Real-Time Adaptive Energy-Scheduling Algorithm for Virtualized Cloud Computing
D B Srinivas1, H K Krishnappa2, Rajan M A3, Sujay N. Hegde4 , 1,4Nitte Meenakshi Institute of Technology,India , 2R V College of Engineering, India , 3TCS Research and Innovation,India
Cloud computing becomes an ideal computing paradigm for scientific and commercial applications. The increased availability of the cloud models and allied developing models creates easier computing cloud environment. Energy consumption and effective energy management are the two important challenges in virtualized computing platforms. Energy consumption can be minimized by allocating computationally intensive tasks to a resource at a suitable frequency. An optimal Dynamic Voltage and Frequency Scaling (DVFS) based strategy of task allocation can minimize the overall consumption of energy and meet the required QoS. However, they do not control the internal and external switching to server frequencies, which causes the degradation of performance. In this paper, we propose the Real Time Adaptive EnergyScheduling (RTAES) algorithm by manipulating the reconfiguring proficiency of Cloud ComputingVirtualized Data Centers (CCVDCs) for computationally intensive applications. The RTAES algorithm minimizes consumption of energy and time during computation, reconfiguration and communication. Our proposed model confirms the effectiveness of its implementation, scalability, power consumption and execution time with respect to other existing approaches
Virtual Machine (VM); Virtualized Data Centers (VDCs); Quality of Service (QoS); Dynamic Voltage and Frequency Scaling (DVFS); Real Time Adaptive Energy-Scheduling (RTAES).
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Advanced Diffusion Approach to Dynamic Load-Balancing for Cloud Storage
Eman Daraghmi1 and Yousef-Awwad Daraghmi2 1,2Palestine Technical University Kadoori (PTUK), Palestine
Load-balancing techniques have become a critical function in cloud storage systems that consist of complex heterogeneous networks of nodes with different capacities. However, the convergence rate of any load-balancing algorithm as well as its performance deteriorated as the number of nodes in the system, the diameter of the network and the communication overhead increased. Therefore, this paper presents an approach aims at scaling the system out not up - in other words, allowing the system to be expanded by adding more nodes without the need to increase the power of each node while at the same time increasing the overall performance of the system. Also, our proposal aims at improving the performance by not only considering the parameters that will affect the algorithm performance but also simplifying the structure of the network that will execute the algorithm. Our proposal was evaluated through mathematical analysis as well as computer simulations, and it was compared with the centralized approach and the original diffusion technique. Results show that our solution outperforms them in terms of throughput and response time. Finally, we proved that our proposal converges to the state of equilibrium where the loads in all in-domain nodes are the same since each node receives an amount of load proportional to its capacity. Therefore, we conclude that this approach would have an advantage of being fair, simple and no node is privileged.
Load balancing, cloud storage, Heterogeneous, Simulation, Task assignment
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Design and Analysis of Secure Smart Home for Elderly People
Mayada Elsaid, Sara Altuwaijri, Nouf Aljammaz and Anees Ara, Prince Sultan University, Saudi Arabia
Internet of Things (IoT) technology is used to enhance the safety of the elderly living in smart home environments and to help their caregivers. The daily behaviour of the elderly people is collected using IoT sensors and then evaluated to detect any abnormal behaviour. This research paper analyzes the smart home based anomaly detection system from a security perspective, to answer the question whether it is reliable and secure enough to leave elderly people alone in their smart homes. In this direction comparative analysis of literature is done to identify the potential security breaches on all layers of an IoT device. Further, this paper proposes a secure smart home model, built using Cisco Packet Tracer to simulate a network of IoT devices in a smart home environment. Consequently, a list of security countermeasures is proposed to protect the IoT devices from the identified attacks
Cyber physical systems, anomaly detection system, intrusion detection system, secure smart home, IoT
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