Wireless Sensor Network Using Cloud Computing Information Technology Essay
Popularity of cloud computer science is increasing twenty-four hours by twenty-four hours in distributed computer science environment. There is a turning tendency of utilizing cloud environments for storage and informations processing demands. Cloud calculating provides applications, platforms and substructure over the cyberspace. It is a new epoch of mentioning to entree shared computing resources. On the other manus, radio detector webs have been seen as one of the most indispensable engineerings for the twenty-first century where distributed spatially connected detector node automatically forms a web for informations transmittal and have among themselves is popularly known as Sensor Network. For security and easy entree of informations, cloud computer science is widely used in distributed/mobile calculating environment. This is possible due to miniaturisation of communicating engineering. Many research workers have cited different types of engineering in this context. But the application scenario are of of import consideration while planing a specific protocol for Sensor web with mention to Cloud Computing. In this paper, we surveyed some typical applications of Sensor Network utilizing Cloud calculating as anchor. Since Cloud calculating provides plentifulness of application, platforms and substructure over the Internet ; it may combined with Sensor web in the application countries such as environmental monitoring, conditions prediction, transit concern, health care, military application etc. Bringing assorted WSNs deployed for different applications under one roof and looking it as a individual practical WSN entity through cloud calculating substructure is fresh.
Index Terms-Cloud Computing, Distributed Computing, Internet, Sensor Network, WSN
The communicating among sensor nodes utilizing Internet is frequently a ambitious issue. It makes a batch of sense to incorporate detector webs with Internet [ 1 ] . At the same clip the informations of detector web should be available at any clip, at any topographic point. It is perchance a hard issue to delegate reference to the detector nodes of big Numberss ; so sensor node may non set up connexion with cyberspace entirely. Cloud calculating scheme can assist concern organisations to carry on their nucleus concern activities with less fuss and greater efficiency. Companies can maximise the usage of their bing hardware to program for and function specific extremums in use. Thousands of practical machines and applications can be managed more easy utilizing a cloud-like environment. Businesss can besides salvage on power costs as they cut down the figure of waiters required.
Fig.1 consists of WSNs ( i.e. WSN1, WSN2, and WSN3 ) , cloud substructure and the clients. Clients seek services from the system. WSN consists of physical radio detector nodes to feel different applications like Transport Monitoring, Weather Forecasting, and Military Application etc. Each detector node is programmed with the needed application. Sensor node besides consists of operating system constituents and web direction constituents. On each detector node, application plan senses the application and sends back to gateway in the cloud straight through base station or in multi-hop through other nodes. Routing protocol plays a critical function in pull offing the web topology and to suit the web kineticss. Cloud provides on-demand service and storage resources to the clients. It provides entree to these resources through cyberspace and comes in ready to hand when there is a sudden demand of resources.
The organisation of our work is as follows. In Section 2 & A ; Section 3 we have presented an overview of Clouds and Sensor Network. In subdivision 4 we have discussed assorted application scenarios of Sensor Network utilizing Cloud Computing. Last, Section 5 concludes our work.
Fig. 1 WSN- Cloud Computing Platform
II. Cloud: Overview
Cloud computer science is a term used to depict both a platform and type of application. A cloud calculating platform dynamically commissariats, configures, reconfigures waiters as needed. Waiters in the cloud can be physical machines or practical machines. It is an option to holding local waiters handle applications. The terminal users of a cloud calculating web normally have no thought where the waiters are physically located-they merely whirl up their application and get down working. Advanced clouds typically include other calculating resources such as storage country webs ( SANs ) , web equipment, firewall and other security devices. Cloud calculating besides describes applications that are extended to be accessible through the Internet. These cloud applications use big informations centres and powerful waiters that host Web applications and Web services. Anyone with a suited Internet connexion and a standard browser can entree a cloud application.
Many formal definitions have been proposed in both academe and industry, the one provided by U.S. NIST ( National Institute of Standards and Technology ) [ 2 ] appears to include cardinal common elements widely used in the Cloud Computing community:
Cloud computer science is a theoretical account for enabling convenient, on demand web entree to a shared pool of configurable calculating resources ( e.g. , webs, waiters, storage, applications, and services ) that can be quickly provisioned and released with minimum direction attempt or service supplier interaction [ 2 ] .
The followers are the indispensable characteristics of cloud computer science:
Service on demand: The petition of the clients to avail resources can be fulfilled automatically without human interaction.
Elasticity of demand: There is no formal understanding or contract on the clip period for utilizing the resources. Clients can utilize the resources whenever they want and can let go of when they finish.
Abstraction: Resources are hidden to clients. Clients can merely utilize the resources without holding cognition sing location of the resource from where informations will be retrieved and where informations will be stored.
Network entree: The client application can execute in assorted platform with the aid of nomadic phone, laptop and PDA utilizing a unafraid cyberspace connexion.
Service measuring: Although calculating resources are pooled and shared by multiple clients ( i.e. multi-tenancy ) , the Cloud substructure can mensurate the use of resources for each single consumer through its metering capablenesss.
Resource pooling: The resources are dynamically assigned as per clients ‘ demand from a pool of resources [ 2 ] .
The cloud provides following three services:
SaaS ( Software as a Service ) : This theoretical account provides services to clients on demand footing. A individual case of the service runs on the cloud can function multiple terminal user. No investing is required on the client side for waiters and package licences. Google is one of the service suppliers of SaaS.
PaaS ( Platform as a Service ) : This theoretical account provides package or development environment, which is encapsulated & amp ; offered as a service and other higher degree applications can work upon it. The client has the freedom to make his ain applications, which run on the supplier ‘s substructure. PaaS suppliers offer a predefined combination of OS and application waiters. Google ‘s App Engine is a popular PaaS illustration.
3 ) IaaS ( Infrastructure as a Service ) : This theoretical account provides basic storage and calculating capablenesss as standardised services over the web. Waiters, storage systems, networking equipment, informations centre infinite etc. are pooled and made available to manage work loads. The client would typically deploy his ain package on the substructure. The common illustration of IaaS is Amazon.
C. Cloud Computing Models
The undermentioned theoretical accounts are presented by sing the deployment scenario:
Private Cloud: This cloud substructure is operated within a individual organisation, and managed by the organisation or a 3rd party irrespective of its location. The aim of puting up a private cloud in an organisation is to maximise and optimise the use of bing in-house resources, supplying security and privateness to informations and lower informations transportation cost [ 3 ] from local IT substructure to a Public Cloud.
Public Cloud: Public clouds are owned and operated by 3rd parties. All clients portion the same substructure pool with limited constellation, security protections, and handiness discrepancies. These are managed and supported by the cloud supplier.
Community Cloud: This cloud substructure is constructed by figure of organisation jointly by doing a common policy for sharing resources. The cloud substructure can be hosted by a third-party seller or within one of the organisations in the community.
Hybrid Cloud: The combination of public and private cloud is known as intercrossed cloud. In this theoretical account, service suppliers can use 3rd party Cloud Providers in a full or partial mode so that the flexibleness for utilizing the resources are increased.
III. Sensor Network: overview
A radio detector web ( WSN ) consists of spatially distributed independent detectors to hand in glove supervise physical or environmental conditions, such as temperature, sound, quiver, force per unit area, gesture or pollutants. [ 4,5 ] The development of radio detector webs was motivated by military applications such as battleground surveillance. They are now used in many industrial and civilian application countries, including industrial procedure monitoring and control, machine wellness monitoring [ 6 ] , environment and home ground monitoring, health care applications, place mechanization, and traffic control [ 4, 7 ] .Each node in a detector web is typically equipped with a wireless transceiver or other wireless communications device, a little microcontroller, and an energy beginning, normally a battery. The size of detector node may change from shoebox down to a grain of dust. The cost of detector nodes is besides varies from 100s of dollars to a few pennies, depending on the size of the detector web and the complexness required of single detector nodes [ 4 ] . Size and cost restraints on detector nodes result in matching restraints on resources such as energy, memory, computational velocity and bandwidth [ 4 ] .
A detector web is a computing machine web Composed of a big figure of detector nodes. [ 8 ] The detector nodes are dumbly deployed inside the phenomenon, they deploy random and have concerted capablenesss. Normally these devices are little and cheap, so that they can be produced and deployed in big Numberss, and so their resources in footings of energy, memory, computational velocity and bandwidth are badly constrained. There are different Detectors such as force per unit area, accelerometer, camera, thermic, mike, etc. They monitor conditions at different locations, such as temperature, humidness, vehicular motion, lightning status, force per unit area, dirt make-up, noise degrees, the presence or absence of certain sorts of objects, mechanical emphasis degrees on affiliated objects, the current features such as velocity, way and size of an object. Normally these Sensor nodes consist there constituents: detection, processing and pass oning [ 9 ] . The development of detector webs requires engineerings from three different research countries: detection, communicating, and calculating ( including hardware, package, and algorithms ) . Therefore, combined and separate promotions in each of these countries have driven research in detector webs. Examples of early detector webs include the radio detection and ranging webs used in air traffic control. The national power grid, with its many detectors, can be viewed as one big detector web. These systems were developed with specialised computing machines and communicating capablenesss, and before the term “ detector webs ” came into trend.
Following are the of import footings which are used widely in detector web:
Detector: A transducer that converts a physical phenomenon such as heat, visible radiation, sound or gesture into electrical or other signal that may be farther manipulated by other setup.
Sensor node: A basic unit in a detector web, with processor, memory, radio modem and power supply.
Network Topology: A connectivity graph where nodes are sensor nodes and borders are communication links.
Routing: The procedure of finding a web way from a beginning node to its finish.
Resource: Resource includes detectors, communicating links, processors and memory and node energy.
Data Storage: The run-time system support for detector web application. Storage may be local to the node where the information is generated, burden balanced across a web, or anchored at a few points.
B. Routing Protocols in WSNs
Routing protocols in WSNs are loosely divided into two classs: Network Structure based and Protocol Operation based. Network Structure based routing protocols are once more divided into flat-based routing, hierarchical-based routing, and location-based routing. Protocol Operation based are once more divided into Multipath based, Query based, QoS based, Coherent based and Negotiation based.
In flat-based routing, all nodes are typically assigned equal functions or functionality detector nodes collaborate together to execute the detection undertaking. Due to the big figure of such nodes, it is non executable to delegate a planetary identifier to each node. The illustrations of flat-based routing protocols are -SPIN [ 10,11 ] , Directed Diffusion [ 12 ] , Rumor Routing [ 13 ] , MCFA [ 14 ] , GBR [ 15 ] , IDSQ & A ; CADR [ 16 ] , COUGAR [ 17 ] , ACQUIRE [ 18 ] , Energy Aware Routing [ 19 ] etc.
In hierarchical-based or bunch based routing, nodes will play different functions in the web. In a hierarchal architecture, higher energy nodes can be used to treat and direct the information while low energy nodes can be used to execute the detection in the propinquity of the mark. This means that creative activity of bunchs and delegating particular undertakings to constellate caputs can greatly lend to overall system scalability, life-time, and energy efficiency. Hierarchical routing is an efficient manner to take down energy ingestion within a bunch and by executing informations collection and merger in order to diminish the figure of familial messages to the BS. Hierarchical routing is chiefly two-layer routing where one bed is used to choose bunch caputs and the other bed is used for routing. The illustrations of hierarchical-based routing protocols are – LEACH [ 20 ] , PEGASIS [ 21 ] , TEEN [ 22 ] , APTEEN [ 23 ] , MECN [ 24 ] , SMECN [ 25 ] , SOP [ 26 ] , Sensor Aggregate routing [ 27 ] , vga [ 28 ] , hpar [ 29 ] , TTDD [ 30 ] etc.
In location-based routing, detector nodes ‘ places are exploited to route informations in the web. In this sort of routing, detector nodes are addressed by agencies of their locations. The distance between neighbouring nodes can be estimated on the footing of incoming signal strengths. Relative co-ordinates of neighbouring nodes can be obtained by interchanging such information between neighbours [ 37, 38, 39 ] . Alternatively, the location of nodes may be available straight by pass oning with a orbiter, utilizing GPS ( Global Positioning System ) , if nodes are equipped with a little low power GPS receiving system [ 40 ] . The illustrations of location-based routing protocols are – GAF [ 31 ] , GEAR [ 32 ] , GPSR [ 33 ] , MFR, DIR, GEDIR [ 34 ] , GOAFR [ 35 ] , SPAN [ 36 ] etc.
In multipath routing, communicating among nodes utilizations multiple waies to heighten the web public presentation alternatively of individual way. In Query based routing, the finish nodes propagate a question for informations from a node through the web and a node holding this information sends the information which matches the question back to the node, which initiates the question. Normally these questions are described in natural linguistic communication, or in high-ranking question linguistic communications. In QoS-based routing protocols, the web has to equilibrate between energy ingestion and informations quality. The web has to fulfill certain QoS prosodies, e.g. , hold, energy, bandwidth, etc for presenting informations to the BS. In coherent routing, the information is forwarded to collectors after minimal processing. The minimal processing typically includes undertakings like clip stamping, duplicate suppression, etc. In Negotiation based routing, protocols use high degree informations forms in order to extinguish excess informations transmittals through dialogue. Communication determinations are besides taken based on the resources that are available to them.
IV. Application Scenarios
Uniting WSNs with cloud makes it easy to portion and analyse existent clip detector informations on-the-fly. It besides gives an advantage of supplying detector informations or sensor event as a service over the cyberspace. The footings Sensing as a Service ( SaaS ) and Sensor Event as a Service ( SEaaS ) are coined to depict the procedure of doing the detector informations and event of involvements available to the clients severally over the cloud substructure.
Unifying of two engineerings makes sense for big figure of application. Some applications of detector web utilizing cloud calculating are explained below:
D. Transport Monitoring
Transport monitoring system includes basic direction systems like traffic signal control, pilotage, automatic figure home base acknowledgment, toll aggregation, exigency vehicle presentment, dynamic traffic light etc. [ 42 ] .
In conveyance monitoring system, detectors are used to observe vehicles and control traffic visible radiations. Video cameras are besides used to supervise route sections with heavy traffic and the pictures are sent to human operators at cardinal locations. Detectors with embedded networking capableness can be deployed at every route intersection to observe and number vehicle traffic and estimation its velocity. The detectors will pass on with neighbouring nodes to finally develop a “ planetary traffic image ” which can be queried by users to bring forth control signals. Data available from detectors is acquired and transmitted for cardinal merger and processing. This information can be used in a broad assortment of applications. Some of the applications are – vehicle categorization, parking counsel and information system, hit turning away systems, electronic toll Gatess and automatic route enforcement.
In the above scenarios, both the applications require storage of informations and immense computational rhythms. They besides require analysis and anticipation of informations to bring forth events. Entree to this information is limited in both the instances. Integrating these WSN applications with the cloud calculating substructure will ease the direction of storage and computational resources. It besides provides an betterment on the application informations over the cyberspace through web.
Sensor webs are used in the armed forces for Monitoring friendly forces, equipment and ammo, Battlefield surveillance, Reconnaissance of opposing forces, Targeting, Battle harm appraisal and Nuclear, biological and chemical onslaught sensing reconnaissance etc [ 43 ] .
The informations collected from these applications are of greatest importance and needs top degree security which may non be provided utilizing normal internet connectivity for security ground. Cloud computer science may be one of the solution for this job by supplying a unafraid substructure entirely for military application which will be used by merely Defense Purpose.
Weather prediction is the application to foretell the province of the ambiance for a future clip and a given location. Weather monitoring and prediction system typically includes- Data aggregation, Data assimilation, Numerical conditions anticipation and Forecast presentation [ 41 ] .
Each conditions station is equipped with detectors to feel the undermentioned parameters-wind speed/direction, comparative humidness, temperature ( air, H2O and dirt ) , barometric force per unit area, precipitation, dirt wet, ambient visible radiation ( visibleness ) , sky screen and solar radiation. The informations collected from these detectors is immense in size and is hard to keep utilizing the traditional database attacks. After roll uping the information, assimilation procedure is done. The complicated equations that govern how the province of the ambiance alterations ( weather prognosis ) with clip require supercomputers to work out them.
Sensor webs are besides widely used in wellness attention country. In some modern infirmary detector webs are constructed to supervise patient physiological informations, to command the drug disposal path and proctor patients and physicians and inside a infirmary.
In the above scenario, the informations collected from the patients are really sensitive and should be maintained decently as collected informations are required by the physicians for their future diagnosing. In traditional attack the patient ‘s history database is maintained in the local nursing place. So reputed physicians who are specially invited from abroad to manage critical instances can non analyse the patient ‘s disease often. They will merely do diagnosing when they will see the peculiar nursing place. This job may be solved by organizing a cloud where the critical information of the patients can be maintained and authorized physicians sitting in abroad can analyse the informations and give proper intervention.
The communicating among sensor nodes utilizing Internet is a disputing undertaking since detector nodes contain limited set breadth, memory and little size batteries. The issues of storage capacity may be overcome by widely used cloud calculating technique. In this paper, we have discussed some issues of cloud calculating & A ; detector web. To develop a new protocol in detector web, the specific application oriented scenarios are of of import consideration. Keeping this in head we have discussed some application of Sensor Network utilizing Cloud Computing.
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Sanjit Kumar Dash received the B.Tech. grade in Information Technology from Biju Patnaik University of Technology, Orissa, India, in 2004 and prosecuting M.Tech. grade in Computer Science and Engineering at Institute of Technical Education and Research, Bhubaneswar, India. He is besides working as a module member at the Information Technology Department, College of Engineering and Technology, Bhubaneswar, India. His research involvements include Cloud Computing, Sensor Network, and Mobile Computing.
Subasish Mohapatra received the B.Tech. grade in computing machine scientific discipline and technology from Biju Patnaik University of Technology, Orissa, India, in 2003 and the M.Tech. grade in computing machine scientific discipline and information engineering from College of Engineering and Technology, Bhubaneswar, India, in 2007. He was a module member at the Computer Science and Engineering Department, College of Engineering and Technology, Bhubaneswar, India, during 2004-2009. Presently, he is an Assistant Professor at the Department of Computer Science and Engineering at the Institute of Technical Education and Research, Bhubaneswar, India. His research involvements include Virtualization, Ad-hoc Network, and Sensor Network.
Prasant Kumar Pattnaik, M.Tech, PhD. At present working as a Professor and Head of Department of Computer Science and Engineering at Konark Institute of Science and Technology, Bhubaneswar, India. He is a senior member of International Association of Computer Science and Information Technology, Singapore. His research involvements include Ad-hoc and Sensor Network.