Exploration of genetic algorithm in network coding for wireless sensor networks

Wireless network comprises of multiples nodes that work together to form a network. Each node in a wireless network communicates with one another by disseminating information packet among them. Source node and destination node are often far apart from each other, thus the information packet has to be transmitted to intermediate node(s) before it is able to be relayed to its destination. Network coding is introduced to combine several packets from different sources and broadcast the combined packet to several destinations in single transmission time slot. Each destination is capable to extract the intended information by decoding from a common packet. In short, network coding improves the throughput for wireless and wired networks but also causes side effects such as complexity of packets management and increases delay for coding opportunity. Hence, genetic algorithm is used to optimize the resources for network coding. Genetic algorithm will search for optimum routes to the destination according to the desired throughput with a desired multicast rate. In this paper, genetic algorithm is further enhanced in searching of optimum route for a packet. The simulation results show the enhanced genetic algorithm can adapt to various situations with different topologies with a better throughput and energy consumption compared to the store-and-forward method used in conventional wireless sensor network

A human PrM antibody that recognizes a novel cryptic epitope on dengue E glycoprotein

10.1371/journal.pone.0033451PLoS ONE74

Network Coding Based Packets Queue Operation for Wireless Ad Hoc Networks

Abstract-Wireless communication is a technology that simplify the daily life and to narrow the distance between people. Unfortunately throughput limitation of wireless networks is limiting the performance of wireless networks. In order to increase the throughput of the wireless network, network coding has been proposed to increase the throughput of network. Unlike conventional store-and-forward method, network coding is a method that intelligently combines packet from difference flow to reduce the transmissions while transfer the packets instead of just relay packets without doing any additional processing. Ad hoc on-demand distance vector routing protocol (AODV) will be used to discover route for packets from source to destination in wireless ad hoc networks. The simulation of wireless ad hoc network with and without network coding will be conducted in MATLAB. This paper introduces the development of simulation to illustrate the performance of network coding in wireless ad hoc network. The simulation will calculate the transmit packet time according to the size of the packet. Lastly, average network throughput performance between network coding and store-and-forward is shown and compared

Design and development of portable fuzzy logic based traffic optimizer

Traffic jam has become a common scene nowadays, due to the rapid increase of road users in the past few years. To solve this problem, the design of traffic control is required. Traffic control parameter can be determined from the traffic flow behavior of the traffic intersection. Currently, most of the traffic control system in Malaysia is using Webster Model, which its green time duration is predetermined by collecting the data from the traffic intersection. Most of the waiting time at the intersection is wasted due to the constant green time duration. The aim of this paper is to optimize the average waiting time of a traffic intersection via a developed Fuzzy Logic traffic control system. Traffic light simulator hardware is built to deal with the difficulties of working in a real environment and to investigate the performance of the traffic control system. Conventional traffic control system, Webster Model and the Fuzzy Logic controller will be applied into the traffic signal simulator in order to investigate their performance

A Wireless Network with Adaptive Modulation and Network Coding in Intelligent Transportation Systems

Abstract-Transportation has evolved to a topic which is highly regarded in multi aspects. Partly, the contribution to its increasing complexity and everlasting significance has some correlation to the continuous rising demands of public transportation. Transportation systems are now urged to break through the boundaries using communication technolog

Potential of incorporating evolutionary based network coding for information scavenging in intelligent public transportation

Intelligent transportation systems use wireless technology as a communication backbone for disseminating vital traffic information. In conventional store-and-forward of a wireless ad hoc network, data packets disseminated separately and independently with different transmission lows limit the overall network performances. Network coding is implemented to combine several packets from different sources and broadcast the combined packet to respective destinations in single transmission flow. Genetic algorithm (GA) is introduced to further optimise the resources for network coding by searching optimum transmission route. The simulation results show the GA can adapt to various topologies with a better throughput and energy consumption of 22.27 % fewer than store-and-forward and 16.33 % fewer than code based forwarding structure (COPE)

Site-directed mutagenesis of predicted epitope on prM-E protein.

<p>(A) To confirm the binding epitope of D29 Fab-IgG, residues within the P3 and P9 predicted sequences were mutated to generate mutants 1–6 (M1-6); M3/4, M3/5, M4/5 and M5/6 contain combinational-mutations as stated. (B) Reactivity of antibodies with the mutants was tested by Western blot analysis. Cleared lysate of DENV2-infected Vero cells (DV2), pCMV-prM-E- (prM-E) or mutants-transfected HEK 293 T cells (M1-5/6) were separated on 12% SDS-PAGE in non-reducing condition, followed by detection with h4G2, m2H2 and D29 Fab-IgG.</p

Localization of P3 and P9 peptide sequence on 3D crystal structure of prM-E heterodimer (PDB 3C6E).

<p>P3 (Purple) and P9 (green) peptide sequences were aligned with the predicted clusters (Cluster 1 – Navy blue; Cluster 2 – Black) on the prM-E crystal structure. The path of peptide phage sequences was highlighted with the participating residues from the cluster and the peptide phage labeled. Matched residues were purple (P3) or green (P9) and numbered accordingly; mis-matched residues were grey. The respective proteins and domains were highlighted as above.</p

Competition Assays and Western Blots of D29 Fab-IgG and monoclonal anti-DENV antibodies with known epitope.

<p>(A) Serially diluted h3H5, h4G2 or m2H2 was incubated with immobilized DENV2 (2×10⁷ pfu/ml) for 1 hr at RT before addition of 2.5 µg/ml of D29 Fab-IgG for a further hour at RT. Bound D29 Fab-IgG was detected by HRP-conjugated anti-human IgG-Fc antibody. 2.5 µg/ml of HRP-conjugated m2H2 was used to compete against m2H2. Values displayed are the average of three independent experiments and error bars represent standard errors of the mean. For Western Blot analysis, DENV1-4 (D1-D4) infected Vero cell lysate and 0.5 µg of recombinant DENV2 E protein (ecto-domain) (rE) were separated on 12% SDS-PAGE in (B) non-reducing, (C) reducing conditions; followed by detection with 1 µg/ml of h3H5, h4G2, m2H2 and D29 Fab-IgG. (D) For competition Western blot analysis, 0.5 µg/ml of D29 Fab-IgG was incubated with 1 µg/ml of h4G2, h3H5, m2H2 for 1 hr at RT before applying to membrane transblotted with DENV2 viral lysate for 30 min at RT.</p