Energy consumption

List of Articles Energy consumption

Open Access Article
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1 - Next Hop Selection to Configuring the Route in LEAP Protocol Based on Fuzzy Logic in WSNs
Vahid Sattari-Naeini F. Movahhedi
20.1001.1.16823745.1396.15.4.13.8

Since in wireless sensor networks, selection of next hop is critical in attack avoidance and lowering the power consumption, a method based on fuzzy logic is proposed in this paper considering status and report transmission of the nodes. In this method, the next hop is More

Since in wireless sensor networks, selection of next hop is critical in attack avoidance and lowering the power consumption, a method based on fuzzy logic is proposed in this paper considering status and report transmission of the nodes. In this method, the next hop is selected considering four factors, based on fuzzy logic system. These factors, indicating four optimized parameters; i.e., degree of node proximity to the shortest path, degree of node proximity to the sink, residual energy ratio of each node, and the number of false filtered messages. This method leads to an increase in energy level as well as maintaining security level in comparison with LEAP protocol. Meanwhile, it is possible to identify safe paths. Comparing with other related methods, it is shown that this method leads to significant reduction in energy consumption level and consequently the life-time of the network is increased. Meanwhile with selecting the appropriate next hop, packet drops are reduced as well. Manuscript profile
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2 - A Method to Get WSN Nodes Data by Web Clients through IoT Gateway Based on CoAP Protocol
M. R. Nikseresht H. Haj Seyyed Javadi Mahdi Mollamotalebi
20.1001.1.16823745.1397.16.4.9.1

The advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of More

The advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of the challenges of the Internet world of things. 6LoWPAN and CoAP standards for using web protocols in low-loss and low-power sensor networks (LLNs) are presented. The 6LoWPAN / CoAP protocol stack allows access to the sensor network through web protocols. This will facilitate the development of applications on the sensor network and access to them by the Internet. Each layer stack of the 6LoWPAN / CoAP protocol imposes overhead on interchange messages, and data overload in multichannel networks exacerbates energy consumption. In this paper, a method for reducing the overhead imposed on small and medium packets in multi-step networks based on 6LoWPAN / CoAP is presented using the scheduling and aggregation of CoAP packets on sensor nodes. In order to achieve the research objectives, measures such as the classification of CoAP requests / responses in terms of network priority (maximum allowed delay detection), scheduling and aggregation of incoming messages on sensor nodes (based on the maximum allowed delay of each), and opening messages aggregated in the destination , It has been done. The evaluation results of the proposed method indicate a reduction of energy consumption and network traffic for applications such as monitoring, in multi-step networks based on the 6LoWPAN/ CoAP protocol stack. Manuscript profile
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3 - Priority-Based Task Scheduling Using Fuzzy System in Mobile Edge Computing
Entesar Hosseini Mohsen Nickray SH. GH.
20.1001.1.16823745.1401.20.4.1.1

Mobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are i More

Mobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are important issue in MEC. In this paper, we use a standard three-level system model of mobile devices, edge and cloud, and propose two offloading and scheduling algorithms. A decision-making algorithm for offloading tasks is based on the greedy Knapsack offloading algorithm (GKOA) on the mobile device side, which selects tasks with high power consumption for offloading and it saves energy consumption of the device. On the MEC side, we also present a dynamic scheduling algorithm with fuzzy-based priority task scheduling (FPTS) for prioritizing and scheduling tasks based on two criteria. Numerical results show that our proposed work compared to other methods and reduces the waiting time, latency and system overhead. Also, provides the balance of the system with the least number of resources. And the proposed system reduces battery consumption in the smart device by up to 90%. The results show that more than 92% of tasks are executed successfully in the edge environment. Manuscript profile
Open Access Article
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4 - Assessment of Demand Side Resources Potential in Presence of Cooling and Heating Equipment Using Data Mining Method Based Upon K-Means Clustering Algorithm
fatemeh sheibani M. Mollahassani-pour هنگامه کشاورز
20.1001.1.16823745.1401.20.3.8.6

Under the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are ide More

Under the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are identified using k-means clustering algorithm as a data mining technique. In this regard, the energy consumption dataset are categorized in different clusters by k-means algorithm based upon variations of energy price and ambient temperature during peak hours of hot (Spring and Summer) and cold (Autumn and Winter) periods. Then, the clusters with the possibility of cooling and heating equipment’s commitment are selected. After that, the confidence interval diagram of energy consumption in elected clusters is provided based upon energy price variations. The nominal potential of DRRs, i.e. flexible load, will be obtained regarding the maximum and minimum differences between the average of energy consumption in upper and middle thresholds of the confidence interval diagram. The energy consumption, ambient temperature and energy price related to BOSTON electricity network over a six-year horizon time is utilized to evaluate the proposed model. Manuscript profile
Open Access Article
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5 - Provide an Energy-aware Markov Based Model for Dynamic Placement of Virtual Machines in Cloud Data Centers
mehdi rajabzadeh Abolfazl Toroghi Haghighat Amir Masoud Rahmani
20.1001.1.16823745.1401.20.1.4.8

The use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new mode More

The use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new model is presented that seeks to achieve the desired results by improving the algorithms and providing appropriate methods. Periodic monitoring of resource status, proper analysis of the data obtained, and prediction of the critical state of the servers using the proposed Markov model have reduced the number of unnecessary migrations as much as possible. The combination of genetic algorithm and simulated annealing in the replacement section along with the definition of the adsorbent Markov chain has resulted in better and faster performance of the proposed algorithm. Simulations performed in different scenarios in CloudSim show that compared to the best algorithm compared, at low, medium and high load, energy consumption has decreased significantly. Violations of service level agreements also fell by an average of 17 percent. Manuscript profile

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List of Articles Energy consumption