Real-time Multimedia Networks Research Articles

Multicast routing for delay variation bound using a modified ant colony algorithm

The delay and delay variation-bounded Steiner tree problem is an important multicast routing problem in real-time multimedia networks. Such a constrained Steiner tree problem is known to be NP-complete. This paper proposes an ant colony algorithm with orientation factor and applies it to multicast routing problem with the constraints of delay variation bound. The orientation factor enables the ant to get rid of the initial blindness when searching paths, makes use of the search results and reduces the misguiding effect of pheromone on irrelevant paths, thus overcoming the drawbacks of slow convergence existing in the basic ant colony algorithm, increasing the speed of convergence and speeding up the finding of feasible solution to the problem. The simulation results show that the modified algorithm makes it possible to find a feasible solution to the multicast routing problem with delay variation bound. Compared with the conventional ant colony algorithm, the convergence speed of the modified algorithm is improved.

Dynamic multicast routing algorithm for delay and delay variation-bounded Steiner tree problem

The delay and delay variation-bounded Steiner tree problem is an important problem in real-time multimedia networks, and is known to be NP-complete. In this paper, we propose an efficient heuristic multicast routing algorithm based on simulated annealing named SADDVMA to construct the constrained Steiner tree. To avoid enlargement of search area and increase of computing time, the proposed heuristic algorithm uses a procedure called Paths-switching to construct neighbors in feasible region according to the relationship between delay and delay variation. We also give a method to dynamically reorganize the multicast tree in response to changes for the destinations. Simulations demonstrate that our algorithm is better in terms of tree cost as compared to the existing algorithms. Further, it performs excellent performance of delay and delay variation, rapid convergence and better real-time property.

A GRASP heuristic for the delay-constrained multicast routing problem

The increasing development of real-time multimedia network applications, many of which require multiple participants, has created the need for efficient multicast routing algorithms. Examples of such applications include video and tele-conferencing, video-on-demand, tele-medicine, distance education, etc. Several of them require multicasting with a certain Quality of Service (QoS) with respect to elements such as delay or bandwidth. This paper deals with Delay-Constrained Multicast Routing (DCMR) where the maximum end-to-end delay in a multicast session is bounded. The DCMR problem can be reduced to the Constrained Minimum Steiner Tree Problem in Graphs (CMStTG) which has been proven to be NP-complete. As a result, several heuristics have been developed to help solve it. In this paper, we developed a GRASP heuristic for the DCMR problem. Computational experiments on medium sized problems (50-100 nodes) from literature and comparison with existing algorithms have shown that the suggested GRASP heuristic is superior in quality for this set of problems.

Distributed multicast routing for delay and delay variation-bounded Steiner tree using simulated annealing

The delay and delay variation-bounded Steiner tree problem is an important multicast routing issue in real-time multimedia networks. Such a constrained Steiner tree problem is known to be NP-complete. In this paper, we propose a distributed multicast routing algorithm based on simulated annealing to produce routing trees having a minimal network cost under delay and delay variation constraints. The proposed algorithm is fully distributed, and supports the dynamic reorganizing of the multicast tree in response to changes for the destination. Simulations demonstrate that our algorithm is better in terms of tree cost as compared with other existing algorithms, and it performs excellently in delay and delay variation. Furthermore, it has high success ratio, rapid convergence and better real-time property.