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RISS 인기검색어
- 검색키워드
- 저자 : G.Siva Shanmugam (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Effort of Load Balancer to Achieve Green Cloud Computing : A Review
G.Siva Shanmugam,N.Ch.S. N. Iyengar 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.3
In a distributed system, from the starting days onwards distribution of load among servers becomes a serious problem in the commercial Internet. The problem in this scenario is? The entire single application oriented server has to engage the entire amount of traffic and if they went down, all commercial activities come down offline result out of business. Running individually the application server couldn’t support start-up budgets. The folks involved in the Web Commercial plan to solve this problem by distributing the load evenly to all the servers running on the web host owned by different agents or organizations; thus new scenario was born named as Load Balancing. In this treatise, we investigate several shapes attenuated by load Balancer and reviewed the algorithms proposed on load balancing. Here we took both static as well as dynamic based algorithms and their performances are formulated by comparison with all other existing scheme. This paper also brings connectivity on green computing with cloud load balancers. By cloud computing we can attain multi tenancy and dynamic resource handling which automatically reduces co2 emission from servers. Without the facility of sharing single resources among thousands of peoples, green computing is not possible. So the nature of cloud load balancer and green computing was illustrated here.
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Enhancement of Semantic Interoperability in Healthcare Systems Using IFCIoT Architecture
Sony P,Siva Shanmugam G,Sureshkumar Nagarajan 한국인터넷정보학회 2024 KSII Transactions on Internet and Information Syst Vol.18 No.4
Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy -hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.
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