Machine learning algorithms for wireless sensor networks: A survey

A system, method, and computer program product are provided for a memory system. The system includes a first semiconductor platform including at least one first circuit, and at least one additional semiconductor platform stacked with the first semiconductor platform and including at least one additional circuit.

System, method, and computer program product for improving memory systems

Wireless body area networks (WBANs) form a new and interesting area in the world of remote health monitoring. An important concern in such networks is the communication between the sensors. This communication needs to be energy efficient and highly reliable while keeping delays low. Mobility also has to be supported as the nodes are positioned on different parts of the body that move with regard to each other. In this paper, we present a new cross-layer communication protocol for WBANs: CICADA or Cascading Information retrieval by Controlling Access with Distributed slot Assignment. The protocol sets up a network tree in a distributed manner. This tree structure is subsequently used to guarantee collision free access to the medium and to route data towards the sink. The paper analyzes CICADA and shows simulation results. The protocol offers low delay and good resilience to mobility. The energy usage is low as the nodes can sleep in slots where they are not transmitting or receiving.

A low-delay protocol for multishop wireless body area networks

Digital video signature apparatus and methods for use with video program identification systems are disclosed. The disclosed apparatus and methods identify a video program using a sequence of signatures. Each of the signatures includes a set of centroids corresponding to one of a plurality of frames of the video program. The apparatus and methods compare the sequence of signatures to a set of reference sequences of signatures and identify the video program based on the comparison of the sequence of signatures to the set of reference sequences of signatures.

Digital video signature apparatus and methods for use with video program identification systems

Sarcastic sentiment detection in tweets streamed in real time: a big data approach

In mobile ad hoc networks, mobile devices wander autonomously for the use of wireless links and dynamically varying network topology. AODV (Ad-hoc on-demand Distance vector routing) is a representative among the most widely studied on-demand ad hoc routing protocols. Previous protocols have shown some shortcomings on performance. AODV and most of the on-demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, especially on high speed mobility. This increases both in communication delay and power consumption as well as decrease in packet delivery ratio. To avoid these problems, we propose a reverse AODV which tries multiple route replies. The extended AODV is called reverse AODV (R-AODV), which has a novel aspect compared to other on-demand routing protocols on Ad-hoc Networks: it reduces path fail correction messages and obtains better performance than the AODV and other protocols have. We design the R-AODV protocol and implement simulation models using NS-2. Simulation results show that the reverse AODV provides good experimental results on packet delivery ratio, power consumption and communication delay.

/pdf/a-reverse-aodv-routing-protocol-in-ad-hoc-mobile-networks-4zmbbnjlkn.pdf

A reverse AODV routing protocol in ad hoc mobile networks

Opinion mining, which extracts meaningful opinion information from large amounts of social multimedia data, has recently arisen as a research area. In particular, opinion mining has been used to understand the true meaning and intent of social networking site users. It requires efficient techniques to collect a large amount of social multimedia data and extract meaningful information from them. Therefore, in this paper, we propose a method to extract sentiment information from various types of unstructured social media text data from social networks by using a parallel Hadoop Distributed File System (HDFS) to save social multimedia data and using MapReduce functions for sentiment analysis. The proposed method has stably performed data gathering and data loading and maintained stable load balancing of memory and CPU resources during data processing by the HDFS system. The proposed MapReduce functions have effectively performed sentiment analysis in the experiments. Finally, the sentiment analysis results of the proposed system are very close to those of manual processes.

https://journals.sagepub.com/doi/pdf/10.1155/2015/417502

MapReduce functions to analyze sentiment information from social big data

In Wireless Sensor Networks (WSN), energy is one of the most important resources since each node collects, processes and transmits data to its base station. Most of the traditional works in WSNs are consisted of static nodes and one base station. Recently, some mobile data gathering methods are proposed to prolong the operation time of sensor networks. One or more mobile collectors are used to gather sensed data from sensor nodes at short transmission ranges. This paper presents to find optimal visiting points and data gathering path for a mobile sink within clusters. With defining an optimal clustering and data gathering path, this method improves the data collection performance as well as the network lifetime extension of sensor networks. The network lifetime is increased to 20% when sensor nodes are divided into from 4 clusters to 15 clusters.

/pdf/an-optimal-data-gathering-method-for-mobile-sinks-in-wsns-xlwydo1r13.pdf

An Optimal Data Gathering Method for Mobile Sinks in WSNs

This paper provides a new test technique for detecting defects in Through Silicon Via (TSV) in 3-D ICs and presents a substrate-dependent equivalent electrical model for TSVs. Process-related defects that affect the functional electrical performance of the TSV are identified, and fault models are developed for each individual defect. The fault models are integrated into the equivalent electrical model of the TSV for testing. Our test technique uses an RF carrier signal modulated with a multi-tone signal with added Gaussian white noise to synthesize the test stimulus; the peak-to-average ratio is measured as output response. We find a significant difference in peak-to-average ratio between defect-free and defective TSVs. Our test technique is very sensitive to small defects in these nanostructures, thereby identifying the defects with high accuracy.

Fault Modeling and Multi-Tone Dither Scheme for Testing 3D TSV Defects

The design and development of reliable 3D integrated systems require high performance interconnects, which in turn are largely dependent on the choice of filler materials used in through-silicon vias (TSVs). Copper, tungsten, and poly-silicon have been explored as filler materials; however, issues such as thermal incompatibility, electromigration, and high resistivity are still a bottleneck. In this paper, we investigate single-walled carbon nanotube (CNT) bundles as a prospective filler material for TSVs and have provided an analysis of CNT based TSVs for package and chip interconnects. The interconnects are fundamental bottlenecks to achieving high performance and reliability. We have provided electrical modeling and performed simulations on TSVs with copper and carbon nanotubes. The results from the CNT based TSVs were greatly superior to those from the conventional vias with copper.

Byoungchul Ahn

Papers

A reverse AODV routing protocol in ad hoc mobile networks

MapReduce functions to analyze sentiment information from social big data

An Optimal Data Gathering Method for Mobile Sinks in WSNs

Fault Modeling and Multi-Tone Dither Scheme for Testing 3D TSV Defects

Development of Carbon Nanotube Based Through-Silicon Vias