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In order to prolong the lifetime of wireless sensor networks, this paper presents a multihop routing protocol with unequal clustering (MRPUC). On the one hand, cluster heads deliver the data to the base station with relay to reduce energy consumption. On the other hand, MRPUC uses many measures to balance the energy of nodes. First, it selects the nodes with more residual energy as cluster heads, and clusters closer to the base station have smaller sizes to preserve some energy during intra-cluster communication for inter-cluster packets forwarding. Second, when regular nodes join clusters, they consider not only the distance to cluster heads but also the residual energy of cluster heads. Third, cluster heads choose those nodes as relay nodes, which have minimum energy consumption for forwarding and maximum residual energy to avoid dying earlier.Simulation results show that MRPUC performs much better than similar protocols. Network model2008 ISECS International Colloquium on Computing, Communication, Control, and Management 978-0-7695-3290-5/08 $25.00

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Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

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