Multi-Channel Scheduling for Fast Convergecast in Wireless Sensor Networks

We explore the following fundamental question - how fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data collection - interference and the half-duplex single-transceiver radios. We show that while power control helps in reducing the number of transmission slots to complete a convergecast under a single frequency channel, scheduling transmissions on different frequency channels is more efficient in mitigating the effects of interference (empirically, 6 channels suffice for most 100-node networks). With these observations, we define a receiver-based channel assignment problem, and prove it to be NP-complete on general graphs. We then introduce a greedy channel assignment algorithm that efficiently eliminates interference, and compare its performance with other existing schemes via simulations. Once the interference is completely eliminated, we show that with half-duplex single-transceiver radios the achievable schedule length is lower-bounded by max(2nk − 1,N), where nk is the maximum number of nodes on any subtree and N is the number of nodes in the network. We modify an existing distributed time slot assignment algorithm to achieve this bound when a suitable balanced routing scheme is employed. Through extensive simulations, we demonstrate that convergecast can be completed within up to 50% less time slots, in 100-node networks, using multiple channels as compared to that with single-channel communication. Finally, we also demonstrate further improvements that are possible when the sink is equipped with multiple transceivers or when there are multiple sinks to collect data

Algorithms for Fast Aggregated Convergecast in Sensor Networks

Fast and periodic collection of aggregated data is of considerable interest for mission-critical and continuous monitoring applications in sensor networks. In the many-to-one communication paradigm, referred to as convergecast, we focus on applications wherein data packets are aggregated at each hop en-route to the sink along a tree-based routing topology, and address the problem of minimizing the convergecast schedule length by utilizing multiple frequency channels. The primary hindrance in minimizing the schedule length is the presence of interfering links. We prove that it is NP-complete to determine whether all the interfering links in an arbitrary network can be removed using at most a constant number of frequencies. We give a sufficient condition on the number of frequencies for which all the interfering links can be removed, and propose a polynomial time algorithm that minimizes the schedule length in this case. We also prove that minimizing the schedule length for a given number of frequencies on an arbitrary network is NP-complete, and describe a greedy scheme that gives a constant factor approximation on unit disk graphs. When the routing tree is not given as an input to the problem, we prove that a constant factor approximation is still achievable for degree-bounded trees. Finally, we evaluate our algorithms through simulations and compare their performance under different network parameters

Resource consumption analysis of online activity recognition on mobile phones and smartwatches

Most of the studies on human activity recognition using smartphones and smartwatches are performed in an offline manner. In such studies, collected data is analyzed in machine learning tools with less focus on the resource consumption of these devices for running an activity recognition system. In this paper, we analyze the resource consumption of human activity recognition on both smartphones and smartwatches, considering six different classifiers, three different sensors, different sampling rates and window sizes. We study the CPU, memory and battery usage with different parameters, where the smartphone is used to recognize seven physical activities and the smartwatch is used to recognize smoking activity. As a result of this analysis, we report that classification function takes a very small amount of CPU time out of total app’s CPU time while sensing and feature calculation consume most of it. When an additional sensor is used besides an accelerometer, such as gyroscope, CPU usage increases significantly. Analysis results also show that increasing the window size reduces the resource consumption more than reducing the sampling rate. As a final remark, we observe that a more complex model using only the accelerometer is a better option than using a simple model with both accelerometer and gyroscope when resource usage is to be reduced

Impact of Network Density on Bandwidth Resource Management in WSN

We describe a self-organizing, clustering protocol for bandwidth resource management in Wireless Sensor Networks. The proposed protocol allows the sensor nodes to communicate by a time-slotted, scheduled MAC algorithm. When the nodes are densely deployed, i.e., the connectivity is very high, the MAC algorithm may not provide access for all of the nodes due to the limited number of time-slots, consequently the network capacity degrades. To overcome this drawback, we extend the time-slotted MAC algorithm by clustering the nodes into direrent frequency domains while they can use the same time domain. The idea is basically to multiplex the time domain with the frequency domain. As a result, the number of nodes that are granted access to the wireless medium is increased by the number of frequency channels available. By using simulations, we evaluate the performance of the protocol. The results reveal that frequency multiplexing has the erect of increasing the capacity up to 100%

Dual functionality of conjugated polymer nanoparticles as an anticancer drug carrier and a fluorescent probe for cell imaging

Cataloged from PDF version of article.Multifunctional nanoparticles based on a green emitting, hydrophobic conjugated polymer, poly[(9,9-bis{propeny}fluorenyl-2,7-diyl)-co-(1,4- benzo-{2,1,3}-thiodiazole)] (PPFBT), that acts both as a fluorescent reporter and a matrix to accommodate an anti-cancer compound, camptothecin (CPT), were prepared, characterized and their potential as a fluorescent probe for cell imaging and as a drug delivery vehicle were evaluated via in vitro cell assays. The cell viability of human hepatocellular carcinoma cell line (Huh7) was investigated in the absence and presence of CPT with sulforhodamine B (SRB) and real-time cell electronic sensing (RT-CES) cytotoxicity assays

Laboratory Genetic Testing in Clinical Practice 2016.

WOS: 000392526600001PubMed ID: 2813360

Evolution of Genetic Techniques: Past, Present, and Beyond.

Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given

Laboratory genetic testing in clinical practice 2014.

WOS: 000352434200001PubMed ID: 2587902

The effects of nitrogen and phosphorus deficiencies and nitrite addition on the lipid content of Chlorella vulgaris (Chlorophyceae)

The effect of 50% N, 100% N, 50% N plus 50% P and 50% P deficiencies and nitrite addition were treated on Chlorella vulgaris (Chlorophyceae) was studied in laboratory conditions with the aim to determine the effects of the deficient nutrient and different nitrogen sources on lipid and protein contents. Proteinand lipid values of the biomass were found as 50.8 and 12.29% for the control group, 20.3 and 17.5% for 50% N(-), 13.01 and 35.6% for 100% N(-), 21.37 and 20.5% for 50% N(-) and 50% P(-), 38.16 and 16.7% for 50% P(-) and 41.03 and 13.04% for the nitrite group that was added. The highest lipid content was recorded with the culture to which 100% N(-) was treated with 0.18 g/L dry-weight.Key words: Chlorella vulgaris, lipid, nitrogen and phosphorus deficiencies, nitrite