Study of the Impact of Self-Similarity on the Network Node Traffic

L. Kaklauskas, L. Sakalauskas
2011 Elektronika ir Elektrotechnika  
Introduction Numerous network traffic research works [1] [2] [3] show that Ethernet networks traffic characteristics have fractal and self-similarity properties with a long-range dependence. The research of self-similarity of networks [1, 3, 4] allows us to predict a change in the flow and to ensure the service's quality [5] [6] . The empirical research of university e-studies network traffic confirmed its selfsimilarity property. The analysis of e-studies network has shown that overflows often
more » ... hat overflows often occur in it [8]. [9] have found that, in the high network traffic, LIFO front drop (when the queue is full for a longer time, former applications are eliminated and new applications are taken) has a more than twice shorter delay than the FIFO tail drop (when the queue is full, new applications are eliminated). [10-12] analysed the optimal queue length. It has been found that the node services with high-speed (about 30 Gb/s) and throughput networks are enough for the 15-20 data packets' queue. It should be noted that there is no exhaustive research pursuing to estimate the impact of the queue discipline and network traffic properties on the network node traffic service. This research focuses on design of appropriate network node parameters when network traffic is selfsimilar. Theoretical justification of the network model The quality of service (QoS) has two components: performance assurance and service differentiation [13] . The component performance assurance directly relates with a bandwidth which affects delay, jitter and packet loss. Our aims are to establish conditions when application's delay and loss are minimal, by analysing the network traffic properties and node parameters and evaluating the offered traffic jitter and service system's throughput. In this article, we do not analyse service differentiation by applying different service requirements to different services. The network model's investigation is based on a stochastic Network Calculus which allows us to analyse end-to-end network QoS systems with a stochastic network traffic and stochastic network nodes. The deterministic network services' theory has been created by Cruz, Chang, Boudec, Thiran and others [14] [15] [16] . This theory was extended in 2008 by Jiang and Liu who wrote a book where stochastic offered and served traffic characteristics are analysed [17] . Our system uses the communication network model for generalised stochastically bounded bursty traffic created by J. Jiang, Q. Yin, Y. Liu and S. Jiang [18] . In this model, both offered and served traffics are independent and stochastic, the network node buffer capacity is determined and finite, the network node is ready for service for the next application when the buffer is empty and the network node doesn't serve any other data packet. The network gets started at time t=0. The network traffic amount arriving in the time interval (s,t] is
doi:10.5755/j01.eee.111.5.350 fatcat:k36s37nzwvcj3n32ezik5rmcay