We describe Charm++, an object oriented portable parallel programming language based on C++. Its design philosophy, implementation, sample applications and their performance on various parallel machines are described. Charm++ is an explicitly parallel language consisting of C++ with a few extensions. It provides a clear separation between sequential and parallel objects. The execution model of Charm++ is message driven, thus helping one write programs that are latency-tolerant. The language supports multiple inheritance, dynamic binding, overloading, strong typing, and reuse for parallel objects, all of which are more difficult problems in a parallel context. Charm++ provides specific modes for sharing information between parallel objects. It is based on the Charm parallel programming system, and its runtime system implementation reuses most of the runtime system for Charm.

CHARM++: a portable concurrent object oriented system based on C++

The Internet Protocol.

Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs.

/pdf/towards-the-unmanned-aerial-vehicles-uavs-a-comprehensive-4zn6jnyk.pdf

Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review

The Internet of Things (IoT) is undeniably transforming the way that organizations communicate and organize everyday businesses and industrial procedures. Its adoption has proven well suited for sectors that manage a large number of assets and coordinate complex and distributed processes. This survey analyzes the great potential for applying IoT technologies (i.e., data-driven applications or embedded automation and intelligent adaptive systems) to revolutionize modern warfare and provide beneﬁts similar to those in industry. It identiﬁes scenarios where Defense and Public Safety (PS) could leverage better commercial IoT capabilities to deliver greater survivability to the warﬁghter or ﬁrst responders, while reducing costs and increasing operation efﬁciency and effectiveness. This article reviews the main tactical requirements and the architecture, examining gaps and shortcomings in existing IoT systems across the military ﬁeld and mission-critical scenarios. The review characterizes the open challenges for a broad deployment and presents a research roadmap for enabling an affordable IoT for defense and PS.

https://www.mdpi.com/1424-8220/16/10/1644/pdf

A Review on Internet of Things for Defense and Public Safety.

Fifth generation wireless networks are expected to provide advanced capabilities and create new markets. Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of unmanned aerial vehicles (UAVs) to collect data in dense wireless sensor networks using projection-based compressive data gathering (CDG) as a novel solution methodology. CDG is utilized to aggregate data en-route from a large set of sensor nodes to selected projection nodes acting as cluster heads (CHs) in order to reduce the number of needed transmissions leading to notable energy savings and extended network lifetime. The UAV transfers the gathered data from the CHs to a remote sink node, e.g., a 5G cellular base station, which avoids the need for long range transmissions or multihop communications among the sensors. Our problem definition aims at clustering the sensors, constructing an optimized forwarding tree per cluster, and gathering the data from selected CH nodes based on projection-based CDG with minimized UAV trajectory distance. We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. We demonstrate the superiority of the proposed approach and the designed algorithms via detailed performance results with analysis, comparisons, and insights.

UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks

Wireless power transfer (WPT) techniques are important in a variety of applications in both civilian and military fields. Unmanned aerial vehicles (UAVs) are being used for many practical purposes, such as monitoring or delivering payloads. There is a trade-off between the weight of the UAVs or their batteries and their flying time. Their working time is expected to be as long as possible. In order to support the UAVs to work effectively, WPT techniques are applied with UAVs to charge secondary energy supply sources in order to increase their working time. This paper reviews common techniques of WPT deployed with UAVs to support them while working for different purposes. Numerous approaches have been considered to illustrate techniques to exploit WPT techniques. The charging distances, energy harvesting techniques, electronic device improvements, transmitting issues, etc., are considered to provide an overview of common problems in utilizing and charging UAVs. Moreover, specific problems are addressed to support suitable solutions with either techniques or applications for UAVs.

https://www.mdpi.com/2079-9292/9/3/461/pdf

Electromagnetic Field Based WPT Technologies for UAVs: A Comprehensive Survey

Random walk (RW) routing for monitoring purposes in Wireless Sensor Networks (WSNs) has been proven to be an energy-efficient method. In this paper, we exploit the integration between Compressive Sensing (CS) and RW to reduce energy consumption for such networks. All the sensory data is reconstructed at the base-station (BS) based on a smaller number of CS measurements compared to the total number of sensor nodes. Each CS measurement is collected through a RW routing with a predefined length. All random CS measurements are forwarded to the BS for the CS recovery process in two either ways: directly or by relaying through intermediate nodes. A trade-off between the sensor transmission range and the length of RWs is investigated for the networks to achieve the smallest energy consumption. We further formulate the average consumed energy of each random walk based on the sensor transmission range. The average consumed energy to send the measurements from RWs to the BS either directly or by relaying in multi-hop are formulated and analyzed. We calculate the total energy consumption in different conditions and suggest the optimal case for the networks to spend the least energy that significantly prolongs the network lifetime.

Compressive sensing based random walk routing in wireless sensor networks

Compressive sensing (CS) provides a new paradigm for data collection in wireless sensor networks (WSNs). In this paper, we continue to exploit the integration between CS and tree-based data gathering in WSNs. Based on a tree formed as down-stream generations from the sink or base-station (BS), each parent node stores its children's readings and the corresponding measurement vectors through the data collecting process. All sensors send their own readings only once to their parents. The parent nodes generate measurements based on the projection matrix and then forward a certain number of measurements required to the upper nodes or the BS. The CS recovery algorithm implemented at the BS reconstructs precise readings from all sensors. This significantly reduces a certain number of transmissions in routing. Two additional ideas are suggested related to sensor transmission range and the probability of non-zero elements in the projection matrix for the purpose of reducing power consumption for the networks.

Tree-based energy-efficient data gathering in wireless sensor networks deploying compressive sensing

Data traversing packet networks experience varying delays, resulting in interarrival jitter. This can result in degraded performance in real-time multimedia communications applications if the jitter delays are large or unaccounted for in the receiver application. This paper examines modeling and simulation of network jitter delay for real-time multimedia communications applications. We examine the multistructure characteristics of network delay and develop a model for simulation of jitter. The model is confirmed empirically using collected packet network jitter delay statistics.

An interarrival delay jitter model using multistructure network delay characteristics for packet networks

Compressive Sensing (CS) represents a new paradigm that addresses the problem of power consumption for collecting data over wireless sensor networks (WSN). Intercluster multi-hop routing, referred to as ICCS, is proposed as an extension to clustering in WSN utilizing CS to further reduce power consumption. With ICCS, CS measurements are relayed from each cluster head (CH) to the base station rather than being transmitted directly. A greedy algorithm is proposed to form a routing tree between the CHs and the base station. Total power consumption for networks supporting intra-cluster and inter-cluster transmission is formulated and compared to cluster based compressive sensing. Network characteristics are analyzed and optimal cases for least power consumption with ICCS are identified.

Inter-cluster Multi-hop Routing in Wireless Sensor Networks Employing Compressive Sensing

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Keith A. Teague

Author Tools

Chat about Author