THE NOVEL COMMUNICATION ALGORITHM AND THE THROUGHPUT ANALYSIS FOR WIRELESS SENSOR NETWORKS

Aiming at the significance of the energy controls of wireless sensor networks, an economical energy consumption algorithm for wireless communicating in Wireless Sensor Networks (WSN) is presented. Based on the algorithm, the maximal system throughput of WSN is analyzed, and the upper bound of throughput of WSN is proposed and proved. Some numerical simulations are conducted and analyzed. The conclusions include that the transmitting radius of sensor node and the parameters of the energy cost function have significant influence upon the throughput, but the monitoring region radius has little influence. For the same transmitting distance, the more the hopping of information trans- mitting, the better the throughput of WSN. On the other hand, for the energy optimization of the whole WSN, the trade-off problem between the throughput capacity and the relay nodes is proposed, and the specific expression of relay hops that minimized the energy consumptions and the maximal throughput of WSN under the specific situation is derived.

CONSTRAINED VITERBI ALGORITHM AND ITS APPLICATION TO ERROR RESILIENT TRANSMISSION OF SPIHT CODED IMAGES

To overcome some drawbacks of Viterbi algorithm （VA）, such as exponential growing complexity of decoding, and its poor performance under bad channel conditions, some available known information must be used as constrained condition and apriori knowledge for decoding. A new constrained VA is proposed by adding con- straint bits directly for conventional codec. Compared with the conventional VA, under the bad channel condi- tion, the proposed scheme can improve the peak signal to noise ratio （PSNR） of the decoding image 2--10 dB by changing the number of constrained bits. Experimental results show that it is an efficient error-controlling way for the transmission of set partitioning in hierarchical trees （SPIHT） coded image.

Design and analysis of a network coding algorithm for ad hoc networks

Network coding is proved to have advantages in both wireline and wireless networks. Especially, appropriate network coding schemes are programmed for underlined networks. Considering the feature of strong node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on ad hoc networks was proposed. Compared with COPE-like network coding algorithms, the proposed algorithm does not require overhearing from other nodes, which meets confidentiality requirements of aviation communication networks. Meanwhile, it does save resource consumption and promise less processing delay. To analyze the performance of the network coding algorithm in scalable networks with different traffic models, a typical network was built in a network simulator, through which receiving accuracy rate and receiving delay were both examined.The simulation results indicate that, by virtue of network coding, the proposed algorithm works well and improves performance significantly. More specifically, it has better performance in enhancing receiving accuracy rate and reducing receiving delay, as compared with any of the traditional networks without coding. It was applied to both symmetric and asymmetric traffic flows and, in particular, it achieves much better performance when the network scale becomes larger. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks.

Layered heuristic algorithm for multiple restriction routes

A layered algorithm by bidirectional searching is proposed in this paper to solve the problem that it is difficult and time consuming to reach an optimal solution of the route search with multiple parameter restrictions for good quality of service. Firstly, a set of reachable paths to each intermediate node from the source node and the sink node based on adjacent matrix transformation are calculated respectively. Then a temporal optimal path is selected by adopting the proposed heuristic method according to a non-linear cost function. When the total number of the accumulated nodes by bidirectional searching reaches n-2, the paths from two directions to an intermediate node should be combined and several paths via different nodes from the source node to the sink node can be obtained, then an optimal path in the whole set of paths can be taken as the output route. Some simulation examples are included to show the effectiveness and efficiency of the proposed method. In addition, the proposed algorithm can be implemented with parallel computation and thus, the new algorithm has better performance in time complexity than other algorithms. Mathematical analysis indicates that the maximum complexity in time, based on parallel computation, is the same as the polynomial complexity of O(kn2-3kn+k), and some simulation results are shown to support this analysis.

Study of low bit rate speech codec algorithm in underwater acoustic communication

At medium or long distance （〉 10 kin） underwater acoustic speech communication, information transfer rate is constrained by the complicated, time varying channel and limited bandwidth. The bit rate of speech coding is required to be as low as possible. The time delay of underwater acoustic wave propagation can be used for low bit rate speech coding. After investigating the Mixed Excitation Linear Prediction （MELP） standard and taking account of the auditory perceptual features, a variable and adjustable bit rate speech codec algorithm has been proposed, whose average bit rate is about 600 bps. The average Perceptual Evaluation of Speech Quality Mean Opinion Score （PESQ MOS） of synthesized speeches is about 2.8. It has been proved by the computer simulation and sea trial that the performance of the proposed algorithm is well and robust when bit error rate is no more than 10-3. The synthesized speech is vivid and intelligible, and keeps main individual characteristics of speaker.

A Combinatorial Auction-Based Collaborative Cloud Services Platform

In this paper, we present a novel, dynamic collaboration cloud platform in which a Combinatorial Auction（CA）-based market model enables the platform to run effectively. The platform can facilitate expense reduction and improve the scalability of the cloud, which is divided into three layers： The user-layer receives requests from end-users, the auction-layer matches the requests with the cloud services provided by the Cloud Service Provider（CSP）, and the CSP-layer forms a coalition to improve serving ability to satisfy complex requirements of users.In fact, the aim of the coalition formation is to find suitable partners for a particular CSP. However, identifying a suitable combination of partners to form the coalition is an NP-hard problem. Hence, we propose approximation algorithms for the coalition formation. The Breadth Traversal Algorithm（BTA） and Revised Ant Colony Algorithm（RACA） are proposed to form a coalition when bidding for a single cloud service in the auction. The experimental results show that RACA outperforms the BTA in bid price. Other experiments were conducted to evaluate the impact of the communication cost on coalition formation and to assess the impact of iteration times for the optimal bidding price. In addition, the performance of the market model was compared to the existing CA-based model in terms of economic efficiency.