Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Secure and Energy Efficient Data Aggregation Technique for Cluster Based Wireless Sensor Network

In the past few years secure transmission of data along with efficiency is a serious issue for wireless sensor networks (WSNs).Clustering is a powerful and convenient way to enhance performance of the WSNs system. In this project work, a secure transmission of data for cluster-based WSNs (CWSNs) is studied, where the clusters are formed dynamically and infrequently. Basically protocols for CWSNs, called SET-IBS (Identity-Based digital Signature)scheme and SET-IBOOS (Identity-Based Online / Offline digital Signature)scheme, correspondingly. In SET-IBS, security relies on the hardness of the Dill-Hellman difficulty in the pairing area. Data aggregation is the process of abbreviation and combining sensor data in order to reduce the amount of data transmission in the network. This paper investigates the relationship between security and data aggregation process in wireless sensor networks. In this paper propose SET-IBS and data aggregation techniques for secure and efficient data transmission. For energy consumption using DRINA algorithm. DRINA means Data Routing for In-Network Aggregation, that has some key aspects such as high aggregation rate, a reduced number of messages for setting up a routing

MANET Network in Internet of Things System

In the current world of technology, various physical things can be used for facilitation of a human work. That is why the Internet of Things,an innovative technology and a good solution which allows the connection of the physical things with the digital world through the use of heterogeneous networks and communication technologies, is used. The Internet of Things in smart environments interacts with wireless sensor network (WSN) and mobile ad‐hoc network (MANET), making it even more attractive to the users and economically successful. Interaction between wireless sensor and mobile ad‐hoc networks with the Internet of Things allows the creation of a new MANET‐IoT systems and IT‐based networks. Such the system gives the greater mobility for a user and reduces deployment costs of the network. However, at the same time it opens new challenging issues in its networking aspects as well. In this work, the authors propose a routing solution for the Internet of Things system using a combination of MANET protocols and WSN routing principles. The presented results of solution\u27s investigation provide an effective approach to efficient energy consumption in the global MANET‐IoT system. And that is a step forward to a reliable provision of services over global Future Internet infrastructure

Route discovery based on energy-distance aware routing scheme for MANET

Route discovery proses in a Mobile Ad hoc Network (MANET) is challenging due to the limitation of energy at each network node. The energy constraint limits network connection lifetime thus affecting the routing process. Therefore, it is necessary for each node in the network to calculate routing factor in terms of energy and distance in deciding optimal candidate relay nodes needed to forward packets. This study proposes a new route discovery mechanism called the Energy-Distance Routing Aware (EDRA) that determines the selection of nodes during route discovery process to improve the network connection lifetime. This mechanism comprises of three schemes namely the Energy-Distance Factor Aware (EDFA), the Energy-Distance Forward Strategy (EDFS), and the Energy-Aware Route Selection (EARS). The EDFA scheme begins by calculating each nodes energy level (ei) and the distance (di) to the neighbouring nodes to produce the energy-distance factor value used in selecting the relay nodes. Next, the EDFS scheme forwards route request packets within discovery area of relay nodes based on the number of nodes. Then, the EARS scheme selects stable routing path utilising updated status information from EDFA and EDFS. The evaluation of EDRA mechanism is performed using network simulator Ns2 based on a defined set of performance metrics, scenarios and network scalability. The experimental results show that the EDRA gains significant improvement in the network connection lifetime when compared to those of the similar mechanisms, namely the AODV and the DREAM. EDRA also optimises energy consumption by utilising efficient forwarding decisions on varying scale of network nodes. Moreover, EDRA maximizes network connection lifetime while preserving throughput and packet drop ratio. This study contributes toward developing an efficient energy-aware routing to sustain longer network connection lifetime in MANET environment. The contribution is significant in promoting the use of green and sustainable next generation network technology

Performance optimization of wireless sensor networks for remote monitoring

Wireless sensor networks (WSNs) have gained worldwide attention in recent years because of their great potential for a variety of applications such as hazardous environment exploration, military surveillance, habitat monitoring, seismic sensing, and so on. In this thesis we study the use of WSNs for remote monitoring, where a wireless sensor network is deployed in a remote region for sensing phenomena of interest while its data monitoring center is located in a metropolitan area that is geographically distant from the monitored region. This application scenario poses great challenges since such kind of monitoring is typically large scale and expected to be operational for a prolonged period without human involvement. Also, the long distance between the monitored region and the data monitoring center requires that the sensed data must be transferred by the employment of a third-party communication service, which incurs service costs. Existing methodologies for performance optimization of WSNs base on that both the sensor network and its data monitoring center are co-located, and therefore are no longer applicable to the remote monitoring scenario. Thus, developing new techniques and approaches for severely resource-constrained WSNs is desperately needed to maintain sustainable, unattended remote monitoring with low cost. Specifically, this thesis addresses the key issues and tackles problems in the deployment of WSNs for remote monitoring from the following aspects. To maximize the lifetime of large-scale monitoring, we deal with the energy consumption imbalance issue by exploring multiple sinks. We develop scalable algorithms which determine the optimal number of sinks needed and their locations, thereby dynamically identifying the energy bottlenecks and balancing the data relay workload throughout the network. We conduct experiments and the experimental results demonstrate that the proposed algorithms significantly prolong the network lifetime. To eliminate imbalance of energy consumption among sensor nodes, a complementary strategy is to introduce a mobile sink for data gathering. However, the limited communication time between the mobile sink and nodes results in that only part of sensed data will be collected and the rest will be lost, for which we propose the concept of monitoring quality with the exploration of sensed data correlation among nodes. We devise a heuristic for monitoring quality maximization, which schedules the sink to collect data from selected nodes, and uses the collected data to recover the missing ones. We study the performance of the proposed heuristic and validate its effectiveness in improving the monitoring quality. To strive for the fine trade-off between two performance metrics: throughput and cost, we investigate novel problems of minimizing cost with guaranteed throughput, and maximizing throughput with minimal cost. We develop approximation algorithms which find reliable data routing in the WSN and strategically balance workload on the sinks. We prove that the delivered solutions are fractional of the optimum. We finally conclude our work and discuss potential research topics which derive from the studies of this thesis

Autonomous Sailboat Navigation

The purpose of this study was to investigate novel methods on an unmanned sailing boat, which enables it to sail fully autonomously, navigate safely, and perform long-term missions. The author used robotic sailing boat prototypes for field experiments as his main research method. Two robotic sailing boats have been developed especially for this purpose. A compact software model of a sailing boat's behaviour allowed for further evaluation of routing and obstacle avoidance methods in a computer simulation. The results of real-world experiments and computer simulations are validated against each other. It has been demonstrated that autonomous boat sailing is possible by the effective combination of appropriate new and novel techniques that will allow autonomous sailing boats to create appropriate routes, to react properly on obstacles and to carry out sailing manoeuvres by controlling rudder and sails. Novel methods for weather routing, collision avoidance, and autonomous manoeuvre execution have been proposed and successfully demonstrated. The combination of these techniques in a layered hybrid subsumption architecture make robotic sailing boats a promising tool for many applications, especially in ocean observation