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Two Techniques for Fast Computation of Constrained Shortest Paths

Abstract:

         Computing constrained shortest paths is fundamental to some important network functions such as QoS routing, MPLS path selection, ATM circuit routing, and traffic engineering. The problem is to find the cheapest path that satisfies certain constraints. In particular, finding the cheapest delay-constrained path is critical for real-time data flows such as voice/video calls. Because it is NP-complete, much research has been designing heuristic algorithms that solve the -approximation of the problem with an adjustable accuracy. A common approach is to discretize (i.e., scale and round) the link delay or link cost, which transforms the original problem to a simpler one solvable in polynomial time. The efficiency of the algorithms directly relates to the magnitude of the errors introduced during discretization. In this paper, we propose two techniques that reduce the discretization errors, which allow faster algorithms to be designed. Reducing the overhead of computing constrained shortest paths is practically important for the successful design of a high-throughput QoS router, which is limited at both processing power and memory space. Our simulations show that the new algorithms reduce the execution time by an order of magnitude on power-law topologies with 1000 nodes.

Existing System:

  • Existing system uses RTF and RTC built up for discretization error along a path.
  • Here efficiency of the algorithms directly relates to the magnitude

      of the errors introduced during discretization .
         
                       
Proposed System:

  • In our project we use two techniques to decrease the discretion error.
  • Here we use randomized discretization and path delay discretization techniques.
  • The above new techniques either make the link errors to cancel out each       other along the path or treat the path delay as a whole for discretization, which results in much smaller errors.
  • The algorithms based on these techniques run much faster than the best existing algorithm

System Requirements:

Hardware:

PROCESSOR          :  PENTIUM IV 2.6 GHz
RAM                       :  512 MB DD RAM
MONITOR              :  15” COLOR
HARD DISK             :  20 GB
CDDRIVE               :  LG 52X
KEYBOARD            :  STANDARD 102 KEYS
    MOUSE                :  3 BUTTONS

Software:

FRONT END                    :  SWINGS,JFRAMEBUILDER.
OPERATING SYSTEM   :  Window’s Xp
                        BACK END                       : Sql Server  2000


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