List of Articles Energy

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  1 - Coverage Improving with Energy Efficient in Wireless Sensor Networks
  Amir Pakmehr Ali Ghaffari
  10.7508/jist.2017.17.008
  Wireless sensor networks (WSNs) are formed by numerous sensors nodes that are able to sense different environmental phenomena and to transfer the collected data to the sink. The coverage of a network is one of the main discussion and one of the parameters of service qua More

  Wireless sensor networks (WSNs) are formed by numerous sensors nodes that are able to sense different environmental phenomena and to transfer the collected data to the sink. The coverage of a network is one of the main discussion and one of the parameters of service quality in WSNs. In most of the applications, the sensor nodes are scattered in the environment randomly that causes the density of the nodes to be high in some regions and low in some other regions. In this case, some regions are not covered with any nodes of the network that are called covering holes. Moreover, creating some regions with high density causes extra overlapping and consequently the consumption of energy increases in the network and life of the network decreases. The proposed approach causes an increase in life of the network and an increase in it through careful selection of the most appropriate approach as cluster head node and form clusters with a maximum length of two steps and selecting some nodes as redundancy nodes in order to cover the created holes in the network. The proposed scheme is simulated using MATLAB software. The function of the suggested approach will be compared with Learning Automata based Energy Efficient Coverage protocol (LAEEC) approach either. Simulation results shows that the function of the suggested approach is better than LAEEC considering the parameters such as average of the active nodes, average remaining energy in nodes, percent of network coverage and number of control packets. Manuscript profile
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  2 - Clustering for Reduction of Energy Consumption in Wireless Sensor Networks by AHP Method
  Mohammad Reza  Taghva Robab  Hamlbarani Haghi Aziz Hanifi Kamran  feizi
  10.7508/jist.2018.21.002
  Due to the type of applications, wireless sensor nodes must always be energy efficient and small. Hence, some studies have been done in order to the reduction in energy consumption. Data collection in wireless sensor networks is one of the most important operations of t More

  Due to the type of applications, wireless sensor nodes must always be energy efficient and small. Hence, some studies have been done in order to the reduction in energy consumption. Data collection in wireless sensor networks is one of the most important operations of these networks. Due to the energy limitation of nodes, energy efficiency is considered as a key objective in the design of sensor networks. In this paper, we present a method in which, in the first phase, nodes obtain their position by using the position of the base station and two other two nodes informed geographic position and are out of covered environment. In the second phase, the optimal location of the base station is determined. In the third phase, we determine the cluster heads based on the criteria such as the remaining energy, the distance (the distance from the cluster head and the distance from the base station), the number of neighbors (the one-step neighbors and the two-step neighbors) and the centrality. Using the multi-as criteria to select optimally cluster heads by decision making method. We implement the proposed method in the NS2 environment and evaluate its effect and compare it with the NEECP E-LEACH protocols. Simulation results show that by reducing energy consumption, the proposed method enhances the network life time expectancy. In addition it improves average packet delivery and the average delay. Manuscript profile
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  3 - Embedding Virtual Machines in Cloud Computing Based on Big Bang–Big Crunch Algorithm
  Ali Ghaffari Afshin Mahdavi
  10.7508/jist.2019.04.006
  Cloud computing is becoming an important and adoptable technology for many of the organization which requires a large amount of physical tools. In this technology, services are provided and presented according to users’ requests. Due to the presence of a large number of More

  Cloud computing is becoming an important and adoptable technology for many of the organization which requires a large amount of physical tools. In this technology, services are provided and presented according to users’ requests. Due to the presence of a large number of data centers in cloud computing, power consumption has recently become an important issue. However, data centers hosting Cloud applications consume huge amounts of electrical energy and contributing to high operational costs to the environment. Therefore, we need Green Cloud computing solutions that can not only minimize operational costs but also reduce the environmental impact. Live migration of virtual machines and their scheduling and embedding lead to enhanced efficiency of dynamic resources. The guarantee of service quality and service reliability is an indispensable and irrevocable requirement with respect to service level agreement. Hence, providing a method for reducing costs of power consumption, data transmission, bandwidth and, also, for enhancing quality of service (QoS) in cloud computing is critical. In this paper, a Big Bang–Big Crunch (BB-BC) based algorithm for embedding virtual machines in cloud computing was proposed. We have validated our approach by conducting a performance evaluation study using the CloudSim toolkit. Simulation results indicate that the proposed method not only enhances service quality, thanks to the reduction of agreement violation, but also reduces power consumption. Manuscript profile
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  4 - Reallocation of Virtual Machines to Cloud Data Centers to Reduce Service Level Agreement Violation and Energy Consumption Using the FMT Method
  Hojjat Farrahi Farimani Davoud  Bahrepour Seyed Reza Kamel Tabbakh reza Ghaemi
  10.7508/jist.2019.04.007
  Due to the increased use of cloud computing services, cloud data centers are in search of solutions in order to better provide the services demanded by their users. Virtual machine consolidation is an appropriate solution to the trade-off between power consumption and s More

  Due to the increased use of cloud computing services, cloud data centers are in search of solutions in order to better provide the services demanded by their users. Virtual machine consolidation is an appropriate solution to the trade-off between power consumption and service level agreement violation. The present study aimed to identify low, medium, and high load identification techniques, as well as the energy consumption and SLAv to minimize. In addition to the reduced costs of cloud providers, these techniques enhance the quality of the services demanded by the users. To this end, reallocation of resources to physical hosts was performed at the medium load level using a centralized method to classify the physical hosts. In addition, quartile was applied in each medium to reduce the energy consumption parameters and violation level. The three introduced SMT - NMT and FMT methods for reallocation of resources were tested and the best results were compared with previous methods.The proposed method was evaluated using the Cloudsim software with real Planet Lab data and five times run, the simulation results confirmed the efficiency of the proposed algorithm, which tradeoff between decreased the energy consumption and service level of agreement violation (SLAv) properly. Manuscript profile
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  5 - Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications
  R Rathna L Mary Gladence J Sybi Cynthia V Maria Anu
  10.52547/jist.9.35.207
  20.1001.1.23221437.2021.9.35.6.5
  Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless d More

  Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless data communication. Nowadays the WSN has become ubiquitous. WSN is used in combination with Internet of Things and in many Big Data applications, it is used in the lower layer for data collection. It is deployed in combination with several high end networks. All the higher layer networks and application layer services depend on the low level WSN in the deployment site. So to achieve energy efficiency in the overall network some simplification strategies have to be carried out not only in the Medium Access Control (MAC) layer but also in the network and transport layers. An energy efficient algorithm for scheduling and clustering is proposed and described in detail. The proposed methodology clusters the nodes using a traditional yet simplified approach of hierarchically sorting the sensor nodes. Few important works on cross layer protocols for WSNs are reviewed and an attempt to modify their pattern has also been presented in this paper with results. Comparison with few prominent protocols in this domain has also been made. As a result of the comparison one would get a basic idea of using which type of scheduling algorithm for which type of monitoring applications. Manuscript profile
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  6 - Optimal Clustering-based Routing Protocol Using Self-Adaptive Multi-Objective TLBO For Wireless Sensor Network
  Ali Sedighimanesh Hessam  Zandhessami Mahmood  Alborzi Mohammadsadegh  Khayyatian
  10.52547/jist.9.34.113
  20.1001.1.23221437.2021.9.34.1.8
  Wireless sensor networks consist of many fixed or mobile, non-rechargeable, low-cost, and low-consumption nodes. Energy consumption is one of the most important challenges due to the non-rechargeability or high cost of sensor nodes. Hence, it is of great importance to a More

  Wireless sensor networks consist of many fixed or mobile, non-rechargeable, low-cost, and low-consumption nodes. Energy consumption is one of the most important challenges due to the non-rechargeability or high cost of sensor nodes. Hence, it is of great importance to apply some methods to reduce the energy consumption of sensors. The use of clustering-based routing is a method that reduces the energy consumption of sensors. In the present article, the Self-Adaptive Multi-objective TLBO (SAMTLBO) algorithm is applied to select the optimal cluster headers. After this process, the sensors become the closest components to cluster headers and send the data to their cluster headers. Cluster headers receive, aggregate, and send data to the sink in multiple steps using the TLBO-TS hybrid algorithm that reduces the energy consumption of the cluster heads when sending data to the sink and, ultimately, an increase in the wireless sensor network’s lifetime. The simulation results indicate that our proposed protocol (OCRP) show better performance by 35%, 17%, and 12% compared to ALSPR, CRPD, and COARP algorithms, respectively. Conclusion: Due to the limited energy of sensors, the use of meta-heuristic methods in clustering and routing improves network performance and increases the wireless sensor network's lifetime. Manuscript profile
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  7 - Dynamic Tree- Based Routing: Applied in Wireless Sensor Network and IOT
  Mehdi Khazaei
  10.52547/jist.22504.10.39.191
  20.1001.1.23221437.2022.10.39.4.8
  The Internet of Things (IOT) has advanced in parallel with the wireless sensor network (WSN) and the WSN is an IOT empowerment. The IOT, through the internet provides the connection between the defined objects in apprehending and supervising the environment. In some app More

  The Internet of Things (IOT) has advanced in parallel with the wireless sensor network (WSN) and the WSN is an IOT empowerment. The IOT, through the internet provides the connection between the defined objects in apprehending and supervising the environment. In some applications, the IOT is converted into WSN with the same descriptions and limitations. Working with WSN is limited to energy, memory and computational ability of the sensor nodes. This makes the energy consumption to be wise if protection of network reliability is sought. The newly developed and effective hierarchical and clustering techniques are to overcome these limitations. The method proposed in this article, regarding energy consumption reduction is tree-based hierarchical technique, used clustering based on dynamic structure. In this method, the location-based and time-based properties of the sensor nodes are applied leading to provision of a greedy method as to form the subtree leaves. The rest of the tree structure up to the root, would be formed by applying the centrality concept in the network theory by the base station. The simulation reveals that the scalability and fairness parameter in energy consumption compare to the similar method has improved, thus, prolonged network lifetime and reliability. Manuscript profile
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  8 - Joint Cooperative Spectrum Sensing and Resource Allocation in Dynamic Wireless Energy Harvesting Enabled Cognitive Sensor Networks
  maryam Najimi
  10.61186/jist.33968.11.44.320
  Due to the limitations of the natural frequency spectrum, dynamic frequency allocation is required for wireless networks. Spectrum sensing of a radio channel is a technique to identify the spectrum holes. In this paper, we investigate a dynamic cognitive sensor networ More

  Due to the limitations of the natural frequency spectrum, dynamic frequency allocation is required for wireless networks. Spectrum sensing of a radio channel is a technique to identify the spectrum holes. In this paper, we investigate a dynamic cognitive sensor network, in which the cognitive sensor transmitter has the capability of the energy harvesting. In the first slot, the cognitive sensor transmitter participates in spectrum sensing and in the existence of the primary user, it harvests the energy from the primary signal, otherwise the sensor transmitter sends its signal to the corresponding receiver while in the second slot, using the decode-and-forward (DF) protocol, a part of the bandwidth is used to forward the signal of the primary user and the remained bandwidth is used for transmission of the cognitive sensor. Therefore, our purposed algorithm is to maximize the cognitive network transmission rate by selection of the suitable cognitive sensor transmitters subject to the rate of the primary transmission and energy consumption of the cognitive sensors according to the mobility model of the cognitive sensors in the dynamic network. Simulation results illustrate the effectiveness of the proposed algorithm in performance improvement of the network as well as reducing the energy consumption. Manuscript profile