A Force Saving in Wireless Device Networks over Multihop Bunch Formula

One of the vital issues for wireless sensing element networks is increasing the network time period. Bunch is associate economical technique for prolonging the time period of wireless sensing element networks. This thesis proposes a multihop bunch formula (MHC-multihop clustering algorithm) for energy saving in wireless sensing element networks. MHC selects the clusterheads consistent with theto parameters the remaining energy and node degree. Additionally cluster heads choose their members consistent with the two parameters of sensing element the remaining energy and therefore the distance to its cluster head. MHC is finished in 3 phases quickly. Simulation results show that the planned formula will increase the network time period over 16 % compared of the LEACH(Low-energy adaptive clustering hierarchy) protocol

An Outline of Security in Wireless Sensor Networks: Threats, Countermeasures and Implementations

With the expansion of wireless sensor networks (WSNs), the need for securing the data flow through these networks is increasing. These sensor networks allow for easy-to-apply and flexible installations which have enabled them to be used for numerous applications. Due to these properties, they face distinct information security threats. Security of the data flowing through across networks provides the researchers with an interesting and intriguing potential for research. Design of these networks to ensure the protection of data faces the constraints of limited power and processing resources. We provide the basics of wireless sensor network security to help the researchers and engineers in better understanding of this applications field. In this chapter, we will provide the basics of information security with special emphasis on WSNs. The chapter will also give an overview of the information security requirements in these networks. Threats to the security of data in WSNs and some of their counter measures are also presented

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

Powerful mobile nodes for enhancing wireless sensor networks\u27 security and lifetime

To maintain the proper functioning of critical applications based on Wireless Sensor Networks, we must provide an acceptable level of security while taking into account limited capabilities of the sensors. In this paper we proposed a mobile approach to secure data exchanged by structured nodes in cluster. The approach is based on mobile nodes with significant calculation and energy resources that allow cryptographic key management and periodic rekeying. However, mobility in wireless sensor networks aims to increase the security and lifetime of the entire network. The technical methods used in this paper are based on cryptography elliptic curves and key management through a balanced binary tree. To compare the performance of the proposed approach with other mobile algorithms, we focused on the following metrics: the energy consumed by normal sensors and cluster heads, the number of packets exchanged during key installation, time to generate and distribute cryptographic keys, and the memory used by the different sensors to store keys

An energy-efficient routing protocol for Hybrid-RFID Sensor Network

Radio Frequency Identification (RFID) systems facilitate detection and identification of objects that are not easily detectable or distinguishable. However, they do not provide information about the condition of the objects they detect. Wireless sensor networks (WSNs), on the other hand provide information about the condition of the objects as well as the environment. The integration of these two technologies results in a new type of smart network where RFID-based components are combined with sensors. This research proposes an integration technique that combines conventional wireless sensor nodes, sensor-tags, hybrid RFID-sensor nodes and a base station into a smart network named Hybrid RFID-Sensor Network (HRSN)

Random Neural Networks and Optimisation

In this thesis we introduce new models and learning algorithms for the Random Neural Network (RNN), and we develop RNN-based and other approaches for the solution of emergency management optimisation problems. With respect to RNN developments, two novel supervised learning algorithms are proposed. The first, is a gradient descent algorithm for an RNN extension model that we have introduced, the RNN with synchronised interactions (RNNSI), which was inspired from the synchronised firing activity observed in brain neural circuits. The second algorithm is based on modelling the signal-flow equations in RNN as a nonnegative least squares (NNLS) problem. NNLS is solved using a limited-memory quasi-Newton algorithm specifically designed for the RNN case. Regarding the investigation of emergency management optimisation problems, we examine combinatorial assignment problems that require fast, distributed and close to optimal solution, under information uncertainty. We consider three different problems with the above characteristics associated with the assignment of emergency units to incidents with injured civilians (AEUI), the assignment of assets to tasks under execution uncertainty (ATAU), and the deployment of a robotic network to establish communication with trapped civilians (DRNCTC). AEUI is solved by training an RNN tool with instances of the optimisation problem and then using the trained RNN for decision making; training is achieved using the developed learning algorithms. For the solution of ATAU problem, we introduce two different approaches. The first is based on mapping parameters of the optimisation problem to RNN parameters, and the second on solving a sequence of minimum cost flow problems on appropriately constructed networks with estimated arc costs. For the exact solution of DRNCTC problem, we develop a mixed-integer linear programming formulation, which is based on network flows. Finally, we design and implement distributed heuristic algorithms for the deployment of robots when the civilian locations are known or uncertain

A Mini Review of Peer-to-Peer (P2P) for Vehicular Communication

In recent times, peer-to-peer (P2P) has evolved, where it leverages the capability to scale compared to server-based networks. Consequently, P2P has appeared to be the future distributed systems in emerging several applications. P2P is actually a disruptive technology for setting up applications that scale to numerous concurrent individuals. Thus, in a P2P distributed system, individuals become themselves as peers through contributing, sharing, and managing the resources in a network. In this paper, P2P for vehicular communication is explored. A comprehensive of the functioning concept of both P2P along with vehicular communication is examined. In addition, the advantages are furthermore conversed for a far better understanding on the implementation