Among the various approaches for parallel depthrst search (DFS), the stack-splitting schemes are most popular. However, as shown in this paper, dynamical stack-splitting is not suitable for massively parallel systems with several hundred processors. Initial work-load imbalances and work packets of dissimilar sizes cause a high communication overhead. We compare work-load balancing strategies of...

Distributed key/value stores are a basic building block for large-scale Internet services. Support for range queries introduces new challenges to load balancing since both the key and workload distribution can be non-uniform. We build on previous work based on the power of choice to present algorithms suitable for active and passive load balancing that adapt to both the key and workload distrib...

In a previous work, we have shown the very high power of asynchronism for parallel iterative algorithms in a global context of grid computing. In this article, we study the interest of coupling load balancing with asynchronism in these algorithms. We propose a non-centralized version of dynamic load balancing which is best suited to asynchronism. After showing, by some experiments on a given OD...

Consider the following load balancing problem. We are given a graph with arbitrary topology and an arbitrary load distribution on the nodes. In each time step, a node can send any amount of load to each neighbor in parallel. This problem is a simple formalization of dynamic load balancing problems arising in various applications on parallel and distributed machines. Earlier work on this problem...

Load balancing is considered by the 3GPP as an important issue in Self-Organizing Networks due to its effectiveness to increase network capacity. In next generation wireless networks, load balancing can be easily implemented by tuning handover (HO) margins, achieving a decrease in call blocking. However, call dropping can be increased as a negative effect of the HO-based load balancing, because...

This paper studies cluster load balancing policies and system support for fine-grain network services. Load balancing on a cluster of machines has been studied extensively in the literature, mainly focusing on coarse-grain distributed computation. Fine-grain services introduce additional challenges because system states fluctuate rapidly for those services and system performance is highly sensi...

The distributed computations are broadly used in the current world for processing large scale jobs. For data intensive applications with big data, it has recently received a very good attention. A simple programming model that allows easy development of scalable parallel applications to process big data on large clusters was required. In our proposed work the input files will be subjected to lo...

RFID middleware often has to process enormous amounts of data, possibly causes overloading and leading to data errors. Therefore, RFID middleware applications require load-balancing mechanisms. This work proposes a grid-based load-balancing mechanism for RFID middleware applications. The proposed mechanism incorporates functional modules Buffer Management and Load Balancing Management over a gr...

This paper proposes a distributed shared memory cluster architecture with load balancing. The architecture is based on dynamic task scheduling approach for distribution and assignment. It enhances the performance of communication across clusters for data access. The proposed dynamic load balancing model uses the concept of work stealing, which intelligently balances the load among different nod...

Load balancing is the process of improving the Performance of a parallel and distributed system through is distribution of load among the processors[1-2]. Most of the previous work in load balancing and distributed decision making in general, do not effectively take into account the uncertainty and inconsistency in state information but in fuzzy logic, we have advantage of using crisps inputs. ...