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248 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 03, Issue 03, March, 2016

International Journal of Computer Systems (ISSN: 2394-1065), Volume 03 – Issue 03, March, 2016

Available at http://www.ijcsonline.com/

Opportunistic Virtual Probing Technique for Data Servers in Multi-Cloud

A. SELVAKUMAR, KAVITHAYENI K.

Department Computer Science and EngineeringChrist College of Engineering and Technology

Abstract

Cloud has become one of the variant access storage and retrieval network these days. Using a basic credential and user

information a user can process/request multiple data at a time. Due to increased server traffic concentration, the

possibility of serving a user in-time and constant traffic patterns in a cloud are being affected that are considered to bethe drawbacks in cloud concept. Though various optimization algorithms have been proposed for LB and to preserve

lossy connections recent approaches in HBLB have been admired in resource allocation and user in-time-service

metrics. Yet the fulfillment is restricted with one-time-resources fetch and refetching process of a vm after utilizing

resources. To minimize the re-use of resources and to avoid multiple agent access of a vm-resource, we propose a

“Probe based definite vm resource sharing method” to avoid complexity and time variant method of a cloud server in

optimization. Besides LB, a probabilistic resource best after fetch and release helps in preserving the reallocation ofthe resource before it is actually being dismissed.

Keywords: load balancing, virtual machine, traffic concentration, resources allocation, fetching, optimization.

I. I NTRODUCTION

Cloud computing is a new technology. It provides allthe data at a lower cost. In cloud computing users canaccess resources all the time through internet. They need to

pay only for those resources as much they use .In Cloudcomputing cloud provider outsourced all the resources to

their client. There are many existing issues in cloudcomputing. The main problem is load balancing in cloudcomputing. Load balancing helps to distribute all loads

between all the nodes. It also ensures that every computingresource is distributed efficiently and fairly. It helps in

preventing bottlenecks of the system which may occur dueto load imbalance. It provides high satisfaction to theusers. Load balancing is a relatively new technique that

provides high resource utilization and better responsetime[1].

Cloud computing and storage solution provide usersand enterprises with various capabilities to store and

process their data in third party data centers. It relies onsharing of resources to achieve coherence and economicsof scale. Cloud computing is a model for enablingconvenient, on-demand network access to a shared poolof configurable computing resources (e.g., networks,servers, storage, applications, and services) that can berapidly provisioned and released with minimalmanagement effort or service provider interaction. Thecloud model of computing promotes availability.

Cloud computing definition in various aspects: i) cloudcomputing is defined as a type of computing that relies onsharing computing resources rather than having local serveror personal device to handle application [2] ii) Cloudcomputing is a model for enabling ubiquitous networkaccess to a shared pool of configurable computingresources [3].

A. CLOUD COMPUTING MODEL

To need ever changing business needs organizationneed to invest time, budget, to scale up their ITinfrastructure such as hardware, software and services. Inon premises IT infrastructure the scaling process can beslow and organizations are frequently unable to achieveoptimal utilization of the IT infrastructure. Cloud

communication provides computing over the internet. Acommunication service consists of highly optimization datacenters that provide various software, hardware andinformation services/ resources for use. We neededorganization can simply connect to the cloud and use theavailable resources on the on pay for use basis. This helpscompany to avoid capital expenditure and additional on

premises infrastructure resources and instead of scale up orscale down according to business requirements. Thefollowing is the overall cloud computing model diagramwith its services and it’s on demand services. This causesthe storage space to be expandable. The layer and itsfunctionalities are explained with the offset demands [1].

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A. SELVAKUMAR et al Opportunistic Virtual Probing Technique for Data Servers in Multi-Cloud


B. TYPES OF CLOUD SERVICES

(i). Software as a Service (SaaS)

SaaS provided all the application to the consumerwhich is provided by the providers. Applications arerunning on a cloud infrastructure. Interfaces (web

browser) are used access the applications. The consumerdoes not control the internal function. The capability

provided to the consumer in this highest level is to use the provider’s applications running on a cloud infrastructure.The applications are accessible from various client devicesthrough a thin client interface such as a Web browser (e.g.,Web-based e-mail). The consumer does not manage orcontrol the underlying cloud infrastructure, includingnetwork, servers, operating systems, storage, or evenindividual application capabilities, with the possibleexception of limited user-specific application configurationsettings. That Customers who are not able to developedsoftware, but they need high level applications can also betake advantages from SaaS. There are some of applicationsof software of services. Customer resource management(CRM) Video conferencing, IT service management,Accounting, Web analytics, Web content management

Advantages

1. SaaS Cloud Providers often take into accountmultiple platforms: mobile, browser, and so on. If you oryour organization wants software that can be accessedfrom multiple platforms, this might be an easy way tomake that happen. As part of this, SaaS Cloud Providersmay also provide apps for mobile devices.

2. The SaaS Cloud Provider may provide bettersecurity than your existing software (security — orinadequate security — can also be a disadvantage). Bettersecurity may come in part because it is critical for the SaaSCloud Provider and is part of their main business. In-housesecurity, on the other hand, is not usually an individual's ora organization's main business and, therefore, may not beas good as that offered by the SaaS Cloud Provider.[4]

3. Platform as a Service (PaaS)

PaaS provides all the resources to the customers that arerequired for building applications. It provides all theservices on the internet .User not need to download andinstall the software. Consumers deploy all the applicationonto the cloud infrastructure. There are different tools and

programming languages are provided to the uses to developthe applications. The consumer does not control network,servers, operating systems, or storage. Consumer controlsall applications which they deploy.

The capability provided to the consumer in thisintermediate level is to deploy onto the cloudinfrastructure consumer created or acquired applicationsdeveloped using programming languages and toolssupported by the provider. The consumer does not manageor control the underlying cloud infrastructure, includingnetwork, servers, operating systems, or storage, but hascontrol over the deployed applications and possiblyapplication hosting environment configurations.

Advantages

1. The maintenance and upgrades of tools, databasesystems, etc. and the underlying infrastructure are theresponsibility of the PaaS Cloud Provider.

2. Various pricing models may allow paying only for

what you use. This, for example, can allow an individual ora small organization to use sophisticated developmentsoftware that they could not afford if it was installed on aninternal, dedicated server.[4]

3. Infrastructure as a Service (IaaS)

In this service consumer does not manage or control theunderlying cloud infrastructure. In infrastructure as aservice consumer able to control operating systems,storage, and all applications which they deployed. There isa limited control of customer on the networkingcomponents. Infrastructure Providers control storing and

processing capacity. Virtualization is used assign and

dynamically resizes these resources to build systems asdemanded by customers. Consumers deploy the softwarestacks that run their services. Provider provide network,services as on demand services. User use these servicesdirectly .It can be used to avoid buying, housing, andmanaging the basic hardware and software infrastructurecomponents, scales up and down quickly to meet demand.The capability provided to the consumer is to provision

processing, storage, networks, and other fundamentalcomputing resources where the consumer is able to deployand run arbitrary software, which can include operatingsystems and applications. The consumer does not manageor control the underlying cloud infrastructure but hascontrol over operating systems; storage, deployed

applications, and possibly limited control of selectnetworking components (e.g., host firewalls).

Advantages

1. Various pricing models may allow paying only firwhat we use. This, for example, can allow individual or asmall organization to use sophisticated developmentsoftware that they could not afford if it was installed on aninternal, dedicated server.

2. Some IaaS Providers provide development optionsfor multiple platforms: mobile, browser, and so on. If youor your organization wants to develop software that can beaccessed from multiple platforms, this might be an easy

way to make that happen [4].

C. TYPES OF CLOUD

1) Public Cloud: The cloud infrastructure is madeavailable to the general public or a large industry group andis owned by an organization .Anyone can use public cloudas they want without restriction[5].

2) Private Cloud: The cloud infrastructure is used by asingle organization. Private cloud is only managed by theorganization or a third party[5].

3) Community Cloud: The cloud infrastructure isshared by many organizations. Community cloud supportsa specific community that has shared concerns. Ex:-security requirements, policy, compliance considerations. Itmay be managed by the organizations or a third party[5].

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4) Hybrid Cloud: Hybrid cloud is a combination oftwo or more clouds (private, community, or public). Thatremains unique entities but is bound together bystandardized technology that enables data and application

portability. Ex: cloud bursting for load-balancing betweenclouds [5].

II. LOAD BALANCING TECHNIQUE

A. HONEY – BEE TECHNIQUE

Honey-bee based resource allocation has two stages.One is dancing phase and other is LB phase. In a dancing

phase, the agent map request handlers to each of theresources to fetch appropriate data to serve the request. Theagents make a traversal in the time lesser than the time out,to service the request. The LB phase is active when a serveris flooded due to unexpected fragments approaching theserver.

The response handler intimates the agent mapping unit

to initiate a virtual agent to share the requested resourcehandling from the server. After load has been distributed orshared between the agents (mapped and temporary agent),the resources is delivered to the user. Once the user port isclosed after reception, the temporary agent is diminished

by the mapping unit and an RSI (request statusinformation) is acknowledged back to the resource handlerunit.

An algorithm for load balancing in nimble peer-to-peersystem and adding together hybrid environments. In most

peer-to-peer system the non uniform of objects in the feeland with the load of the node can be distorted continuouslydue to the insertion, taking away and subsidiary various

operations. This will leads to fall the produce aconsequences of the system. So the concept of virtualserver can be introduced. The load hint of the peer nodes isstored in inconsistent directories in this proposed load

balancing algorithm. These directories in the back toschedule reassignment of the virtual servers to generate animproved relation. Greedy heuristic algorithm used tolocate out a bigger resolved for the proper utilization of thenodes.

The huge number of virtual servers in the system helpsto gathering the utilization. The various load counsel in tothe corresponding pool and with the virtual serverassignments are to be finished. This proposed algorithm

should be applied to every second types of resourcesassociated to storage, bandwidth etc, It was intended tohandle the various situations in imitation of changing loadof the node, node adroitness, entering and leaving of nodesand in addition to insertion and elimination of the nodes.Advantages are high node utilization and increasingscalability [6].

III. SYSTEM CONCEPT

Other than LB, in order to minimize the trafficconcentration at one particular server, the virtual agents areheld at each port of the request. The probe information andtraffic concentration are updated to the Agent MappingUnit. When the traffic concentration of a server exceeds its

saturated handling capacity, the ported virtual agent isinitiated to receive the information based on sharing. Thevirtual machine after completing the resource allocation,usually releases the connection. Here, we make an

opportunistic broadcast with a Probe Timer (PT) beforewhich the resources can be shared on request.

Probe time is the maximum active time after a resourceis being released from one request and is awaiting areleased time. If a request needs the balanced resource, but

its Probe Time exceeds the actual release time, the virtualmachine moves the resource to the local cloud storage. Thelocal storage sets a timed out condition for the started datawithin which it has to be served. Once the data is server,the local manager re-imbuses the stored data to the virtualmachine from which the release phase is continued. Ifnumber of request has approached a virtual machine withinthe Probe Time, then the virtual machine releases theresources.

The request handler on receiving the request from theend user. The request handler creates fetching agent (bees)for collecting data from the available resources. If therequested resources is available with the local storage, then

the resources handler flow the resources to the requesthandler and then to the end user. For accessing foreignresources, the request handler on creating bees, requests theagent unit for accessing foreignresources. The agent unitcreates a resolver to handle the foreign resource accessrequests. The foreign resource handler mapping unitallocates the vm to the forwarded bees. The vm broadcastsits active time (relieving time span) to the requesting bees.

Before the expiry time, the vm broadcasts its state tothe other agent in the network. If any agent wants to accessthe same resource as the first request then the vm extendsits expiry time in order to service the further requests.When the numbers of bees are maximum, then the vmchecks for the capacity of handling the bees and accepts thefollowing requests. The same condition is checked for theinferring servers to handle the load ubiquitously withoutcreating congestion. This result in seamless connectivitykeeping the link uptime constant. The vm resources afterfurther services can extent/shrink its expiry time based onthe availability of request. Through this, the bandwidthwastage is minimized by constantly maintaining theutilization of the links.

A. SYSTEM ARCHITECTURE

The system architecture consists of many blocks which

are used for individual purpose. First of all the end usersends some request, the request handler receives this

request and it will send the request to the agent actuator. In

this agent actuator there are two main components they are

Agent Pool and Service Mapping. It also has the

components such as local resource that are used for

fetching the resources that are needed by the end user.

Then comes the local balancer, it balance the load that are

going it fetches the data from the data base with the time

constraints with the help of time scheduler. Task object

send and receive the request from work station and

resources allocator. The resource allocator collects theresources and other things that the request is in need from

the database, vm tail, global or de-centralized blocks.

The Agent pool comprises of the following functions they

are agent creation and service agent. Once the agent is

created it will send the request in the form of services, this

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is handled by service agent. Allocation takes place and

then the task agent specifies the task that agent has to do

base on the pdf value and then it is received by request

handler from task agent. After the process are over then

status of the agent is displayed which is used for the

fetching or using this agent without the time delay. Once it

reaches the request handler then it is send to the task

object.

Once the request received to the task object, itautomatically fetches the resources that are asked for theresource. Then the loads are balanced by means of

creation of n number of agents to work with is based on

the input request. With respect to pdf value the agent is

allocated to the end user. In the task object the agent

allocation process is done along with the load balancing.

B. FLOWCHART

The flowchart for the proposed system is based on the

work flow of the process. The first step is to receive the

request from the end user then the agent is allocated if the

agent is busy it will wait for the acknowledgement from

the data center otherwise the process handler assign the

request to the resources handler. When the resources

handler is available then it will map to the resource then

the service request is made available to continue the

process. If the resource handler is not available then it

should request for a vm the data center fetch it to the local

vm handler. Then it will check whether the resource is

sufficient is yes then vm is shared to the global resource

and get the time slot for the best time of execution request

then it is mapped to its corresponding agent. On the other

hand after the request is mapped to the resources along

with the service handler. If the request is serviced then it

will release the process and also the resource of that agent.

Then reallocation is done after that the process is againcontinued for the other request.

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IV. CONCLUSION

The tasks are to be sending to the under loaded machine

and like foraging bee the next tasks are also sent to that

virtual machine till the machine gets overloaded as flower

patches exploitation is done by scout bees. Honey bee

behavior inspired load balancing improves the overallthroughput of processing and priority based balancing

focuses on reducing the amount of time a task has to waiton a queue of the VM. Thus, it reduces the response of

time of VMs. We have compared our proposed algorithm

with other existing techniques. Results show that our

algorithm stands good without increasing additional

overheads.

A. PARAMETER EVALUATION

(i) Resource Mapping in Load Balancing

(ii) Throughput

(iii) Bandwidth Utilization

(iv). Maximum Transfer Unit

(v) Buffer overhead

(vi) Resource mapping

R EFERENCES

[1] Won Kim, Department of Software Design & Management,Gachon University,Gyeonggi- do, South Korea, “International

Journal of Web and Grid Services”,volume 9, issue 3, August2013, pp 287-303.

[2] http://www.webopedia.com/TERM/C/cl oud_computing.html

[3] Peter Mell, Timothy Grance, Recommendations of the NationalInstitute of Standards and Technology , September 2011.

[4] Grosu, D., Das, A., “Auction-Based Resource AllocationProtocols In Grids”, 16th Iasted International Conference OnParallel And Distributed Computing And Systems, 2004

[5] http://www.servicearchitecture.com/articles/cloudcomputing/cloud_computing_defi nition.html

[6] Harshit Gupta , Kalicharan Sahu, “International Journal of Scienceand Research(IJSR)”, Volume 3, Issues 6,June 2014, pp 843-845.

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