Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results

Intelligent Technique for Seamless Vertical Handover in Vehicular Networks

Seamless mobility is a challenging issue in the area of research of vehicular networks that are supportive of various applications dealing with the intelligent transportation system (ITS). The conventional mobility management plans for the Internet and the mobile ad hoc network (MANET) is unable to address the needs of the vehicular network and there is severe performance degradation because of the vehicular networks’ unique characters such as high mobility. Thus, vehicular networks require seamless mobility designs that especially developed for them. This research provides an intelligent algorithm in providing seamless mobility using the media independent handover, MIH (IEEE 802.21), over heterogeneous networks with different access technologies such as Worldwide Interoperability for Microwave Access (WiMAX), Wireless Fidelity (Wi-Fi), as well as the Universal Mobile Telecommunications System (UMTS) for improving the quality of service (QoS) of the mobile services in the vehicular networks. The proposed algorithm is a hybrid model which merges the biogeography-based optimization or BBO with the Markov chain. The findings of this research show that our method within the given scenario can meet the requirements of the application as well as the preferences of the users

A comparative study of task assignment and path planning methods for multi-UGV missions

Many important problems involving a group of unmanned ground vehicles (UGVs) are closely related to the multi traviling salesman problem (m-TSP). This paper comprises a comparative study of a number of algorithms proposed in the litterature to solve m-TSPs occuring in robotics. The investigated algoritms include two mixed integer linear programming (MILP) formulations, a market based approach (MA), a Voronoi partition step (VP) combined with the local search used in MA, and a deterministic and a stocastic version of the granular tabu search (GTS). To evaluate the algoritms, an m-TSP is derived from a planar environment with polygonal obstacles and uniformly distributed targets and vehicle positions. The results of the comparison indicate that out of the decentralized approaches, the MA yield good solutions but requires long computation times, while VP is fast but not as good. The two MILP approaches suffer from long computation times, and poor results due to the decomposition of the assignment and path planning steps. Finally, the two GTS algorithms yield good results in short times with inputs from MA as well as the much faster VP. Thus the best performing centralized approach is the GTS in combination with the VP

Energy-efficient and reliable data delivery in wireless sensor networks

Clustering has been used as one of energyefficient mechanisms for data routing in wireless sensor networks. In hierarchical routing approaches, cluster heads are responsible for management (e.g. data aggregation, queries dispatch) and transmission of the collected data in the region controlled by them. For efficient data delivery, several researches have proposed various mechanisms for cluster organization and cluster head selection. However, less focus is given in the area of data transmission associated with Base Station (BS). In such a situation, any failure or packet loss may lead to considerable packet loss. For solving this problem, we propose an efficient data routing scheme for controlling data delivery from nodes to BS. In our proposed approach every node is aware about the link quality of all nodes and is able to deliver data to the BS through the most reliable and energy-efficient route

Multi-objective UAS flight management in time constrained low altitude local environments

This paper presents a new framework for Multi-Objective Flight Management of Unmanned Aerial Systems (UAS), operating in partially known environments, where planning time constraints are present. During UAS operations, civilian UAS may have multiple objectives to meet including: platform safety; minimizing fuel, time, distance; and minimizing deviation from the current path. The planning layers within the framework use multi-objective optimization to converge to a solution which better reflects overall mission requirements. The solution must be generated within the available decision window, else the UAS must enter a safety state; this potentially limits mission efficiency. Local or short range planning at low altitudes requires the classification of terrain and infrastructure in proximity as potential obstacles. The potential increase in the number of obstacles present further reduces the decision window in comparison to high altitude flight. A novel Flight Management System (FMS) has been incorporated within the framework to moderate the time available to the environment abstraction, path and trajectory planning layers for more efficient use of the available decision window. Enabling the FMS during simulation increased the optimality of the output trajectory on systems with sufficient computational power to run the algorithm in real time. Conversely, the FMS found sub-optimal solutions for the system with insufficient computational capability once the objective utility threshold was decreased from 0.95 to 0.85. This allowed the UAS to continue operations without having to resort to entering a safe state

The impact of ebony wood harvesting on Diospyros samoensis (Ebenaceae) on Vangunu Island, Western Solomon Islands

Ebony wood, the black heartwood of trees in the genus Diospyros, is a high-value commodity of many Pacific Islands. The revenue earned from the sale of ebony carvings is important for many low-income rural communities, resulting in high harvesting pressure and reported declines of ebony-producing species. This study investigates the impact of ebony wood harvesting on species of Diospyros on Vangunu Island, Western Solomon Islands. Diospyros samoensis, locally known as rihe, was the main source of ebony wood, with D. vera occasionally harvested but producing poorer quality wood. For D. samoensis, we investigated the existing ethnobotanical knowledge and harvesting dynamics using questionnaires and surveyed eleven populations using five 15 × 15 m plots. Although D. samoensis was common throughout the study area, trees with harvestable ebony heartwood were considered rare. The sale of ebony carvings contributed substantially to the livelihood of carvers. Harvesting practices cause considerable damage to the stem and appeared to alter population structure, with fewer seedlings found in stands with higher harvesting intensities (r = -0.704, p = 0.008). Therefore, populations of D. samoensis appear to be negatively impacted by current harvesting practices, which should be modified to 1) cause less damage to individual trees and populations and 2) protect larger and older trees to help regeneration. Therefore, the increasing rarity of ebony heartwood in the Pacific may not equate to dangerous declines in Diospyros species and implementing low-impact harvesting practices could help improve the health and long-term persistence of Diospyros populations