Publish in OALib Journal
APC: Only $99
The treatment of moving material
interfaces and their vicinity is very important for compressible multifluids.
In this paper, we propose one type of ghost fluid method based on Riemann
solutions for front tracking method. The accuracy of the interface boundary
condition is discussed for the gas-gas
Riemann problem. It is shown that the solution of the ghost fluid method
approximates the exact solution to second-order accuracy in the sense of
comparing to the exact solution of a Riemann problem at the material interface.
Numerical examples suggest that the present scheme is able to handle
multifluids problems with large density differences and has the property of
reduced conservation error.
In wireless sensor networks, the
traditional multi-relay incremental cooperative relaying (MIR) scheme could
improve the system throughput over the fading channel enormously by exploiting
multiple relay nodes to retransmit the copy of the source packet to the
destination in turn, but increase the energy consumption and transmission delay.
In order to mitigating the energy consumption and transmission delay, this
paper proposes a new cooperative relaying scheme termed as
incremental-selective relaying with best-relay selection (ISR), which selects
the best relay node from the candidate relays to retransmit the packet to the
destination only when the direct transmission between the source and the
destination is not successful. Expressions of normalized throughput, normalized
delay and energy efficiency for the ISR and MIR systems are derived respectively
and their performances are compared through simulations. The results show that
normalized throughput, normalized delay and energy efficiency for the ISR
system all outperform the corresponding performances of the MIR system.
Especially, there are different the optimal number of relays which can maximize
the energy efficiency of system.
Based on the analysis of the existing classic
clustering routing algorithm HEED, this paper proposes an efficient dynamic
clustering routing algorithm ED-HEED. In the cluster selection process, in
order to optimize the network topology and select more proper nodes as the
cluster head, the proposed clustering algorithm considers the shortest path prediction
of the node to the destination sink and the congestion situation. In the data
transmission procedure, the high-efficiency CEDOR opportunistic routing
algorithm is applied into the ED-HEED as the data transmission mode between
cluster headers. A novel adaptive dynamic clustering mechanism is also
considered into the algorithm, as well as the data redundancy and security
control. Our Simulation demonstrates that the ED-HEED algorithm can reduce the
energy consumption, prolong the network life and keep the security and
availability of the network compared with the HEED algorithm.