Search Word(s) in Title, Keywords, Authors, and Abstract: Load Balancing

Duplication with Task Assignment in Mesh Distributed System
Rashmi Sharma and Nitin
Page: 193~214, Vol. 10, No.2, 2014
10.3745/JIPS.01.0001
Keywords: Distributed System(DS), Task Assignment Heuristics, Task Duplication(TD), Directed Acyclic Graph(DAG)
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Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).


Cost-Effective Replication Schemes for Query Load Balancing in DHT-Based Peer-to-Peer File Searches
Qi Cao and Satoshi Fujita
Page: 628~645, Vol. 10, No.4, 2014
10.3745/JIPS.03.0020
Keywords: DHT, Load Balancing, Load Reduction, Multi-Keyword Search, Replication
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In past few years, distributed hash table (DHT)-based P2P systems have been proven to be a promising way to manage decentralized index information and provide efficient lookup services. However, the skewness o


An Efficient Load Balancing Scheme for Multi-Gateways in Wireless Mesh Networks
Junping Liu and Sang-Hwa Chung
Page: 365~378, Vol. 9, No.3, 2013
10.3745/JIPS.2013.9.3.365
Keywords: Wireless Mesh Network, Internet Gateway, Multi-Gateway Multi-Root, Load Balancing
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In Wireless Mesh Networks (WMNs), we usually deploy multiple Internet Gateways (IGWs) to improve the capacity of WMNs. As most of the traffic is oriented towards the Internet and may not be distributed evenly among different IGWs, some IGWs may suffer from bottleneck problem. To solve the IGW bottleneck problem, we propose an efficient scheme to balance the load among different IGWs within a WMN. Our proposed load-balancing scheme consists of two parts: a traffic load calculation module and a traffic load migration algorithm. The IGW can judge whether the congestion has occurred or will occur by using a linear smoothing forecasting method. When the IGW detects that the congestion has occurred or will occur, it will firstly select another available IGW that has the lightest traffic load as the secondary IGW and then inform some mesh routers (MPs) which have been selected by using the Knapsack Algorithm to change to the secondary IGW. The MPs can return to their primary IGW by using a regression algorithm. Our Qualnet 5.0 experiment results show that our proposed scheme gives up to 18% end-to-end delay improvement compared with the existing schemes.


Round Robin with Server Affinity: A VM Load Balancing Algorithm for Cloud Based Infrastructure
Komal Mahajan, Ansuyia Makroo and Deepak Dahiya
Page: 379~394, Vol. 9, No.3, 2013
10.3745/JIPS.2013.9.3.379
Keywords: Virtual Machine (VM), Server affinity, VM load balancer, CloudAnalyst, Data center, Cloudlet
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Cloud computing is an evolving computing paradigm that has influenced every other entity in the globalized industry, whether it is in the public sector or the private sector. Considering the growing importance of cloud, finding new ways to improve cloud services is an area of concern and research focus. The limitation of the available Virtual Machine Load balancing policies for cloud is that they do not save the state of the previous allocation of a virtual machine to a request from a Userbase and the algorithm requires execution each time a new request for Virtual Machine allocation is received from the Userbase. This problem can be resolved by developing an efficient virtual machine load balancing algorithm for the cloud and by doing a comparative analysis of the proposed algorithm with the existing algorithms.


Dynamic Load Balancing and Network Adaptive Virtual Storage Service for Mobile Appliances
Ivy Ong and Hyotaek Lim
Page: 53~62, Vol. 7, No.1, 2011
10.3745/JIPS.2011.7.1.053
Keywords: iATA Protocol, Load Balancing, Network Monitoring, Storage Network Solution, Write Replication
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With the steady growth of mobile technology and applications, demand for more storage in mobile devices has also increased. A lightweight block-level protocol, Internet Advanced Technology Attachment (iATA), has been developed to deliver a costeffective storage network solution for mobile devices to obtain more storage. This paper seeks to contribute to designing and implementing Load Balancing (LB), Network Monitoring (NM) and Write Replication (WR) modules to improve the protocol¡¯s scalability and data availability. LB and NM modules are invoked to collect system resources states and current network status at each associate node (server machine). A dynamic weight factor is calculated based on the collected information and sent to a referral server. The referral server is responsible to analyze and allocate the most ideal node with the least weight to serve the client. With this approach, the client can avoid connecting to a heavily loaded node that may cause delays in subsequent in-band I/O operations. Write replication is applied to the remaining nodes through a WR module by utilizing the Unison file synchronization program. A client initially connected to node IP A for write operations will have no hindrances in executing the relevant read operations at node IP B in new connections. In the worst case scenario of a node crashing, data remain recoverable from other functioning nodes. We have conducted several benchmark tests and our results are evaluated and verified in a later section.