Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of Distance between Nodes in Wireless Mesh Networks

Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%

Ant-based evidence distribution with periodic broadcast in attacked wireless network

In order to establish trust among nodes in large wireless networks, the trust certicates need to be distributed and be readily accessible. However, even so, searching for trust certicates will still become highly cost and delay especially when wireless network is suering CTS jamming attack. We believe the individual solution can lead us to solve this combination problems in the future. Therefore, in this work, we investigate the delay and cost of searching a distributed certicate and the adverse eects of fabiricated control packet attacks on channel throughput and delivery ratio respectively, and propose two techniques that can improve the eciency of searching for such certicates in the network and mitigate the CTS jamming attack's eect. Evidence Distribution based on Periodic Broadcast (EDPB) is the rst solution we presented to help node to quickly locate trust certicates in a large wireless sensor network. In this solution, we not only take advantages from swarm intelligence alogrithm, but also allow nodes that carrying certicates to periodically announce their existence. Such announcements, together with a swarm-intelligence pheromone pdate procedure, will leave traces on the nodes to lead query packets toward the certicate nodes. We then investigate the salient features of this schema and evaluate its performance in both static and mobile networks. This schema can also be used for other essential information dissemination in mobile ad hoc networks. The second technqiue, address inspection schema (AIS) xes vulnerabilities exist in distribution coordinating function (DCF) dened in IEEE 802.11 standard so that each node has the ability to beat the impact of CTS jamming attack and furthermore, benets network throughput. We then perform ns-2 simulations to evaluate the benet of AIS

Ant-Fuzzy Meta Heuristic Genetic Sensor Network System for Multi Sink Aggregated Data Transmission

Wireless sensor network with the hierarchical organization of sensors aggregate the tasks into groups. The sensor nodes broadcast the aggregated data directly to the distant base station. Existing Mixed Integer Programming (MIP) formulation obtain the good solutions for multi-action processes but not effectual in developing the hybrid genetic algorithms with the Tabu search meta-heuristics ant colony optimization. Another existing work developed for security purpose named as Dynamic secure end-to-end Data Aggregation with Privacy function (DyDAP) decrease the network load but topological configurations with multiple sinks are not addressed. To develop the hybrid genetic algorithm on ant-fuzzy system, Hybrid (i.e.,) ant-fuzzy Meta-heuristic Genetic method (HMG) based on the Tabu search is proposed in this paper. Ant-fuzzy Meta heuristic Genetic method carries out the classification process on the aggregated data. The classification based on the genetic method uses the Tabu search based mathematical operation to attain the feasible solution on multiple sinks. Initially, Ant-fuzzy Meta-heuristic Genetic method classifies the data record based on the weighted meta-heuristic distance. The classified records perform the Tabu search operation to transmit the aggregated data to the multiple sink nodes. HMG method achieves approximately 19 % improved transmitted message rate. Experiment is conducted in the network simulator on the factor such as classification time and transmission rate

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

The current market’s demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature’s insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufactur- ing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets

Resource discovery for distributed computing systems: A comprehensive survey

Large-scale distributed computing environments provide a vast amount of heterogeneous computing resources from different sources for resource sharing and distributed computing. Discovering appropriate resources in such environments is a challenge which involves several different subjects. In this paper, we provide an investigation on the current state of resource discovery protocols, mechanisms, and platforms for large-scale distributed environments, focusing on the design aspects. We classify all related aspects, general steps, and requirements to construct a novel resource discovery solution in three categories consisting of structures, methods, and issues. Accordingly, we review the literature, analyzing various aspects for each category

Optimising routing and trustworthiness of ad hoc networks using swarm intelligence

This thesis was submitted for the degree of Doctor of Philsophy and awarded by Brunel UniversityThis thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes

Wireless Mesh Networks Based on MBPSO Algorithm to Improvement Throughput

Wireless Mesh Networks can be regarded as a type of communication technology in mesh topology in which wireless nodes interconnect with one another. Wireless Mesh Networks depending on the semi-static configuration in different paths among nodes such as PDR, E2E delay and throughput. This study summarized different types of previous heuristic algorithms in order to adapt with proper algorithm that could solve the issue. Therefore, the main objective of this study is to determine the proper methods, approaches or algorithms that should be adapted to improve the throughput. A Modified Binary Particle Swarm Optimization (MBPSO) approach was adapted to improvements the throughput. Finally, the finding shows that throughput increased by 5.79% from the previous study