Paulvanna Nayaki Marimuthu

Data aggregation at the gateways through sensors' tasks scheduling in wireless sensor networks

The authors present a novel graph-based model for aggregating sensors’ data at the gateways within wireless sensor networks (WSNs), where the proposed graph can act as a mean of guiding and assessing the needed resources for data aggregation. In this study, the authors have modelled all sensors’ tasks in a graph so that their collected data are to be smoothly aggregated (scheduled) at the gateway without losing or overlapping the collected data at the gateways. A typical WSN comprises of hundreds of sensors and few gateways; moreover, each sensor executes periodically and sequentially three tasks, which are sensing, processing and transmitting. The three tasks are modelled as a directed acyclic graph (DAG) per sensor, and then all DAGs are grouped into a super task-flow-graph (STFG). The data aggregation problem is solved by scheduling the tasks within STFG, where the authors have utilised three scheduling algorithms: as soon as possible, as late as possible and branch-and-bound. The simulation results for 50 sensors covering an area of 10 000 m2 utilising deterministic and stochastic execution models show a requirement of eight and six gateways, respectively, with minimal waiting time for aggregating the collected data from sensors to the gateways.

Supporting multimedia applications through network redesign

Recent evolutions in high-performance computing and high speed broadband Internet access have paved a way to enterprise-wide multimedia applications, which require stern QoS from the underlying networks. In this paper, we have explored threefold studies on existing enterprise network, whereby we proposed an analytical approach to evaluate the performance of the existing network; we have examined the feasibility of existing enterprise networks to accommodate voice over Internet protocol VoIP services with acceptable QoS, and we have redesigned the enterprise network to accommodate VoIP services to comply with the user defined QoS. The network performance is evaluated by number of VoIP calls sustained by the network, bandwidth utilization, loss rate and latency through Network Simulation NS-2 tool. We have derived a cost model to show the cost-effectiveness of VoIP services over telephonic network. For a medium-size enterprise network of 200 clients and 9 servers, our simulation results show that the redesign improves the network performance by increasing the number of VoIP calls by 57% and decreasing bandwidth utilization and packet loss rate by 20% and 7%, respectively. Moreover, the proposed network redesign demonstrates that the network can be scalable and it can handle up to 4% increased voice calls in the future maintaining QoS standards. Copyright

Self-organization in ambient networks through molecular assembly

An ambient network provides a homogeneous environment to the mobile node amidst the heterogeneity, which arises from the connections to various clusters over its lifespan. When a mobile node in an ambient network changes its location or communication pattern, these changes force the mobile node to join a new cluster. Therefore, we have extended the molecular self-assembly for the ambient network to search for the best set of clusters to seize all the nodes. An internal-view of a molecular system depicts all its molecules and their relationships as holding together due to the equilibrium between the attraction and repulsion forces among its molecules. Here we have analogized the nodes within the ambient network as molecules where these nodes are also governed by special-forces (relations) to configure a connected topology. In this paper, we have defined three forces, which are the physical distance, incoming traffic and outgoing traffic with respect to the pair-wise relations between the node-to-node (at micro-level of a cluster in an ambient network), to act as attraction and repulsion among nodes and forming clusters in a self-organized manner. The ambient network topology problem is formulated as an optimization problem to find suitable clusters of nodes with an objective to reduce the backbone traffic where a cluster assembles the strongly attracted nodes together with respect to all three forces. The simulation results show that our proposed molecular assembly (MA) algorithm embedded on each node coordinates the clustering and our algorithm leads in reducing the backbone traffic up to 20% under the influence of an individual force and up to 10% with the forces applied together when compared to our previous network redesign algorithm with genetic algorithm (GA), which offered reduction in backbone traffic up to 3% as an optimization tool. The robustness of the proposed algorithm is tested by varying the network sizes with 25 and 50 nodes and the convergence rate of MA, which is faster in comparison with GA.

A coverage restoration scheme for wireless sensor networks within Simulated Annealing

This paper presents a simple but an effective approach to restore the coverage within a wireless sensor network (WSN) when sensors fail without adding new sensors. We have considered a sensor node failure due to electrical faults or malfunctions during the initial deployment. Each sensor has a limited energy supply, and the failure of a sensor results in extra overhead during restoration of the uncovered regions of the failed sensors on the active sensors. Therefore, we have proposed a restoration problem, which is to find the nearest and most apt neighbor in order to cover the uncovered region and at the same time maintain the lifespan of WSN to an accepted level. We have developed a restoration scheme within an optimization search algorithm, Simulated Annealing- a generic probabilistic metaheuristic algorithm. Our scheme searches the neighborhood space of the failing sensors in west-first counterclockwise. Our algorithm analyzes all the categories of failed nodes and the computational results show that our algorithm assists to increase the coverage area of the failing sensors with optimized energy consumption.

Molecular Assembly Tool for Synthesizing Multitier Computer Networks

We have proposed a design tool for synthesizing multitier computer networks based on the concept of molecular assembly (MA), where the networks nodes integrate intelligently together by exploiting various forces of attraction existing between the nodes. Three forces are defined and the forces are the distance force, the incoming flow force and the outgoing flow force. Our simulation results demonstrate that for a given unassembled network of 50 nodes, our design tool forms a self-assembled network and manages to reduce the traffic at the backbone by 40% in a short computing time.

Query-based data aggregation within WSN through Monte Carlo simulation

Most of the current research in wireless sensor network (WSN) focuses on energy related issues because of the fact that tiny sensor devices possess a limited power supply. Out of the three normally executed sensors tasks (sense, process and transmit), data transmission consumes most of the power. In this paper, we propose a query-based data aggregation model that is based on the base stations within WSN that query the sensors to transmit their collected data due to special events. The worst-case scenario for a query-based activation would be that all sensors transmit their collected data simultaneously to the base station. This could lead to a loss of data due to the overlapping of transmissions at the base station. Therefore, we have embedded our query-based model within a Monte Carlo Simulator to explore the best- and worst-case scenarios for a base station to initiate its queries to all sensors. Monte Carlo Simulator is utilized to evaluate the throughput, which is the amount of data collected at the base station, under three schemes; contiguous aggregation, aggregation with overlapping of sensing tasks, and aggregation with overlapping of sensing and processing tasks. Our simulation results demonstrate that, for the WSN of 25 sensors with a single base station deployed within the WSN, the aggregation scheme with overlapping of sensing and processing tasks shows better performance by aggregating a minimum of 56% of the data in lower time duration in comparison to other schemes.

Optimized capacity planning and performance measurement through OPNET Modeler

This paper presents a number of performance assessment studies of the capacity planning operations on existing networks using OPNET Modeler. We have combined a novel custom-made planning tool and OPNET Modeler to redesign and evaluate an existing network through various redesign techniques, which involve relocating the existing nodes and consolidating clusters (sub-networks). The proposed tool is intended with the conscious to reduce the extra-traffic and the operational/maintenance cost of the network, where Simulated Annealing and Genetic Algorithm are utilized to search the redesign space to find enhanced network topologies. The commercial OPNET Modeler analyzes the performance of the redesigned topology at node (client) level through link utilization. Our simulation studies show a better trade-off by increasing the overall utilization of the redesigned network around 20%, thereby reducing the network maintenance cost accordingly.

An integrated restoration framework for coverage and communication within wireless sensor networks

The paper presents a novel integrated framework to restore the coverage and communication failures within a wireless sensor network (WSN) without adding new resources. We view WSN as a collection of tree topologies, where each tree comprises of base station (BS) as a root, and the sensors as rest of nodes. The sensor/BS failures produce a disjoint set of sensors, thus generating coverage and communication issues simultaneously. We have formulated the restoration within WSN as an optimisation problem, where the objective function is to maximise the lifespan of WSN, subject to energy constraints. The restoration framework employs Simulated Annealing to select the best alternate neighbouring sensor/BS to restore the coverage and communication. The simulation results of a typical WSN with 26% sensor failures and 40% BS failures demonstrate the capability of our framework to maintain 100% communications for up to 200 days of operation than without utilising restoration.

Comparing Communication Protocols within an Enterprise Network for Carbon Footprint Reduction

We present a comparison study between communication protocols relative to carbon footprint within enterprise network. The comparative study focuses on three factors; the communication protocols (transmission control protocol (TCP) and user datagram protocol (UDP)) of the transport layer, the quality of service (QoS) offered by the transmission line and the data encoding schemes in the physical layer. The high quality transmission lines produce low carbon footprint, whereby the maximum capacity of transmission line is utilized to reduce the number of transmissions. The carbon footprint of an enterprise is estimated from the power spectrum of the transmitted packets through Manchester coding. The enterprise is often susceptible to heavy transactions at the backbone, thereby producing more carbon footprint. Consequently, the carbon footprint reduction within the enterprise is formulated as an optimization problem, wherein the given single enterprise is synthesized into suitable clusters by integrating the heavily communicating nodes together. The simulation results demonstrate that a typical single enterprise comprising of 100 nodes with 4 GB backbone traffic when both the UDP and TCP utilize high capacity link produces low and nearly equal volumes of carbon. However, the difference becomes significantly high with the link offering poor QoS, in which, UDP based transmissions produce 14% less carbon than TCP based transmissions. The optimization within molecular assembly manages to produce 64.5% reduced annual carbon emission than the initial network.

Carbon offsetting through computer network redesign

Sustaining green communications in digital data transmission is gaining prime importance, as the 24/7 access networks contribute large electrical power consumption. Presently, the increased number of digital transactions in most of the enterprise network (EN) tremendously increases the volume of data transmitted through out the EN at all the time that would increase the electrical power consumption. We have proposed few operations to redesign the clusters of an enterprise network and we have modeled the cluster redesign problem as an optimization problem and utilized Simulated Annealing (SA) to search for the best re-clustering to reduce traffic at the backbone. The two redesign operations move node and swap nodes as the neighborhood functions in Simulated Annealing are utilized to reduce the traffic at the backbone of the enterprise network and we have extended our algorithm to prove that the decrease in volume of traffic at the backbone decreases the power consumption. We have selected Manchester coding to encode the generated and transmitted data, and it is our basic model to estimate the utilized power. Our simulation results demonstrate that an overall reduction in the backbone traffic after the redesign operations decreases the power consumption by 13% and 3.7% in move node and swap nodes operation, thus offsetting the carbon emissions per year by 45% and 13% respectively.