Data and resource management in wireless networks via data compression, GPS-free dissemination, and learning

“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting the data of interest. As most of the low-cost wireless sensors won’t be equipped with a GPS module, the virtual coordinates are used to estimate the locations. The proposed work utilizes the anchor-based virtual coordinate system and DV-Hop (Distance vector of hops to anchors) to estimate the relative location of nodes to anchors. Also, it uses circle and hyperbola constraints to encode the position of interest (POI) and any user-defined trajectory into a data request message which allows only the sensors in the POI and routing trajectory to collect and route. It also provides location anonymity by avoiding using and transmitting GPS location information. This has been extended also for heterogeneous WSNs and refined the encoding algorithm by replacing the circle constraints with the ellipse constraints. Last, it proposes a framework that predicts the trajectory of the moving object using a Sequence-to-Sequence learning (Seq2Seq) model and only wakes-up the sensors that fall within the predicted trajectory of the moving object with a specially designed control packet. It reduces the computation time of encoding geospatial trajectory by more than 90% and preserves the location anonymity for the local edge servers”--Abstract, page iv

Multiple solutions for Kirchhoff type problems involving super-linear and sub-linear terms

In this paper, we consider the multiplicity of solutions for a class of Kirchhoff type problems with concave and convex nonlinearities on an unbounded domain. With the aid of Ekeland's variational principle, Jeanjean's monotone method and the Pohožaev identity we prove that the Kirchhoff problem has at least two solutions

Sneutrino DM in the NMSSM with inverse seesaw mechanism

In supersymmetric theories like the Next-to-Minimal Supersymmetric Standard Model (NMSSM), the lightest neutralino with bino or singlino as its dominant component is customarily taken as dark matter (DM) candidate. Since light Higgsinos favored by naturalness can strength the couplings of the DM and thus enhance the DM-nucleon scattering rate, the tension between naturalness and DM direct detection results becomes more and more acute with the improved experimental sensitivity. In this work, we extend the NMSSM by inverse seesaw mechanism to generate neutrino mass, and show that in certain parameter space the lightest sneutrino may act as a viable DM candidate, i.e. it can annihilate by multi-channels to get correct relic density and meanwhile satisfy all experimental constraints. The most striking feature of the extension is that the DM-nucleon scattering rate can be naturally below its current experimental bounds regardless of the higgsino mass, and hence it alleviates the tension between naturalness and DM experiments. Other interesting features include that the Higgs phenomenology becomes much richer than that of the original NMSSM due to the relaxed constraints from DM physics and also due to the presence of extra neutrinos, and that the signatures of sparticles at colliders are quite different from those with neutralino as DM candidate.Comment: 33 page

Efficient Data Collection in IoT Networks using Trajectory Encoded with Geometric Shapes

The mobile edge computing (MEC) paradigm changes the role of edge devices from data producers and requesters to data consumers and processors. MEC mitigates the bandwidth limitation between the edge server and the remote cloud by directly processing the large amount of data locally generated by the network of the internet of things (IoT) at the edge. An efficient data-gathering scheme is crucial for providing quality of service (QoS) within MEC. To reduce redundant data transmission, this paper proposes a data collection scheme that only gathers the necessary data from IoT devices (like wireless sensors) along a trajectory. Instead of using and transmitting location information (which may leak the location anonymity), a virtual coordinate system called \u27distance vector of hops to anchors\u27 (DV-Hop) is used. The proposed trajectory encoding algorithm uses ellipse and hyperbola constraints to encode the position of interest (POI) and the trajectory route to the POI. Sensors make routing decisions only based on the geometric constraints and the DV-Hop information, both of which are stored in their memory. Also, the proposed scheme can work in heterogeneous networks (with different radio ranges) where each sensor can calculate the average one-hop distance within the POI dynamically. The proposed DV-Hop updating algorithm enables the users to collect data in an IoT network with mobile nodes. The experiments show that in heterogeneous IoT networks, the proposed data collection scheme outperforms two other state-of-the-art topology-based routing protocols, called ring routing, and nested ring. The results also show that the proposed scheme has better latency, reliability, coverage, energy usage, and provide location privacy compared to state-of-the-art schemes

Identification and characterisation of the missing components of the ER reductive pathway

Efficient folding of proteins frequently requires the introduction of disulfide bonds. The insertion of disulfide bonds could result in native disulfides, which can be found in the correctly folded and functional protein structure, and non-native disulfides which are not present in the native protein. The resolution of non-native disulfides is absolutely required for cells to fold secreted proteins correctly and to remove misfolded proteins to alleviate cell stress. The pathways for disulfide formation are well characterised. However, our understanding of the reduction of non-native disulfides is still limited. How the reducing equivalents are transferred across the ER membrane and whether there are additional components needed in the reduction pathway either in cytosol or ER lumen are the questions we need to address. Microsomes including redox-sensitive green fluorescence protein (roGFP) were used to address which membrane protein was involved in the ER reductive pathway. We demonstrated that a membrane protein is required for the reduction of microsomal proteins by the membrane impermeable reducing agent Tris(2-carboxyethyl)phosphine (TCEP) or a reconstituted thioredoxin/thioredoxin reductase (Trx/TrxR) pathway. Previous research in our group suggests that ERp57 has a specific role in the isomerisation of non-native disulfide bonds in specific glycoprotein. We optimised the determination of redox state of ERp57 in semi-permeabilised (SP) cells. It was found that the reduction of ERp57 in SP cells required reducing equivalents generated by the Trx/TrxR pathway and the reduction was dependent on catalytic cysteines in the Trx motif. It was also shown by proteinase experiments that different membrane proteins are required for the transduction of electrons from TCEP and the Trx/TrxR pathway. In addition, we took advantage of an in vitro translational system supplemented with SP cells. A post-translationally folding assay was developed to evaluate the ability of the cytosolic components to resolve non-native disulfides in nascent polypeptides proteins in the ER. We showed that the minimal components in the cytosolic Trx/TrxR pathway are sufficient for disulfide rearrangement in the ER and that the reduction process is Trx - dependent