Threshold based locking routing strategy for delay tolerant network

Delay tolerance network probabilistic routing protocols forward message to a node by observing its predictability value to meet the message destination. However, it is vital to predict the ability of node to carry the transmitted message. For instance, the traffic confluence on the high probable nodes can produce congestion that results in the drop of previously stored messages. These drops diminish the delivery ratio because the dropped message lost its opportunity to be delivered. Since, there exist multiple copies of each message; therefore, the same node invariably receives the dropped messages from other parts of the network and causes the highest number of transmissions. Additionally, the replication from source node continues on the high probable peers even the previous copies were transmitted on the better predictable neighbors than the current. In this paper, we have proposed a novel routing method called as the adaptive threshold based locking method that maintains the contemporary status of the node based on its activity in the network. We have used the adaptive status measuring metrics such as transmit factor, drop factor and hop away count. Moreover, a threshold based locking method has been introduced to control the diffusion of messages. We have performed the comparison of existing and proposed routing methods with real time mobility traces. The proposed strategy has bolstered the delivery ratio and minimizes hop count, end-to-end delay and number of transmission.     

Cooperative data collection in ad hoc networks

This paper studies the problem of data gathering in multi-hop wireless ad hoc networks. In this scenario, a set of wireless devices constantly sample their surroundings and initiate report messages addressed to the base station. The messages are forwarded in a multi-hop fashion, where the wireless devices act both as senders and relays. We consider data gathering without aggregation, i.e. the nodes are required to forward all the messages initiated by other nodes (in addition to their own) to the base station. This is in contrast to the well studied problem of data gathering with aggregation, which is significantly simpler. As some nodes experience a larger load of forward requests, these nodes will have their battery charges depleted much faster than the other nodes—which can rapidly break the connectivity of the network. We focus on maximizing the network lifetime through efficient balancing of the consumed transmission energy. We show that the problem is NP-hard for two network types and develop various approximation schemes. Our results are validated through extensive simulations.     

On minimizing the total power of <Emphasis Type="Italic">k</Emphasis>-strongly connected wireless networks

Given a wireless network, we want to assign each node a transmission power, which will enable transmission between any two nodes (via other nodes). Moreover, due to possible faults, we want to have at least k vertex-disjoint paths from any node to any other, where k is some fixed integer, depending on the reliability of the nodes. The goal is to achieve this directed k-strong connectivity with a minimal overall power assignment. The problem is NP-Hard for any k ≥ 1 already for planar networks. Here we first present an optimal power assignment for uniformly spaced nodes on a line for any k ≥ 1. We also prove a number of useful properties of power assignment which are also of independent interest. Based on it, we design an approximation algorithm for linear radio networks with factor min{2,(\frac \Updelta d)^a },\hbox{min}\left\{2,\left(\frac {\Updelta} {\delta}\right)^\alpha \right\}, where Δ and δ are the maximal and minimal distances between adjacent nodes respectively and parameter α ≥ 1 being the distance-power gradient. We then extend it to the weighted version. Finally, we develop an approximation algorithm with factor O(k ²), for planar case, which is, to the best of our knowledge, the first non-trivial result for this problem.     

Rh promoted and ZrO2/Al2O3 supported Ni/Co based catalysts: High activity for CO2 reforming,steam–CO2 reforming and oxy–CO2 reforming of CH4

Ni (2.5 wt%) and Co (2.5 wt%) supported over ZrO₂/Al₂O₃ were prepared by following a hydrolytic co-precipitation method. The synthesized catalysts were further promoted by Rh incorporation (0.01–1.00 wt%) and tested for their catalytic performance for dry CO₂ reforming, combined steam–CO₂ reforming and oxy–CO₂ reforming of methane for production of syngas. The catalysts were characterized by using N₂ physical adsorption, XRD, H₂–TPR, SEM, CO₂–TPD, NH₃–TPD, TEM and TGA. The results revealed that ZrO₂ phase was in crystalline form in the catalysts along with amorphous Al oxides. Ni and Co were confirmed to be in their respective spinel phases that were reducible to metallic form at 800 °C under H₂. Ni and Co were well dispersed with their nano-crystalline nature. The catalyst with 0.2% loading of Rh showed superior performance in the studied reactions for reforming of methane. This catalyst also showed good coke resistance ability for dry CO₂ reforming reaction with 3.8 wt% of carbon formation during the reaction as compared to 11.6 wt% carbon formation over the catalyst without Rh. The catalyst performance was stable throughout the reaction time for CH₄ conversions, irrespective of carbon formation with slight decline (～1%) in CO₂ conversion. For dry CO₂ reforming reaction, this catalyst showed good conversion for both CH₄ and CO₂ (67.6% and 71.8% respectively) with a H₂/CO ratio of 0.84, while for the Oxy-CO₂ reforming reaction, the activity was superior with CH₄ and CO₂ conversions (73.7% and 83.8% respectively) and H₂/CO ratio of 1.05.     

From Bugs to Bioplastics: Total (+)-Dihydrocarvide Biosynthesis by Engineered Escherichia coli

The monoterpenoid lactone derivative (+)-dihydrocarvide ((+)-DHCD) can be polymerised to form shape-memory polymers. Synthetic biology routes from simple, inexpensive carbon sources are an attractive, alternative route over chemical synthesis from (R)-carvone. We have demonstrated a proof-of-principle in vivo approach for the complete biosynthesis of (+)-DHCD from glucose in Escherichia coli (6.6 mg L⁻¹). The pathway is based on the Mentha spicata route to (R)-carvone, with the addition of an ′ene′-reductase and Baeyer–Villiger cyclohexanone monooxygenase. Co-expression with a limonene synthesis pathway enzyme enables complete biocatalytic production within one microbial chassis. (+)-DHCD was successfully produced by screening multiple homologues of the pathway genes, combined with expression optimisation by selective promoter and/or ribosomal binding-site screening. This study demonstrates the potential application of synthetic biology approaches in the development of truly sustainable and renewable bioplastic monomers.     

Nanoparticles as tool for enhanced ophthalmic delivery of vancomycin: a multidistrict-based microbiological study,solid lipid nanoparticles formulation and evaluation

Context: A microbiological multidistrict-based survey from different Egyptian governorates was conducted to determine the most prevalent causative agents of ocular infections in the Egyptian population. Antibiotic sensitivity testing was then performed to identify the most potent antimicrobial agent. Vancomycin (VCM) proved the highest activity against gram-positive Staphylococcus bacteria, which are the most commonly isolated causative agents of ocular infection. However, topically applied VCM suffers from poor ocular bioavailability because of its high molecular weight and hydrophilicity. Objective: The aim of the present study was to develop VCM-loaded solid lipid nanoparticles (SLNs) using water-in-oil-in-water (W/O/W) double emulsion, solvent evaporation technique to enhance ocular penetration and prolong ophthalmic residence of VCM. Method: Two consecutive full factorial designs (2⁴ followed by 3²) were adopted to study the effect of different formulation and process parameters on SLN formulation. The lipid type and structure, polyvinyl alcohol (PVA) molecular weight and concentration, sonication time, as well as lipid:drug ratio were studied as independent variables. The formulated SLN formulae were evaluated for encapsulation efficiency (EE%), particle size (PS), and zeta potential as dependent variables. Results: The statistically-optimized SLN formula (1:1 ratio of glyceryltripalmitate:VCM with 1% low molecular weight PVA and 1?min sonication time) had average PS of 277.25?nm, zeta potential of ?20.45, and 19.99% drug encapsulation. Scanning and transmission electron micrographs showed well-defined, spherical, homogenously distributed particles. Conclusion: The present study suggests that VCM incorporation into SLNs is successfully achievable; however, further studies with different nanoencapsulation materials and techniques would be valuable for improving VCM encapsulation.     

Experience with software conversion

Experience with a program to convert from LISP 1.6 to INTERLISP is described. The conversion program was designed with two goals in mind. First, it had to be capable of being executed in either of the languages's environments and it had to yield identical results. Second, the speed of the converted program was to be approximately the same as the original program. This meant that the conversion process must be completed prior to execution of the converted program. The various constraints and considerations imposed by these goals are examined. In addition, aside from problems in finding INTERLISP analogs for various LISP 1.6 constructs, careful consideration must also be paid to input/output functions, escape characters, global variables, representation of numbers and different string implementations.     

Modified Garden Balsan Optimization Based Machine Learning for Intrusion Detection

The Internet of Things (IoT) environment plays a crucial role in the design of smart environments. Security and privacy are the major challenging problems that exist in the design of IoT-enabled real-time environments. Security susceptibilities in IoT-based systems pose security threats which affect smart environment applications. Intrusion detection systems (IDS) can be used for IoT environments to mitigate IoT-related security attacks which use few security vulnerabilities. This paper introduces a modified garden balsan optimization-based machine learning model for intrusion detection (MGBO-MLID) in the IoT cloud environment. The presented MGBO-MLID technique focuses on the identification and classification of intrusions in the IoT cloud atmosphere. Initially, the presented MGBO-MLID model applies min-max normalization that can be utilized for scaling the features in a uniform format. In addition, the MGBO-MLID model exploits the MGBO algorithm to choose the optimal subset of features. Moreover, the attention-based bidirectional long short-term (ABiLSTM) method can be utilized for the detection and classification of intrusions. At the final level, the Aquila optimization (AO) algorithm is applied as a hyperparameter optimizer to fine-tune the ABiLSTM methods. The experimental validation of the MGBO-MLID method is tested using a benchmark dataset. The extensive comparative study reported the betterment of the MGBO-MLID algorithm over recent approaches.     

EF-MPR,a new energy eFficient multi-point relay selection algorithm for MANET

MultiPoint Relay (MPR) selection algorithm is a flooding technique for propagating a broadcast message inside an ad-hoc network which reduces the number of unnecessary broadcast messages in order to save more energy in the network, minimize the number of packet collisions, and speed up the propagation time. In this paper, we demonstrate that MPR selection is an application of Set Covering Problem (SCP). A few optimization methods are developed in this work to find the optimum solution including Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), and a new greedy algorithm. Extensive simulations are set up to evaluate the developed methods. The new algorithm is named Energy eFficient MPR or EF-MPR in short. The simulation results show that EF-MPR can reduce the number of MPR nodes up to 19%. Moreover, EF-MPR algorithm reduces the power-consumption of network up to 12% and speed up the propagation time by 9%.     

Intensive Benchmarking of D2D communication over 5G cellular networks: prototype,integrated features,challenges, and main applications

Wireless Networks - The evolving Fifth generation (5G) cellular wireless networks are envisioned to provide higher data rates, lower end-to-end latency, and lower energy consumption for devices. In...