scholarly journals Efficient Interference Estimation with Accuracy Control for Data-Driven Resource Allocation in Cloud-RAN

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3000 ◽  
Author(s):  
Yanchao Zhao ◽  
Jie Wu ◽  
Wenzhong Li ◽  
Sanglu Lu
Keyword(s):  
Resource Allocation ◽  
Network Architecture ◽  
Measurement Data ◽  
Network Size ◽  
Base Station ◽  
Edge Computing ◽  
Sensor Nodes ◽  
Data Driven ◽  
Accuracy Control ◽  
Computing Paradigm

The emerging edge computing paradigm has given rise to a new promising mobile network architecture, which can address a number of challenges that the operators are facing while trying to support growing end user’s needs by shifting the computation from the base station to the edge cloud computing facilities. With such powerfully computational power, traditional unpractical resource allocation algorithms could be feasible. However, even with near optimal algorithms, the allocation result could still be far from optimal due to the inaccurate modeling of interference among sensor nodes. Such a dilemma calls for a measurement data-driven resource allocation to improve the total capacity. Meanwhile, the measurement process of inter-nodes’ interference could be tedious, time-consuming and have low accuracy, which further compromise the benefits brought by the edge computing paradigm. To this end, we propose a measurement-based estimation solution to obtain the interference efficiently and intelligently by dynamically controlling the measurement and estimation through an accuracy-driven model. Basically, the measurement cost is reduced through the link similarity model and the channel derivation model. Compared to the exhausting measurement method, it can significantly reduce the time cost to the linear order of the network size with guaranteed accuracy through measurement scheduling and the accuracy control process, which could also balance the tradeoff between accuracy and measurement overhead. Extensive experiments based on real data traces are conducted to show the efficiency of the proposed solutions.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2016 ◽  
pp. 79-114
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2020 ◽  
pp. 372-399
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

scholarly journals Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Asis Kumar Tripathy ◽  
Suchismita Chinara
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Architecture ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness

Wireless sensor network swears an exceptional fine-grained interface between the virtual and physical worlds. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. Each clustering algorithm is composed of three phases cluster head (CH) selection, the setup phase, and steady state phase. The hot point in these algorithms is the cluster head selection. The focus, however, has been given to the residual energy-based clustering protocols which might differ depending on the application and network architecture. In this paper, a survey of the state-of-the-art clustering techniques in WSNs has been compared to find the merits and demerits among themselves. It has been assumed that the sensor nodes are randomly distributed and are not mobile, the coordinates of the base station (BS) and the dimensions of the sensor field are known.

scholarly journals A Novel Energy-Efficient, Static Scenario-Oriented Routing Method of Wireless Sensor Network Based on Edge Computing

2022 ◽  
Vol 2022 ◽  
pp. 1-25
Author(s):  
Gang Liu ◽  
Zhaobin Liu ◽  
Victor S. Sheng ◽  
Liang Zhang ◽  
Yuanfeng Yang
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Base Station ◽  
Edge Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Area Network ◽  
Routing Method

In wireless sensor network (WSN), the energy of sensor nodes is limited. Designing efficient routing method for reducing energy consumption and extending the WSN’s lifetime is important. This paper proposes a novel energy-efficient, static scenario-oriented routing method of WSN based on edge computing named the NEER, in which WSN is divided into several areas according to the coverage of gateway (or base station), and each of the areas is regarded as an edge area network (EAN). Each edge area network is abstracted into a weighted undirected graph model combined with the residual energy of the sensor nodes. The base station (or a gateway) calculates the optimal energy consumption path for all sensor nodes within its coverage, and the nodes then perform data transmission through their suggested optimal paths. The proposed method is verified by the simulations, and the results show that the proposed method may consume about 37% less energy compared with the conventional WSN routing protocol and can also effectively extend the lifetime of WSN.

scholarly journals An Efficient Resource Allocation Strategy for Edge-Computing Based Environmental Monitoring System

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6125
Author(s):  
Juan Fang ◽  
Juntao Hu ◽  
Jianhua Wei ◽  
Tong Liu ◽  
Bo Wang
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Environmental Monitoring ◽  
Monitoring System ◽  
Edge Computing ◽  
Resource Allocation Algorithm ◽  
Computing Paradigm ◽  
Environmental Monitoring System ◽  
Monitoring Applications ◽  
Efficient Resource

The cloud computing and microsensor technology has greatly changed environmental monitoring, but it is difficult for cloud-computing based monitoring system to meet the computation demand of smaller monitoring granularity and increasing monitoring applications. As a novel computing paradigm, edge computing deals with this problem by deploying resource on edge network. However, the particularity of environmental monitoring applications is ignored by most previous studies. In this paper, we proposed a resource allocation algorithm and a task scheduling strategy to reduce the average completion latency of environmental monitoring application, when considering the characteristic of environmental monitoring system and dependency among task. Simulations are conducted, and the results show that compared with the traditional algorithms. With considering the emergency task, the proposed methods decrease the average completion latency by 21.6% in the best scenario.

scholarly journals Developing Energy Aware Distributed Aggregation Tree Technique for Wireless Sensor Networks

2017 ◽  
Vol 43 (2) ◽  
pp. 1-8
Author(s):  
Intisar Al-Mejibli
Keyword(s):  
Mobile Networks ◽  
Network Architecture ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Power Resources ◽  
Aggregation Tree ◽  
Aggregation Technique ◽  
Parent Node

Wireless sensor network WSN consists of small sensor nodes with limited resources, which are sensing, gathering and transmitting data to base station. Sensors of various types are deployed ubiquitously and widely in varied environments for instance, wildlife reserves, battlefields, mobile networks and office building. Sensor nodes are having restricted and non replenishable power resources and this is regarded as one of the main of their critical limits. All applied techniques and protocols on sensor nodes must take into consideration their power limitation. Data aggregation techniques are used by sensor nodes in order to minimize the power consumption by organizing the communication among sensor nodes and eliminating the redundant of sensed data. This paper proposed lightweight modification on data aggregation technique named Energy Aware Distributed Aggregation Tree EADAT. The main principle of this development is using the available information in sensor nodes to pass the role of parent node among sensor nodes in each cluster. The process of passing parent node role is based on nominating the sensor nodes which have higher power on regular bases. A model based on tree network architecture is designed for validation purpose and is used with NS2 simulator to test the proposed development. EADAT and EADAT with proposed development are applied on the designed model and the results were promising

scholarly journals A Collaborative Cache Strategy in Satellite-Ground Integrated Network Based on Multiaccess Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Yang ◽  
Xiangguang Kong ◽  
Yaowen Qi ◽  
Chengsheng Pan
Keyword(s):  
Network Architecture ◽  
Storage Capacity ◽  
Base Station ◽  
Edge Computing ◽  
Average Delay ◽  
Integrated Network ◽  
Delivery Delay ◽  
Collaborative Caching ◽  
Hit Rate ◽  
Cache Scheme

Multiaccess edge computing (MEC) provides users with a network environment and computing storage capacity at the edge of the network, ensuring a deterministic service with low delivery delay. This paper introduces a new satellite-ground integrated collaborative caching network architecture based on MEC and studies the caching strategy. On the ground side, the edge nodes (ENs) are deployed to the user side to form a hierarchical collaborative cache mode centered on the base station. On the satellite side, we utilize intelligent satellite ENs to precache and multicast the highly popular contents, reducing the initial content delivery delay. Under the constraints of the user demand and storage capacity, we study the deployment and cache scheme of ENs and establish the delivery delay minimization problem. To solve the problem, we propose a content update decision parameter for content cache update and transform the problem into improving the hit rate of ENs. Simulation results show that the proposed MEC network architecture and content caching scheme can increase the caching system hit rate to 64% and reduce the average delay by 32.96% at most.

scholarly journals Edge Computing through Virtual Force for Detecting Trustworthy Values

2020 ◽  
Vol 2 (2) ◽  
pp. 84-91
Author(s):  
Dr. Dhaya R. ◽  
Dr. Kanthavel R.
Keyword(s):  
Sensor Networks ◽  
Edge Computing ◽  
Sensor Nodes ◽  
Trust Value ◽  
Computing Paradigm ◽  
Virtual Force ◽  
Resource Requirements ◽  
Noticeable Improvement ◽  
Different Dimensions ◽  
Best Fit

As the advancement of IoT (Internet of Things) and other emerging mobile application continues, it is an accepted fact that Edge Computing paradigm is considered to be the best fit in terms of fulfilling the resource requirements. Moreover, it is a fact that the data collected by the sensor networks serves as the base for the IoT applications as well as the systems. However, due to advancement in cybercrimes, there is a possibility that the data collected through the sensor networks are vulnerable to attacks which may result in serious consequences. The proposed work focuses on a new model which is used to gather trustworthy data using edge computing in IoT. In order to get the accurately quantified trust values, the sensor nodes are analyzed and found from different dimensions. Moreover, with the help of trust value obtained, it is possible to find the best mobility path which carries the highest value of trust. This data is gathered from the sensors with the help of mobile edge data collector. This analysis shows that for a trustworthy data collection model of IoT, there is noticeable improvement in terms of energy conservation and system security, thereby improving the performance of the system.

scholarly journals Design of a Wireless and Energy Autonomous Sensor Network for Condition Monitoring of Tram Drive Components

Designs ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 50 ◽  
Author(s):  
Maik Wolf ◽  
Silvio Hund ◽  
Mathias Rudolph ◽  
Olfa Kanoun
Keyword(s):  
Sensor Network ◽  
Condition Monitoring ◽  
Electromagnetic Compatibility ◽  
Sampling Rate ◽  
Measurement Data ◽  
Base Station ◽  
Sensor Nodes ◽  
Autonomous Sensor ◽  
Security Costs ◽  
The Individual

Although condition monitoring is very important for a reliable operation of tram powertrain components, conventional wired sensor systems do not manage to find wide acceptance because of installation and security costs. To address those issues, we propose a novel condition monitoring system based on a wireless and energy self-sufficient sensor network, where the individual sensor nodes harvest energy from vibrations, occurring while the tram is in motion. First, we performed an experimental investigation to identify the most important boundary conditions for the system design. Second, we designed individual sensor nodes using parameters derived from the previous investigation. Finally, the sensor network was deployed and tested on the tram gearboxes. The obtained measurement data were recorded at a sufficient sampling rate of 4.56 kHz and were successfully transferred from the tram gearbox to the network base station within a radius of 10 m inside the tram despite factors such as reflections, fading and electromagnetic compatibility. A piezoelectric vibration harvester is the power supply for the sensor nodes and it delivers up to 21.22 mW for relevant vibration frequency range between 10 Hz and 30 Hz, thus enabling deployment of autonomous sensor nodes.

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