EH-GC: An Efficient and Secure Architecture of Energy Harvesting Green Cloud Infrastructure

Abstract

Nowadays, the high power consumption of data centers is the biggest challenge to making cloud computing greener. Many researchers are still seeking effective solutions to reduce or harvest the energy produced at data centers. To address this challenge, we propose a green cloud infrastructure which provides security and efficiency based on energy harvesting (EH-GC). The EH-GC is basically focused on harvesting the heat energy produced by data centers in the Infrastructure-as-a-Service (IaaS) infrastructure. A pyroelectric material is used to generate the electric current from heat using the Olsen cycle. In order to achieve efficient green cloud computing, the architecture utilizes a genetic algorithm for proper virtual machine allocation, taking into consideration less Service Level Agreement (SLA) violations. The architecture utilizes Multivariate Correlation Analysis (MCA) correlation analysis based on a triangular map area generation to detect Denial of Service (DoS) attacks in the data center layer of the IaaS. Finally, the experimental analysis is explained based on the energy parameter, which proves that our model is efficient and secure, and that it efficiently reuses the energy emitted from the data center.

Predictive model for battery life in IoT networks

“…An architecture was proposed for the green cloud environment to provide secure and efficient energy harvesting. The architecture includes a genetic algorithm for the allocation of the virtual machine and multivariate correlation analysis for the detection of denial of service attacks that can happen at data centers [43]. Genetic algorithm and multivariate correlation analysis were used in the proposed framework in order to obtain systematic consumption and utilisation of power.…”

Energy Efficient Computation Offloading Mechanism in Multi-Server Mobile Edge Computing—An Integer Linear Optimization Approach

“…Several IoT devices offload the heavy computation workload to the MEC devices such as base stations, access points, and so forth [2]. Integrating EH and MEC techniques contribute to improving computation performance and open new possibilities for cloud computing [3,4].…”