IMPROVED ROUTING PROTOCOLS BASED ON RPL FOR FULL IOT-WSN STACK

The Internet Engineering Task Force (IETF) standardized several protocols such as Constraint Application Protocol (CoAP) to run over WSN-IoT constrained devices. IPv6 is used to transmit packets over IEEE802.15.4 radio link called 6LoWPAN. The routing protocol for low power and lossy (RPL) network enable connectivity of WSN over IoT. Nodes in RPL optimized its path using objective function (OF), which depends on different node/link metrics. In this paper, the performance of IoT-WSN stack consisting of CoAP, 6LoWPAN and two proposed protocols based on RPL are evaluated. The two proposed protocols depend on a new OF based on link reliability and energy metric. The first is a modification of recently introduced protocol called Energy Threshold RPL (ETRPL) protocol. ETRPL uses the remaining energy of the preferred parent node as a metric. The other protocol used a new metric that combines energy consumption with ETX for all paths to the root called EERPL. The protocols are tested with full IoT-WSN stack and implemented using Cooja simulator. The results showed that ETRPL and EERPL performed better than standard RPL in terms of the energy consumption, average time delay, packet reception ratio, throughput and the number of dead nodes.

Unsupervised random forest for affinity estimation

This paper presents an unsupervised clustering random-forest-based metric for affinity estimation in large and high-dimensional data. The criterion used for node splitting during forest construction can handle rank-deficiency when measuring cluster compactness. The binary forest-based metric is extended to continuous metrics by exploiting both the common traversal path and the smallest shared parent node.The proposed forest-based metric efficiently estimates affinity by passing down data pairs in the forest using a limited number of decision trees. A pseudo-leaf-splitting (PLS) algorithm is introduced to account for spatial relationships, which regularizes affinity measures and overcomes inconsistent leaf assign-ments. The random-forest-based metric with PLS facilitates the establishment of consistent and point-wise correspondences. The proposed method has been applied to automatic phrase recognition using color and depth videos and point-wise correspondence. Extensive experiments demonstrate the effectiveness of the proposed method in affinity estimation in a comparison with the state-of-the-art.

Enhanced layered fog architecture for IoT sensing and actuation as a service

The reduced service cost offered by Sensing and Actuation as a Service paradigm, particularly in Internet of Things (IoT) era, has encouraged many establishments to start without worrying about having their own infrastructure. Such a paradigm is typically managed by a centralized cloud service provider. Fog paradigm has emerged as a mini-cloud that if designed with care to assist the cloud, together will achieve better performance. This article introduces a layered fog architecture called Sensors and Actuator Layered Fog Services Delivery (SALFSD) for IoT ecosystems. The significance of SALFSD is being fault resistant; it dynamically reassigns tasks of the failed node to the nearest active node to maintain the network connection. Besides, SALFSD monitors end users pre-specified cases closer to the physical devices hired by end users to fasten generating the actuation commands. Such node may offload its monitoring responsibility to its parent node in case it is overloaded. SALFSD is evaluated using Yet Another Fog Simulator in different scenarios (numbers of users, sensors, actuators, and areas). A comparison was made for Sensing and Actuating as a Service (SAaaS) with/without layered fog, and layered fog with/without (failure reassignment, pre-specified cases in fog nodes, and offloading). The comparison was conducted in terms of computing/communication latencies and the number of missed messages for both observations and actuation commands. Results show that failure reassignment prevented losing messages and maintained network connectivity. Also, wisely selecting the monitoring fog node per end user pre-specified cases and the offloading scheme decreased actuation latency.

THE IMPACT OF ORTHOGRAPHY ON LEXICAL ACCESS

Previous research has shown that orthographic marking may have a function beyond identifying orthographic word forms. In two visual priming experiments with native speakers and advanced learners of German (Czech natives) we tested the hypothesis that orthography can convey word-class cues comparable to morphological marking. We examined the effect of initial letter capitalization of nouns (a specific property of German orthography) on the processing of five homonymous and grammatically ambiguous forms. Both populations showed the same pattern of results: deverbal nouns (conversions) patterned together with countable nouns while in a previous study (with eliminated orthographic word-class cues) they patterned together with infinitives. Together, findings suggest that orthographic cues can trigger word-class-specific lexical retrieval/access. They also suggest a lexical entry structure in which conversion nouns, infinitives, and inflected verbal forms share a category-neutral parent node and that specified subnodes are accessed only when specifying cues are available and/or necessary for processing.

Incentives against Max-Min Fairness in a Centralized Resource System

Resource allocating mechanisms draw much attention from various areas, and exploring the truthfulness of these mechanisms is a very hot topic. In this paper, we focus on the max-min fair allocation in a centralized resource system and explore whether the allocation is truthful when a node behaves strategically. The max-min fair allocation enables nodes receive appropriate resources, and we introduce an efficient algorithm to find out the allocation. To explore whether the allocation is truthful, we analyze how the allocation varies when a new node is added to the system, and we discuss whether the node can gain more resources if it misreports its resource demands. Surprisingly, if a node misrepresents itself by creating several fictitious nodes but keeps the sum of these nodes’ resource demands the same, the node can achieve more resources evidently. We further present some illustrative examples to verify the results, and we show that a node can achieve 1.83 times resource if it misrepresents itself as two nodes. Finally, we discuss the influence of node’s misrepresenting behavior in tree graph: some child nodes gain fewer resources even if their parent node gains more resources by creating two fictitious nodes.

Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments

In order to achieve the safe and efficient navigation of mobile robots, it is essential to consider both the environmental geometry and kinodynamic constraints of robots. We propose a trajectory planner for car-like robots on the basis of the Dual-Tree RRT (DT-RRT). DT-RRT utilizes two tree structures in order to generate fast-growing trajectories under the kinodynamic constraints of robots. A local trajectory generator has been newly designed for car-like robots. The proposed scheme of searching a parent node enables the efficient generation of safe trajectories in cluttered environments. The presented simulation results clearly show the usefulness and the advantage of the proposed trajectory planner in various environments.

The Optimization Model of Composite Material UAV Shooting Flight Routes

UAV is one of the important achievements of scientific and technological innovation, which has been widely used in various fields of life in recent years. UAVs of composite materials are the most popular because the composite itself has designability, and can be optimized according to the strength and stiffness of the aircraft without changing the structural weight. In order to ensure the UAV to carry out more accurate image acquisition under the actual ground conditions, through the analysis of decision variables, this paper uses the linear weighting of image shooting range and pixel accuracy to establish the objective function, and establishes the optimal shooting angle under different constraints Considering the actual motion characteristics of objects such as automobiles, this paper assumes that the tracked ground targets are a class of motion objects with non-integrity constraints when the flight altitude of UAV is fixed and the flight speed is constant. The ground target model and the flight dynamics nonlinear model are established. This paper presents a new RRT* algorithm for path planning based on the obstacles encountered by UAV during flight, that is, using the cost function to select the node with the minimum cost in the field of expanding nodes as the parent node, using the MATLAB to select a reasonable obstacle avoidance strategy, the global optimal route is obtained by smoothing processing, and the data simulation test is carried out. The experimental results show that the model is robust.

Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing

Workflow scheduling is one of the significant issues for scientific applications among virtual machine migration, database management, security, performance, fault tolerance, server consolidation, etc. In this paper, existing time-based scheduling algorithms, such as first come first serve (FCFS), min–min, max–min, and minimum completion time (MCT), along with dependency-based scheduling algorithm MaxChild have been considered. These time-based scheduling algorithms only compare the burst time of tasks. Based on the burst time, these schedulers, schedule the sub-tasks of the application on suitable virtual machines according to the scheduling criteria. During this process, not much attention was given to the proper utilization of the resources. A novel dependency and time-based scheduling algorithm is proposed that considers the parent to child (P2C) node dependencies, child to parent node dependencies, and the time of different tasks in the workflows. The proposed P2C algorithm emphasizes proper utilization of the resources and overcomes the limitations of these time-based schedulers. The scientific applications, such as CyberShake, Montage, Epigenomics, Inspiral, and SIPHT, are represented in terms of the workflow. The tasks can be represented as the nodes, and relationships between the tasks can be represented as the dependencies in the workflows. All the results have been validated by using the simulation-based environment created with the help of the WorkflowSim simulator for the cloud environment. It has been observed that the proposed approach outperforms the mentioned time and dependency-based scheduling algorithms in terms of the total execution time by efficiently utilizing the resources.

Handling Quantity in Variability Models for System-of-Systems

Problem: Modern systems contain parts that are themselves systems. Such complex systems thus have sets of subsystems that have their own variability. These subsystems contribute to the functionality of a whole system-of-systems (SoS). Such systems have a very high degree of variability. Therefore, a modeling technique for the variability of an entire SoS is required to express two different levels of variability: variability of the SoS as a whole and variability of subsystems. If these levels are described together, the model becomes hard to understand. When the variability model of the SoS is described separately, each variability model is represented by a tree structure and these models are combined in a further tree structure. For each node in a variability model, a quantity is assigned to express the multiplicity of its instances per one instance of its parent node. Quantities of the whole system may refer to the number of subsystem instances in the system. From the viewpoint of the entire system, constraints and requirements written in natural language are often ambiguous regarding the quantities of subsystems. Such ambiguous constraints and requirements may lead to misunderstandings or conflicts in an SoS configuration. Approach: A separate notion is proposed for variability of an SoS; one model considers the SoS as an undivided entity, while the other considers it as a combination of subsystems. Moreover, a domain-specific notation is proposed to express relationships among the variability properties of systems, to solve the ambiguity of quantities and establish the total validity. This notation adapts an approach, named Pincer Movement, which can then be used to automatically deduce the quantities for the constraints and requirements. Validation: The descriptive capability of the proposed notation was validated with four examples of cloud providers. In addition, the proposed method and description tool were validated through a simple experiment on describing variability models with real practitioners.

Semantic Discovery of Composite GIS Services

With an increasing number of Geographical Information System (GIS) services publicly available on the Web, the discovery of composite GIS services is promising when novel requirements are to be satisfied. GIS services in the repository like ArcGIS software are organized in a tree hierarchy, where a parent node represents a categorial GIS service with a coarser-granularity than its child GIS services, while leaf nodes correspond to atomic and exercisable GIS services. In this setting, discovering appropriate atomic GIS services is challenging. To remedy this issue, this paper proposes a composite GIS service discovery mechanism. Specifically, for the given requirement, select the parent nodes that take the given input parameters as input and remove their inactivated children. Use remaining children to build the network and repeat the previous operation until finding the services that contain the required output. Then record the semantic similarity degree, calculated by services functional description, in this network. By using the simulated annealing algorithm, a composite GIS services solution will be recommended from this semantic network. Evaluation results demonstrate that our approach could give more significant solution compared with the state-of-the-art techniques.