in the last decade. Dividing data...
International audienceDivisible Load Theory (DLT) is an established mathematical framework to study ...
High performance parallel and distributed computing systems are used to solve large, complex, and da...
Abstract: Scheduling an application in data grid was significantly complex and very challenging beca...
The Divisible Load Theory (DLT) is a paradigm in the area of parallel and distributed computing. Ba...
In this paper we introduce the Divisible Load Scheduling (DLS) family of algorithms for data-intensi...
In many data grid applications, data can be decomposed into multiple independent sub-datasets and di...
In many data grid applications, data can be decomposed into multiple independent sub datasets and d...
Cluster computing has emerged as a new paradigm for solving large-scale problems. To enhance QoS and...
Abstract. Divisible load theory is a methodology involving the linear and continuous modeling of par...
There is extensive literature concerning the divisible load theory. The divisible load theory is mai...
During the last decade, the use of parallel and distributed systems has become more common. In these...
International audienceDivisible Load Theory (DLT) is an established framework to study Divisible Loa...
There is extensive literature concerning the divisible load theory. The divisible load theory is mai...
Problem statement: In many data grid applications, data can be decomposed into multiple independent ...
The use of parallel and distributed systems has become very common in the last decade. Dividing data...
International audienceDivisible Load Theory (DLT) is an established mathematical framework to study ...
High performance parallel and distributed computing systems are used to solve large, complex, and da...
Abstract: Scheduling an application in data grid was significantly complex and very challenging beca...
The Divisible Load Theory (DLT) is a paradigm in the area of parallel and distributed computing. Ba...
In this paper we introduce the Divisible Load Scheduling (DLS) family of algorithms for data-intensi...
In many data grid applications, data can be decomposed into multiple independent sub-datasets and di...
In many data grid applications, data can be decomposed into multiple independent sub datasets and d...
Cluster computing has emerged as a new paradigm for solving large-scale problems. To enhance QoS and...