Paper Info
Title
Autonomic Self Healing-Based Load Assessment For Load Division In Okkam Backbone Cluster
Abstract
Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.
Year
DOI
Venue
2009
10.3745/JIPS.2009.5.2.069
JOURNAL OF INFORMATION PROCESSING SYSTEMS
Keywords
Field
DocType
Self Healing Systems, Load Estimation and Balancing, OKKAM, Entity Naming System
Virtual machine,Software deployment,Intelligent decision support system,Computer science,Computer network,Real-time computing,Default gateway,Fault tolerance,Software,Access control,Configuration management,Distributed computing
Journal
Volume
Issue
ISSN
5
2
1976-913X
Citations 
PageRank 
References 
0
0.34
14
Authors
1
Name
Order
Citations
PageRank
Junaid Ahsenali Chaudhry15914.78