Reducing Communication Overhead in Threshold Monitoring with Arithmetic Aggregation

2009 ◽  
Author(s):  
Yuanqiang Huang ◽  
Yongjian Wan ◽  
Yinan Ren ◽  
BingHeng Yan ◽  
Zhongzhi Luan ◽  
...  
Keyword(s):  
Communication Overhead ◽  
Threshold Monitoring

An Efficient Cluster-Based Flooding Using Fuzzy Logic Scheme (CBF2S) In Mobile Adhoc Networks

2020 ◽  
Vol 14 ◽  
Author(s):  
S. Mahima ◽  
N. Rajendran
Keyword(s):  
Fuzzy Logic ◽  
Ad Hoc ◽  
Link Quality ◽  
Traffic Load ◽  
Node Degree ◽  
Communication Overhead ◽  
Delivery Ratio ◽  
Node Mobility ◽  
Centralized Control ◽  
Hop Count

: Mobile ad hoc networks (MANET) hold a set of numerous mobile computing devices useful for communication with one another with no centralized control. Due to the inherent features of MANET such as dynamic topology, constrained on bandwidth, energy and computing resources, there is a need to design the routing protocols efficiently. Flooding is a directive for managing traffic since it makes use of only chosen nodes for transmitting data from one node to another. This paper intends to develop a new Cluster-Based Flooding using Fuzzy Logic Scheme (CBF2S). To construct clusters and choose proper cluster heads (CHs), thefuzzy logic approach is applied with the use of three parameters namely link quality, node mobility and node degree. The presented model considerably minimizes the number of retransmissions in the network. The presented model instructs the cluster members (CM) floods the packets inside a cluster called intra-cluster flooding and CHs floods the packets among the clusters called inter-cluster flooding. In addition, the gateway sends a packet to another gateway for minimizing unwanted data retransmissions when it comes under different CH. The presented CBF2S is simulated using NS2 tool under the presence of varying hop count. The CBF2S model exhibits maximum results over the other methods interms of overhead, communication overhead, traffic load, packet delivery ratio and the end to end delay.

scholarly journals Monitoring Wind Turbine Gearbox with Echo State Network Modeling and Dynamic Threshold Using SCADA Vibration Data

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 982 ◽  
Author(s):  
Xin Wu ◽  
Hong Wang ◽  
Guoqian Jiang ◽  
Ping Xie ◽  
Xiaoli Li
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Operating Conditions ◽  
Dynamic Threshold ◽  
Detection Accuracy ◽  
Echo State Network ◽  
Monitoring Method ◽  
Vibration Data ◽  
Static Monitoring ◽  
Threshold Monitoring

Health monitoring of wind turbine gearboxes has gained considerable attention as wind turbines become larger in size and move to more inaccessible locations. To improve the reliability, extend the lifetime of the turbines, and reduce the operation and maintenance cost caused by the gearbox faults, data-driven condition motoring techniques have been widely investigated, where various sensor monitoring data (such as power, temperature, and pressure, etc.) have been modeled and analyzed. However, wind turbines often work in complex and dynamic operating conditions, such as variable speeds and loads, thus the traditional static monitoring method relying on a certain fixed threshold will lead to unsatisfactory monitoring performance, typically high false alarms and missed detections. To address this issue, this paper proposes a reliable monitoring model for wind turbine gearboxes based on echo state network (ESN) modeling and the dynamic threshold scheme, with a focus on supervisory control and data acquisition (SCADA) vibration data. The aim of the proposed approach is to build the turbine normal behavior model only using normal SCADA vibration data, and then to analyze the unseen SCADA vibration data to detect potential faults based on the model residual evaluation and the dynamic threshold setting. To better capture temporal information inherent in monitored sensor data, the echo state network (ESN) is used to model the complex vibration data due to its simple and fast training ability and powerful learning capability. Additionally, a dynamic threshold monitoring scheme with a sliding window technique is designed to determine dynamic control limits to address the issue of the low detection accuracy and poor adaptability caused by the traditional static monitoring methods. The effectiveness of the proposed monitoring method is verified using the collected SCADA vibration data from a wind farm located at Inner Mongolia in China. The results demonstrated that the proposed method can achieve improved detection accuracy and reliability compared with the traditional static threshold monitoring method.

scholarly journals MedShard: Electronic Health Record Sharing Using Blockchain Sharding

2021 ◽  
Vol 13 (11) ◽  
pp. 5889
Author(s):  
Faiza Hashim ◽  
Khaled Shuaib ◽  
Farag Sallabi
Keyword(s):  
Healthcare System ◽  
Small Groups ◽  
Network Performance ◽  
Communication Overhead ◽  
Privacy And Security ◽  
Health Records ◽  
Medical Practitioners ◽  
Blockchain Technology ◽  
Simulation Results ◽  
Electronic Health

Electronic health records (EHRs) are important assets of the healthcare system and should be shared among medical practitioners to improve the accuracy and efficiency of diagnosis. Blockchain technology has been investigated and adopted in healthcare as a solution for EHR sharing while preserving privacy and security. Blockchain can revolutionize the healthcare system by providing a decentralized, distributed, immutable, and secure architecture. However, scalability has always been a bottleneck in blockchain networks due to the consensus mechanism and ledger replication to all network participants. Sharding helps address this issue by artificially partitioning the network into small groups termed shards and processing transactions parallelly while running consensus within each shard with a subset of blockchain nodes. Although this technique helps resolve issues related to scalability, cross-shard communication overhead can degrade network performance. This study proposes a transaction-based sharding technique wherein shards are formed on the basis of a patient’s previously visited health entities. Simulation results show that the proposed technique outperforms standard-based healthcare blockchain techniques in terms of the number of appointments processed, consensus latency, and throughput. The proposed technique eliminates cross-shard communication by forming complete shards based on “the need to participate” nodes per patient.

scholarly journals A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Raphael Anaadumba ◽  
Qi Liu ◽  
Bockarie Daniel Marah ◽  
Francis Mawuli Nakoty ◽  
Xiaodong Liu ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Mobile Devices ◽  
Prediction Models ◽  
Renewable Energy Sources ◽  
Electrical Network ◽  
Effective Control ◽  
Energy Sources ◽  
Forecasting Model ◽  
Communication Overhead ◽  
Energy Forecasting

AbstractEnergy forecasting using Renewable energy sources (RESs) is gradually gaining weight in the research field due to the benefits it presents to the modern-day environment. Not only does energy forecasting using renewable energy sources help mitigate the greenhouse effect, it also helps to conserve energy for future use. Over the years, several methods for energy forecasting have been proposed, all of which were more concerned with the accuracy of the prediction models with little or no considerations to the operating environment. This research, however, proposes the uses of Deep Neural Network (DNN) for energy forecasting on mobile devices at the edge of the network. This ensures low latency and communication overhead for all energy forecasting operations since they are carried out at the network periphery. Nevertheless, the cloud would be used as a support for the mobile devices by providing permanent storage for the locally generated data and a platform for offloading resource-intensive computations that exceed the capabilities of the local mobile devices as well as security for them. Electrical network topology was proposed which allows seamless incorporation of multiple RESs into the distributed renewable energy source (D-RES) network. Moreover, a novel grid control algorithm that uses the forecasting model to administer a well-coordinated and effective control for renewable energy sources (RESs) in the electrical network is designed. The electrical network was simulated with two RESs and a DNN model was used to create a forecasting model for the simulated network. The model was trained using a dataset from a solar power generation company in Belgium (elis) and was experimented with a different number of layers to determine the optimum architecture for performing the forecasting operations. The performance of each architecture was evaluated using the mean square error (MSE) and the r-square.

scholarly journals Stable routing and energy-conserved data transmission over wireless sensor networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Suzan Shukry
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Data Transmission ◽  
Source Node ◽  
Wireless Sensor ◽  
Dominant Factor ◽  
Communication Overhead ◽  
Forwarding Node ◽  
Stable Path ◽  
Stable Routing

AbstractStable routing and energy conservation over a wireless sensor network (WSN) is a major issue in Internet of Things applications. The network lifetime can be increased when studying this issue with interest. Data transmission is a dominant factor in IoT networks for communication overhead and energy consumption. A proposed efficient node stable routing ($$ENSR$$ ENSR ) protocol is introduced to guarantee the stability of transmission data between the source and destination nodes, in a dynamic WSN conditions. $$ENSR$$ ENSR minimizes energy consumption and selects more stable nodes for packets forwarding. Stability becomes the most important factor that qualifies the node's centrality. A node’s stability is characterized by residual energy, link quality, and number of hops needed to reach the destination from the node. To calculate node's stability, an enhanced centrality concept, known as stable betweenness centrality ($$SBC$$ SBC ) is introduced. In $$ENSR$$ ENSR , at first, some nodes will be selected as the stable forwarding nodes, usually with maximum $$SBC$$ SBC between their neighbors within a limited communication radio range of a particular region. Furthermore, each stable forwarding node then broadcasts its identity, including $$SBC$$ SBC , to the source node separately. The source node can compute a stable path to forward packets to the corresponding stable forwarding node, based on a proper designed stable path routing metric ($$SPRM$$ SPRM ). Then, the stable forwarding node will behave as a new source node and start another stable path routing process until the packets are forwarded and reached to the destination node. In addition, the change of stable nodes over time balances and conserves node energy consumption, thereby mitigating “hot spots”. The proposed routing protocol is validated through simulation. The numerical results show that the proposed protocol outperforms the existing algorithms, global and local reliability-based routing ($$GLRR$$ GLRR ) and reliable energy-aware routing protocol $$(RER)$$ ( R E R ) , in terms of network efficiency and reliability.

scholarly journals A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Shanshan Yu ◽  
Jicheng Zhang ◽  
Ju Liu ◽  
Xiaoqing Zhang ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Denial Of Service ◽  
Attack Detection ◽  
Coarse Grained ◽  
Communication Overhead ◽  
Detection Scheme ◽  
Fine Grained ◽  
Ddos Attack ◽  
Network Status ◽  
Ddos Attack Detection

AbstractIn order to solve the problem of distributed denial of service (DDoS) attack detection in software-defined network, we proposed a cooperative DDoS attack detection scheme based on entropy and ensemble learning. This method sets up a coarse-grained preliminary detection module based on entropy in the edge switch to monitor the network status in real time and report to the controller if any abnormality is found. Simultaneously, a fine-grained precise attack detection module is designed in the controller, and a ensemble learning-based algorithm is utilized to further identify abnormal traffic accurately. In this framework, the idle computing capability of edge switches is fully utilized with the design idea of edge computing to offload part of the detection task from the control plane to the data plane innovatively. Simulation results of two common DDoS attack methods, ICMP and SYN, show that the system can effectively detect DDoS attacks and greatly reduce the southbound communication overhead and the burden of the controller as well as the detection delay of the attacks.

scholarly journals Transparent CoAP Services to IoT Endpoints through ICN Operator Networks

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1339 ◽  
Author(s):  
Hasan Islam ◽  
Dmitrij Lagutin ◽  
Antti Ylä-Jääski ◽  
Nikos Fotiou ◽  
Andrei Gurtov
Keyword(s):  
Storage Capacity ◽  
Communication Overhead ◽  
Full Potential ◽  
Core Network ◽  
Computation Complexity ◽  
State Management ◽  
Iot Devices ◽  
Novel Applications ◽  
And Storage ◽  
The Internet Of Things

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.

A STRATEGY FOR SCHEDULING PARTIALLY ORDERED PROGRAM GRAPHS ONTO MULTICOMPUTERS

1995 ◽  
Vol 05 (04) ◽  
pp. 575-586
Author(s):  
BEN LEE ◽  
ALI R. HURSON
Keyword(s):  
Parallel Processing ◽  
Message Passing ◽  
Massively Parallel ◽  
Communication Overhead ◽  
Simulation Studies ◽  
Global Approach ◽  
Partially Ordered ◽  
Massively Parallel Processing ◽  
Time Scheduling ◽  
Scheduling Heuristic

The issue of scalability is key to the success of massively parallel processing. Due to their distributed nature, message-passing multicomputers are appropriate for achieving scalar performance. However, the message-passing model lacks programmability due to difficulties encountered by the programmers to partition and schedule the computation over the processors and to establish efficient inter-processor communication in the user code. Therefore, this paper presents a compile-time scheduling heuristic, called BLS, that maps programs onto the processors of a message-passing multicomputer. In contrast to other methods proposed, BLS takes a more global approach in attempt to balance the tradeoff between exploiting parallelism and reducing communication overhead. To evaluate the effectiveness of BLS, simulation studies of scheduling SISAL programs are presented.

Coding Algorithms and Network Plan for Context-Aware Data Collection Based on Internet of Things in Large Marine Ships

2014 ◽  
Vol 701-702 ◽  
pp. 957-960
Author(s):  
Feng Xie
Keyword(s):  
Internet Of Things ◽  
Formal Analysis ◽  
Cluster Head ◽  
Communication Overhead ◽  
Context Aware ◽  
Sensing Data ◽  
Communication Efficiency ◽  
Data Volume ◽  
Using Data ◽  
Data Context

The equipment maintenance in large marine ships may rely on Internet of Things to provide monitoring of equipment status instantly. The data volume of sensing data is huge as the number of equipments is large. It is critical to decrease the communication overhead of uploading sensing data for efficiently and timely monitoring. In this paper, we propose several coding algorithms by using data context that is modeled by our normal forms on the base of our observations. The communication efficiency is improved, which is justified by formal analysis and rigorous proof. We also propose several network plan policies for further improvement of the communication efficiency by using data context and cluster head deployment.

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