Abstract: Routing protocols in underwater wireless sensor networks (UWSNs) require the consideration of several aspects such as energy consumption, amount of packets delivered successfully (packet delivery ratio), network topology and propagation delay during the data transmission process. Once a wireless sensor network is deployed under water, it will be really difficult and costly to recover them for later battery repositions, mainly due to the issue that their location may not be accessed. For this reason, it is important to have a routing protocol that guarantees a long life time of the UWSN and also optimizes the use of the network by improving not only the network energy consumption but also the packet delivery ratio. In this paper a new routing protocol named DBR applying Energy Criteria (DBR-EC) is presented. This protocol is an improvement of the DBR protocol [1] by applying criteria of energy saving in each node that belongs to the network. DBREC guarantees a longer life time than othe

• Publication Date: 11-Dec-2015
• DOI: 10.15224/978-1-63248-077-4-25
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Abstract: Nonnegative Tensor Factorization has previously been used in many multi-way data analyses. We use NTF model to do personalized paper recommendation. For recommendation, we analyze four different multiplicative algorithms for NTF based on different decomposition models and different optimization functions. On one hand, one part of algorithms use CP decomposition, the other part use Tucker decomposition. On the other, half of algorithms minimize the least squares error while the others minimize the Kullback- Leibler divergence. Further, we also compare recommendation performance with different rank NTFs. From our experiments, nonnegative Tucker decomposition based on KL divergence has the better result, and to some extent, lower rank NTF can get most of information from dataset.

• Publication Date: 11-Dec-2015
• DOI: 10.15224/978-1-63248-077-4-26
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