* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Load Balancing Performance in Content Delivery Networks (CDN`s)
Survey
Document related concepts
Video on demand wikipedia , lookup
Computer network wikipedia , lookup
Network tap wikipedia , lookup
Wireless security wikipedia , lookup
Piggybacking (Internet access) wikipedia , lookup
Dynamic Host Configuration Protocol wikipedia , lookup
Airborne Networking wikipedia , lookup
Distributed firewall wikipedia , lookup
Remote Desktop Services wikipedia , lookup
Cracking of wireless networks wikipedia , lookup
List of wireless community networks by region wikipedia , lookup
Zero-configuration networking wikipedia , lookup
Transcript
ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) IJCST Vol. 5, Issue 4, Oct - Dec 2014 Load Balancing Performance in Content Delivery Networks (CDN’s) 1 Kanthai Srinivasa Rao, 2Manjula Srinivas, 3Molli Srinivasa Rao 1,2,3 Dept. of CSE, VITAM College of Engineering, Andhra Pradesh, India Abstract It is an interesting issue of describing and executing an effective law for load balancing in Content Delivery Networks (CDNs). A CDN system conceded out through the exploitation of a fluid flow model classification of the network of servers. Beginning from such categorization, we develop and demonstrate a lemma about the network queues balance. The result is then leveraged in mandate to create a novel distributed and time-continuous algorithm for load balancing which is also reformulated in a timediscrete form. The isolated devising of the proposed balancing law is ultimately deliberated in terms of its definite application in a realworld consequence. Lastly, the complete method is authenticated by means of imitations. Keywords Content Delivery Network (CDN), Control Theory, Request Balancing I. Introduction A CDN contains of a unique server called as back-end server comprising new data to be dispersed together with one or more dissemination servers called as surrogate servers. The surrogate servers are dynamically efficient by the back-end server. Surrogate servers are characteristically used to store static data, while dynamic information (i.e., data that change in time) is just stored in a small number of back-end servers. In some characteristic situations, there is a server called redirector, which dynamically redirects client requests based on designated policies. The furthermost important performance enhancements derived from the adoption of such a network concern two aspects. Firstly, overall system amount that is the average number of requests served in a time unit which is improved also on the basis of the processing capabilities of the available servers. Secondly, response time proficient by clients after issuing a request. II. Related Work Active load-balancing approaches characterise a valid substitute to static algorithms. Such methods make use of information approaching either from the network or from the servers in order to advance the request assignment process. The selection of the suitable server is done through a assortment and succeeding analysis of various parameters extracted from the network elements. Depending on how the scheduler interrelates with the other mechanisms of the node, it is conceivable to classify the balancing algorithms in three fundamental models a queueadjustment model, a rate-adjustment model and a hybridadjustment model. III. Existing Method In a rate-adjustment model, in its place the scheduler is situated just before the local queue. As per the new request the scheduler chooses whether to allocate it to the local queue or send it to a remote server. In a hybrid-adjustment approach for load balancing, the scheduler is permitted to switch both the inward appeal rate at a node and 148 International Journal of Computer Science And Technology the local queue length. Therefore in Existing systems, a new request indeed a CDN server can both intricate locally the request or forward it to other servers according to a definite decision rule which is grounded on the state information swapped by the servers. Such a method bounds state switching above to fair local servers. IV. Disadvantages A precarious constituent of CDN design is the request routing mechanism. It permits to direct user requests for content to the appropriate server based on a specified set of parameters. The routing process related with a request might take into account various constraints like traffic load, bandwidth, and servers’ computational capabilities in order to deliver the best performance in terms of time of service, delay, etc. V. Proposed Method An appropriate load-balancing law that promises equilibrium of the queues in a balanced CDN by means of a fluid flow model for the network of servers. We present a new mechanism for readdressing inward customer requirements to the furthermost suitable server, thus corresponding the overall system requests load. The mechanism leverages local balancing in demand to attain global balancing. This is carried out through a periodic collaboration among the system nodes. VI. Advantages The outstanding performance of mechanism might be paid in terms of an important number of redirections. Subsequently the redirection process is communal to all the algorithms analyzed, we completely appraise the proportion of requests redirected more than once over the total number of requests generated. VII. Content Delivery Network Fig. 1: VIII. Modules A. Network Formation The Content Delivery Network is formed in network formation module. The network comprise back end server, redirect server, number of surrogate server and number of client. Every client links with one surrogate server. The Back end server uphold all server as redirect and surrogate server. w w w. i j c s t. c o m ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) B. Fluid Queue Model Every server preserve an own queue for unloading the client request. Let qi(t) be the queue occupancy of server i at time t. Study the instant arrival rate αi(t) and the instant service rate δi(t). The fluid model of CDN servers queues is given by C. Load Balance The client sends the request to the server. The server initially check the queue, if queue limit exceeds it redirect the server to others, else it respond the user request. Each T seconds, the server directs its status information to its neighbors and at the same time waits for their information. When a new request attains at a server, it confirms the presence of neighbors with a lower load. If no such neighbors are present, the server locally procedures the request and serves it; otherwise the balancing strategy is implemented. For requests rearrangement, we implement a random number generator with identical distribution between 0 and 1. Conditional on which interval the generated number falls in, the algorithm selects the corresponding peer for redirecting the incoming request. Algorithm Used Distributed Load-Balancing Algorithm w w w. i j c s t. c o m IJCST Vol. 5, Issue 4, Oct - Dec 2014 X. Conclusion Characterisation of an algorithm that objectives at achieving load balancing in the network by eliminating local queue instability conditions through redeployment of potential excess traffic to the set of neighbours of the crowded server. The algorithm is first presented in its time-continuous formulation and then put in a discrete version precisely conceived for its actual execution and deployment in an operational scenario. The present work signifies for us a first step to the consciousness of a complete solution for load balancing in a cooperative, distributed environment. References [1] S. Manfredi, F. Oliviero, S. P. Romano,“Distributed management for load balancing in content delivery networks”, in Proc. IEEE GLOBECOM Workshop, Miami, FL, Dec. 2010, pp. 579–583. [2] H. Yin, X. Liu, G. Min, C. Lin,“Content delivery networks: A Bridge between emerging applications and future IP networks”, IEEE Netw., Vol. 24, No. 4, pp. 52–56, Jul.–Aug. 2010. [3] J. D. Pineda, C. P. Salvador,“On using content delivery networks to improve MOG performance”, Int. J. Adv. Media Commun., Vol. 4, No. 2, pp. 182–201, Mar. 2010. [4] D. D. Sorte, M. Femminella, A. Parisi, G. Reali,“Network delivery of live events in a digital cinema scenario”, In Proc. ONDM, Mar. 2008, pp. 1–6. [5] Akamai,“Akamai”, 2011 [Online] Available: http://www. akamai. com/index.html [6] Limelight Networks,“Limelight Networks”, 2011 [Online] Available: http://.uk.llnw.com [7] CDNetworks,“CDNetworks”, 2011 [Online] Available: http://www.us.cdnetworks.com/index.php [8] Coral,“The Coral Content Distribution Network”, 2004 [Online] Available: http://www.coralcdn.org [9] Network Systems Group,“Projects”, Princeton University, Princeton, NJ, 2008. [Online] Available: http://nsg. cs.princeton.edu/projects [10]A. Barbir, B. Cain, R. Nair,“Known content network (CN) re- quest-routing mechanisms”, IETF, RFC 3568 Internet Draft, Jul. 2003, [Online] Available: http://tools.ietf.org/html/ rfc3568 [11] T. Brisco,“DNS support for load balancing”, IETF, RFC 1794 In- ternet Draft, Apr. 1995 [Online] Available: http:// www.faqs.org/rfcs/rfc1794.html [12]M. Colajanni, P. S. Yu, D. M. Dias,“Analysis of task assignment policies in scalable distributed Web-server systems”, IEEE Trans. Parallel Distrib. Syst., Vol. 9, No. 6, pp. 585–600, Jun. 1998. [13]D. M. Dias, W. Kish, R. Mukherjee, R. Tewari,“A scalable and highly available Web server”, In Proc. IEEE Comput. Conf., Feb. 1996. International Journal of Computer Science And Technology 149 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) IJCST Vol. 5, Issue 4, Oct - Dec 2014 Kanthai Srinivasa Rao is pursuing his M.Tech in Computer Science and Engineering from VITAM College of Eng affiliated to JNTU Kakinada. He received his B.Tech degree from Avanthi Institute of Engineering & Technology JNTU Hyderabad, Andhra Pradesh, India. His research interests include computer and network security. Manjula Srinivas. She received her M.Tech in Computer Science and Engineering from Avanthi Institute of Engineering & Technology, Vizianagaram in 2012. She received her B.E from K.V.G. College of Engineering,Sullia, Karnataka State. She is currently working as Assistant Professor, CSE Dept. in VITAM College of Engg., Andhra Pradesh, India. Her research interests include computer network architectures, algorithms and protocols, Sensor Networks,mobile Ad-hoc Networks,Wireless Mesh Networks, computer and network security. Molli Srinivasa Rao is pursuing his Ph.D from Andhra University. He received his M.Tech in Computer Science and Technology from Andhra University in 2003. He received his B.Tech degree from C.B.I.T., Hyderabad in 2001. He is currently working as Associate Professor, CSE Dept. in VITAM College of Engg., Andhra Pradesh, India. His Research Interests include mobile Ad-hoc Networks, Sensor Networks,Wireless Mesh Networks, computer and network security. 150 International Journal of Computer Science And Technology w w w. i j c s t. c o m