scholarly journals Energy and performance costs evaluation for BLE mesh links

2018 ◽  
Author(s):  
Henrique Carvalho Silva ◽  
Cíntia Borges Margi
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Mesh Networks ◽  
Lower Boundary ◽  
Low Energy ◽  
Trade Offs ◽  
Main Challenge ◽  
And Performance ◽  
Large Scale Networks ◽  
The Internet Of Things

Bluetooth Low Energy (BLE for short) is among the favorites to become a de facto standard in the context of the Internet of Things (IoT). However, its main challenge is the lack of standards for efficient mesh networking. Furthermore, the literature lacks works analyzing energy consumption trade-offs for BLE mesh networks. We address this issue by experimentally evaluating three minimal topologies for linking separate BLE star networks. We aim to determine a lower boundary in terms of energy and performance costs using the metrics of energy consumption, delivery rate, and goodput. We perform our experiments using a testbed comprised of TI CC1350 nodes running Contiki OS. Our results enable us to estimate similar costs for large scale networks.

scholarly journals A Hybrid Method for Mobile Agent Moving Trajectory Scheduling using ACO and PSO in WSNs

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 575 ◽  
Author(s):  
Yu Gao ◽  
Jin Wang ◽  
Wenbing Wu ◽  
Arun Sangaiah ◽  
Se-Jung Lim
Keyword(s):  
Energy Consumption ◽  
Mobile Agent ◽  
Hybrid Method ◽  
Large Scale ◽  
Data Gathering ◽  
Sensor Field ◽  
Efficient Data ◽  
Anchor Nodes ◽  
Large Scale Networks ◽  
Moving Path

Wireless Sensor Networks (WSNs) are usually troubled with constrained energy and complicated network topology which can be mitigated by introducing a mobile agent node. Due to the numerous nodes present especially in large scale networks, it is time-consuming for the collector to traverse all nodes, and significant latency exists within the network. Therefore, the moving path of the collector should be well scheduled to achieve a shorter length for efficient data gathering. Much attention has been paid to mobile agent moving trajectory panning, but the result has limitations in terms of energy consumption and network latency. In this paper, we adopt a hybrid method called HM-ACOPSO which combines ant colony optimization (ACO) and particle swarm optimization (PSO) to schedule an efficient moving path for the mobile agent. In HM-ACOPSO, the sensor field is divided into clusters, and the mobile agent traverses the cluster heads (CHs) in a sequence ordered by ACO. The anchor node of each CHs is selected in the range of communication by the mobile agent using PSO based on the traverse sequence. The communication range adjusts dynamically, and the anchor nodes merge in a duplicated covering area for further performance improvement. Numerous simulation results prove that the presented method outperforms some similar works in terms of energy consumption and data gathering efficiency.

Service Level Agreement Conformance in Virtual Machine Migration with an Improved Energy and Performance Management Method

2020 ◽  
Vol 17 (9) ◽  
pp. 3904-3906
Author(s):  
Susmita J. A. Nair ◽  
T. R. Gopalakrishnan Nair
Keyword(s):  
Energy Consumption ◽  
Performance Management ◽  
Large Scale ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Performance Degradation ◽  
Virtual Machine Migration ◽  
And Performance

Increasing demand of computing resources and the popularity of cloud computing have led the organizations to establish of large-scale data centers. To handle varying workloads, allocating resources to Virtual Machines, placing the VMs in the most suitable physical machine at data centers without violating the Service Level Agreement remains a big challenge for the cloud providers. The energy consumption and performance degradation are the prime focus for the data centers in providing services by strictly following the SLA. In this paper we are suggesting a model for minimizing the energy consumption and performance degradation without violating SLA. The experiments conducted have shown a reduction in SLA violation by nearly 10%.

scholarly journals The Bluetooth Mesh Standard: An Overview and Experimental Evaluation

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2409 ◽  
Author(s):  
Mathias Baert ◽  
Jen Rossey ◽  
Adnan Shahid ◽  
Jeroen Hoebeke
Keyword(s):  
Experimental Evaluation ◽  
Statistical Approach ◽  
Mesh Networks ◽  
New Technology ◽  
Low Energy ◽  
Future Research ◽  
Path Diversity ◽  
The Internet Of Things ◽  
Roll Out ◽  
Open Issues

Mesh networks enable a many-to-many relation between nodes, which means that each node in the network can communicate with every other node using multi-hop communication and path diversity. As it enables the fast roll-out of sensor and actuator networks, it is an important aspect within the Internet of Things (IoT). Utilizing Bluetooth Low Energy (BLE) as an underlying technology to implement such mesh networks has gained a lot of interest in recent years. The result was a variety of BLE meshing solutions that were not interoperable because of the lack of a common standard. This has changed recently with the advent of the Bluetooth Mesh standard. However, a detailed overview of how this standard operates, performs and how it tackles other issues concerning BLE mesh networking is missing. Therefore, this paper investigates this new technology thoroughly and evaluates its performance by means of three approaches, namely an experimental evaluation, a statistical approach and a graph-based simulation model, which can be used as the basis for future research. Apart from showing that consistent results are achieved by means of all three approaches, we also identify possible drawbacks and open issues that need to be dealt with.

scholarly journals Efficient Communication Scheme for Bluetooth Low Energy in Large Scale Applications

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6371
Author(s):  
Maciej Nikodem ◽  
Mariusz Slabicki ◽  
Marek Bawiec
Keyword(s):  
Energy Efficiency ◽  
Large Scale ◽  
Real Life ◽  
Low Energy ◽  
Typical Application ◽  
Bluetooth Low Energy ◽  
Iot Applications ◽  
Communication Scheme ◽  
Improve Device ◽  
The Internet Of Things

The use of Bluetooth Low Energy (BLE) in the Internet-of-Things (IoT) applications has become widespread and popular. This has resulted in the increased number of deployed BLE devices. To ensure energy efficiency, applications use connectionless communication where nodes broadcast information using advertisement messages. As the BLE devices compete for access to spectrum, collisions are inevitable and methods that improve device coexistence are required. This paper proposes a connectionless communication scheme for BLE that improves communication efficiency in IoT applications where a large number of BLE nodes operate in the same area and communicate simultaneously to a central server. The proposed scheme is based on an active scanning mode and is compared with a typical application where passive scanning mode is used. The evaluation is based on numerical simulations and real-life evaluation of a network containing 150 devices. The presented scheme significantly reduces the number of messages transmitted by each node and decreases packet loss ratio. It also improves the energy efficiency and preserves the battery of BLE nodes as they transmit fewer radio messages and effectively spent less time actively communicating. The proposed connectionless BLE communication scheme can be applied to a large variety of IoT applications improving their performance and coexistence with other devices operating in the 2.4 GHz band. Additionally, the implementation complexity and costs of the proposed communication scheme are negligible.

SLA and Performance Efficient Heuristics for Virtual Machines Placement in Cloud Data Centers

2017 ◽  
Vol 9 (3) ◽  
pp. 17-33 ◽  
Author(s):  
Oshin Sharma ◽  
Hemraj Saini
Keyword(s):  
Energy Consumption ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Consolidation Process ◽  
Cloud Data ◽  
Trade Offs ◽  
And Performance ◽  
High Level

Cloud computing has revolutionized the working models of IT industry and increasing the demand of cloud resources which further leads to increase in energy consumption of data centers. Virtual machines (VMs) are consolidated dynamically to reduce the number of host machines inside data centers by satisfying the customer's requirements and quality of services (QoS). Moreover, for using the services of cloud environment every cloud user has a service level agreement (SLA) that deals with energy and performance trade-offs. As, the excess of consolidation and migration may degrade the performance of system, therefore, this paper focuses the overall performance of the system instead of energy consumption during the consolidation process to maintain a trust level between cloud's users and providers. In addition, the paper proposed three different heuristics for virtual machine (VM) placement based on current and previous usage of resources. The proposed heuristics ensure a high level of service level agreements (SLA) and better performance of ESM metric in comparison to previous research.

GAA-Based Decision Approach for Hospital Building Renovation Management

2011 ◽  
Vol 403-408 ◽  
pp. 5265-5272
Author(s):  
Yi Kai Juan ◽  
Yu Ching Cheng ◽  
Yeng Horng Perng ◽  
Guang Bin Wang
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Energy Use ◽  
Search Algorithm ◽  
Hybrid Approach ◽  
Optimal Solution ◽  
Developed Countries ◽  
Sustainable Technologies ◽  
Trade Offs ◽  
Hospital Building

More and more attention has been paid to hospital facilities since modern pandemics have emerged such as SARS and avian influenza. Energy consumption by buildings accounts for 20-40% of energy use in developed countries, so many global organizations make efforts to develop sustainable technologies or materials to create a sustainable environment, and to reduce energy consumption when renovating building. Therefore, maintaining high standards of hygiene and reducing energy consumption has become the major task for hospital buildings. This study develops an integrated decision support system to assess existing hospital building conditions and to recommend an optimal scheme of sustainable renovation actions, considering trade-offs between renovation cost, improved building quality, and environmental impacts. A hybrid approach that combines the A* graph search algorithm with genetic algorithms (GA) is used to analyze all possible renovation actions and their trade-offs to develop the optimal solution. A simulated hospital renovation project is established to demonstrate the system. The result reveals the system can solve complicated and large-scale combinational, discrete and determinate problems such as the hospital renovation project, and also improve traditional building condition assessment to be more effective and efficient.

scholarly journals An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Min Tian ◽  
Jie Zhou ◽  
Xin Lv
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Large Scale ◽  
Low Energy ◽  
Wireless Sensor ◽  
Mixed Integer ◽  
Clustering Problem ◽  
Systems Simulation

Large-scale wireless sensor networks consist of a large number of tiny sensors that have sensing, computation, wireless communication, and free-infrastructure abilities. The low-energy clustering scheme is usually designed for large-scale wireless sensor networks to improve the communication energy efficiency. However, the low-energy clustering problem can be formulated as a nonlinear mixed integer combinatorial optimization problem. In this paper, we propose a low-energy clustering approach based on improved niche chaotic genetic algorithm (INCGA) for minimizing the communication energy consumption. We formulate our objective function to minimize the communication energy consumption under multiple constraints. Although suboptimal for LSWSN systems, simulation results show that the proposed INCGA algorithm allows to reduce the communication energy consumption with lower complexity compared to the QEA (quantum evolutionary algorithm) and PSO (particle swarm optimization) approaches.

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