intelligent computing relating to cloud computing

International Journal of Mechanical Engineering and Computer Applications(IJMCA), Vol 1, Issue 1,February ,2013.

www.ijmca.org Page 5

Intelligent Computing Relating to Cloud ComputingSujata Kumari Rahul Abhishek B S Panda

Research Student Research Student Asst. ProfessorMITS Engg College MITS Engg College MITS Engg College

Rayagada, Odisha. Rayagada, Odisha. Rayagada, [email protected] [email protected] [email protected]

Abstract:This paper contends that the real understanding ofnatural language and the fulfillment of cloudcomputing cannot be reached without dealing withthe significant sentimental factor. This paper pointsout that the achievement and enjoyment of cloudcomputing is highly reliant on breakthroughs inadvanced intelligence. In this paper, advancedintelligence refers to the high level of interactionbetween natural intelligence and artificialintelligence.

We introduce intelligent computing language in thesoftware so that machines can take decisionsautonomously and in real time.By applying artificialintelligence to the cloud, we are hoping to develop asystem through which computers can managethemselves. For example, computer scientists arelooking to develop software that follows computers’power consumption and regulates their operationaccording to the specific needs at any given time, thusreducing energy expenditure.

Implanting artificial intelligence into codes that willrun in the cloud to improve efficiency is one of thestrong research lines . It’s part of a drive to createapplications, executed in the cloud, that go beyondbasic automation to anticipate situations and takedecisions in real time over the Internet. We introduceintelligent computing language in the software so thatmachines can take decisions autonomously and in realtime.Keywords: Affective computing; Artificialintelligence; Cloud computing.

Introduction:This paper discusses the definition for cloudcomputing with the base of artificial intelligence,affective computing, and advanced intelligence, aswell as the relationship among the two fields. By

reporting the latest progress and future prospects, weattempt to unify engineering and affective computingwith the concept of advanced intelligence.Cloudcomputing has recently become a very popular topic.Instead of discussing the concept and intension ofcloud computing, this paper focuses on how progressin engineering field, including natural intelligenceprocessing and natural intelligence understanding,will enormously aid in the achievement of cloudcomputing. It particularly deals with how to constructclouds, how to sweep clouds, and how to predict andexploit clouds.

Another concept discussed in this paper is affectivecomputing. To a large extent, this is a breakthroughin advanced intelligence. Here, it refers to a highfusion of natural and artificial intelligence, anddepends on the emotional capacity entrusted to thecomputer, including the capability of affectiverecognition and affective generation.

The difference between natural intelligence (e.g humanintelligence) and artificial intelligence is hard todefine, as not much is known about naturalintelligence.

Artificial Intelligence (AI) can learn, just like naturalintelligence (NI). When programmed to, ArtificialIntelligence can sense changes in its environment andreact accordingly. It can then refer to the ways itreacted to previous changes to help decide what to dothe next time a similar change occurs.

Both Artificial Intelligence and natural intelligence aremortal. Like humans, Artificial Intelligence can ceaseworking and all that is needed is a natural or man-made disaster to occur.

One big difference between Artificial Intelligence andnatural intelligence is the fact that natural intelligencecan forget and lose information. Artificial Intelligence



could do this if it was program to do so, but this wouldbe counter-productive.

Another big difference is accuracy. ArtificialIntelligence, when given the same information can beexact, every time with speed. When naturalintelligence is given the same information, it can notbe as exact, and is slower.

1.Artificial intelligenceArtificial intelligence (AI) [1,2,3] is the intelligenceof machines and the branch of computer science thataims to create it. AI textbooks define the field as "thestudy and design of intelligent agents" where anintelligent agent is a system that perceives itsenvironment and takes actions that maximize itschances of success. Who coined the term in 1956,defines it as "the science and engineering of makingintelligent machines."

The field was founded on the claim that a centralproperty of humans, intelligence can be so preciselydescribed that it can be simulated by a machine. Thisraises philosophical issues about the nature and theethics of creating artificial beings. Artificialintelligence has been the subject of optimism, but hasalso suffered setbacks and, today, has become anessential part of the technology industry, providingthe heavy lifting for many of the most difficultproblems in computer science.

AI research is highly technical and specialized,deeplydivided into subfields that often fail in the task ofcommunicating with each other. Subfields havegrown up around particular institutions, the work ofindividual researchers, the solution of specificproblems, longstanding differences of opinion abouthow AI should be done and the application of widelydiffering tools. The central problems of AI includesuch traits as reasoning, knowledge, planning,learning, communication, perception and the abilityto move and manipulate objects. General intelligence(or "strong AI") is still among the field's long termgoals.

Basic concept of an Intelligent System

2. Affective computing:

Affective computing is the study and development ofsystems and devices that can recognize, interpret,process, and simulate human affects. It is aninterdisciplinary field spanning computer sciences,psychology, and cognitive science. While the originsof the field may be traced as far back as to earlyphilosophical enquiries into emotion. A motivation forthe research is the ability to simulate empathy. Themachine should interpret the emotional state ofhumans and adapt its behaviour to them, giving anappropriate response for those emotions.

In case of advance intelligence we can relate to anequation;The value of cloud computing v can be described as

v = d ∗ s ∗ (1 + n) ∗ (1 + ai)2 (1)Where d signifies the value of resource pools, s thevalue of service, n the value ofLanguage understanding and ai the value of advancedintelligence.

3. Cloud Computing:Cloud computing [4,5,6] is the use of computingresources (hardware and software) that are deliveredas a service over a network (typically the Internet).Cloud computing entrusts remote services with auser's data, software and computation. At thefoundation of cloud computing is the broader conceptof converged infrastructure and shared services.

Although we literally discussed “clouds” and “cloudcomputing”, this paper stresseson affective computing, and advanced intelligence.



We cited cloud computing as an example, andproposed a paradigm to evaluate the value of cloudcomputing, which is growing linearly alongsidelanguage From Cloud computing to LanguageEngineering, Affective Computing and AdvancedIntelligence engineering, and quadratically along sideadvanced intelligence.

We emphasized that natural language processing andunderstanding were achieved through data,information, knowledge, and intelligence. Wepresented the significance of affective computing andproposed a value function for information processing,including data and affective processing.

Finally, we provided an ecograph of advancedintelligence. Cloud computing can be viewed as anew mode of business computing that from Cloudcomputing to Language Engineering, AffectiveComputing and Advanced Intelligence deployssoftware and data via the Internet. Software and dataare stored in data centers on hardware that areextremely efficient in supporting the load. Users canleverage software and applications at a much lowercost than constructing their own systems [7].

Cloud computing can effectively build computingtasks on resource pools with tremendously reliablehardware, enabling systems to access the scalablecomputing power, storages, and services as needed.Resource pools can take the form of data pools,software pools, computing pools, or even capabilitysupport pools, or any other future strategy thatsupports pools. Such types of resource pools arecalled “clouds”.4. Algorithm

Algorithm 1: MRW (_)Input: a classical planning problem _Output: a solution plan1 s ← sI ;2 hmin ← h(sI ) ;3 counter ← 0 ;4 while s does not satisfy sG do5 if counter > cmor dead-end(s) then6 s ← sI ;7 hmin ← h(sI ) ;8 counter ← 0 ;9 s ← RandomWalk(s,_) ;10 if h(s) < hmin then11 hmin ← h(s);12 counter ← 0;13 else14 counter ← counter + 1;15 return plan;

AI's scientific goal is to understand intelligence bybuilding computer programs that exhibit intelligentbehaviour. It is concerned with the concepts andmethods of symbolic inference, or reasoning, by acomputer, and how the knowledge used to makethose inferences will be represented inside themachine.

Of course, the term intelligence covers manycognitive skills, including the ability to solveproblems, learn, and understand language; AIaddresses all of those. But most progress to date in AIhas been made in the area of problem solving --concepts and methods for building programs thatreason about problems rather than calculate asolution.

The term “cloud” is used because a resource poolshares some features with clouds that waft across thesky as masses of condensed water droplets and frozencrystals. Clouds are massive blocks and dynamicallyextensible, with fuzzy boundaries and irregularshapes. Furthermore, clouds drift as puffs in the sky,so that people cannot exactly grasp where they areand when they come and go, but they are there whenyou look up into the sky. They have various types:iridescent clouds, auspicious clouds, dark clouds,heavy clouds, and fantastic and outrageous clouds,which properly describe resource pools in the cloudera. On the Internet, the term “cloud” has beenwidely used since one of the Internet frontiercompanies, Amazon, referred to network computingas the “Elastic Compute Cloud (EC2)” and gainedconsiderable business success with the term [8, 9].

5. ProposalAs the Internet becomes faster and more robust, thedesktop or laptop computers we all work with will



become, primarily, tools to access the cloud. That initself is not too much of a surprise. After all, the useof applications that live on the Internet has gainedmomentum since we entered the 21st century. Everytime we check a web-based email, like Hotmail, orinteract with our friends on social networking sites,we are cloud computing. But the challenge for cloudcomputing now is for business to take advantage ofit.

However, current research on cloud computing hasfocused mainly on attempts to construct resourcepools, including data, platforms, software, and so on.In fact, real cloud computing should be built upon thebasis of natural language understanding, because theattainment of cloud computing should rely onlightweight devices (such as cell phones) to accessservices, and not on traditional facilities (such asheavyweight PCs).

Cloud computing can be regarded as the developmentof distributed processing, parallel processing, andnetwork computers, or even as a commercial productof computer science.Customers can access the cheap services delivered bycloud computing at any place (as long as they can seethe “sky”) and any time (unless a solar eclipse andpower outage occur simultaneously). It is exciting toforecast that only a laptop or cell phone is required toaccess a service through the Internet.

7. Conclusion:AI's scientific goal is to understand intelligence by

building computer programs that exhibit intelligentbehaviour. It is concerned with the concepts andmethods of symbolic inference, or reasoning, by acomputer, and how the knowledge used to makethose inferences will be represented inside themachine.

Of course, the term intelligence covers manycognitive skills, including the ability to solveproblems, learn, and understand language; AIaddresses all of those. But most progress to date in AIhas been made in the area of problem solving --concepts and methods for building programs thatreason about problems rather than calculate asolution.

Reference:

[1] Rich, Elaine, and Kevin Knight, (2006), “ArtificialIntelligence”, McGraw Hills Inc.

[2] Hyde, Andrew Dean (Sept 28, 2010), “The future ofArtificial Intelligence”.

[3] George F. Lunger, William A. Stubblefield (1993) ArtificialIntelligence – Structuresand Strategiew for Complex ProblemSolving, Benjamin-Cummings, Albuquerqe, ISBN ) 0-8053-4780-1.

[4] "Babura an, Rajang, (August 24, 2011)"The Rising CloudStorage Market Opportunity Strengthens Vendors,"InfoTech, ". It.tmcnet.com. 2011-08-24. Retrieved 2011-12-02.

[5] "Ostrich, Ken, (November 15, 2010) "ConvergedInfrastructure," CTO Forum, ". Thectoforum.com. 2010-11-15. Retrieved 2011-12-02.

[6] a b c d e (24 July 2011) "The NIST Definition of CloudComputing". National Institute of Science and Technology.

[7] Andy BechtolsheimChairman & Co-founder, AristaNetworks. November 12th, 2008.

[8] Encrypted Storage and Key Management for the cloud.

[9] http://www.cryptoclarity.com/CryptoClarityLLC/Welcome/Entries/2009/7/23_Encrypted_Storage_and_Key_Management_for_the_cloud.html.

[10] Mills, Elinor (2009-01-27). "Cloud computing securityforecast: Clear skies". CNET.

[11] "Service-Oriented Computing and Cloud Computing:Challenges and Opportunities". IEEE Internet Computing.Retrieved 2010-12-04.

[12] Encrypted Storage and Key Management for the cloud.Cryptoclarity.com. 2009-07-30.