Smart algorithm to optimize performance of the heterogeneous multi-cloud network

Dr Sambit Kumar Mishra

As the world goes more digital in the future, the dependability on cloud computing is going to be more. The availability of high-capacity networks, low-cost computers and storage devices as well as the widespread adoption of hardware virtualization, service-oriented architecture and autonomic and utility computing has led to growth in cloud computing. But is it enough? How to improve its performance? How to make it more reliable with high-end technology and impeccable performance quality? Dr Sambit Kumar Mishra’s research has an answer to that.

System Model for Multi-cloud Networks Dr Sambit Kumar Mishra, Assistant Professor, Computer Science and Engineering has published a paper “Energy-Aware Task Allocation for Multi-Cloud Networks” in renowned journal IEEE ACCESS with an Impact Factor: 3.745. The research was done in collaboration with Dr Sonali Mishra, SOA (Deemed to be) University Bhubaneswar, India; Dr Ahmed Alsayat, College of Computer and Information Sciences Jouf University, Al-Jouf, Saudi Arabia; Dr N Z Jhanjhi and Dr Mamoona Humayun, School of Computer Science and Engineering (SCE), Taylor’s University, Malaysia; Dr Ashish Kr. Luhach, The PNG University of Technology, Papua New Guinea Lae, Morobe; Dr Kshira Sagar Sahoo, VNRVJIET, Hyderabad, India.

Example of Direct Acyclic Graph (DAG)with four TasksIn recent years, the growth rate of Cloud computing technology is exponentially, mainly for its extraordinary services with expanding computation power, the possibility of massive storage and all other services with the maintained quality of services (QoS). The task allocation is one of the best solutions to improve different performance parameters in the cloud, but when multiple heterogeneous clouds come into the picture, the allocation problem becomes more challenging. This research work proposed a resource-based task allocation algorithm. The same is implemented and analysed to understand the improved performance of the heterogeneous multi-cloud network. The proposed task allocation algorithm (Energy-aware Task Allocation in Multi-Cloud Networks (ETAMCN)) minimizes the overall energy consumption and also reduces the makespan. The results show that the makespan is approximately overlapped for different tasks and does not show a significant difference. However, the average energy consumption improved through ETAMCN is approximately 14%, 6.3%, and 2.8% in opposed to the random allocation algorithm, Cloud Z-Score Normalization (CZSN) algorithm, and multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS), respectively. An observation of the average SLA-violation of ETAMCN for different scenarios is performed.

Energy Consumption Vs SLA Violation when
the number of VMs varies and the number of Task is 100.The multi-cloud strategy offers flexibility to service providers. It allows businesses to be productive while using the proper set of services to optimize their opportunities. Adopting a multi-cloud network enables an enterprise to implement a “best of breed” model for the services. Organizations’ ability to choose the vendor that offers the best price for their workload is added significant advantage of multi-cloud. Thus, the optimization of energy consumption in a multi-cloud environment is necessary for the current generation.

However, this proposed work has not considered any priority-oriented users, such as task execution through reserve resource in the network, which will be considered as his future work. The future work also aims to propose a task cum resource-aware scheduling approach that will exploit the nature of the presented workload and efficiently map on the available Cloud resources so that energy consumption will optimize.

Link to the research paper: Please Click Here

K. Sree Rama Murthy, Second Year B. Tech-CSE student presented a paper at a conference in IIT-Kharagpur

K. Sree Rama MurthySRM University-AP always inspires the students in their pursuits, be it a job of their choice or a career in research and higher studies. K. Sree Rama Murthy, a 2nd-year student of B.Tech in Computer Science and Engineering, has recently presented a research paper on “A Block-wise Histogram Shifting based Reversible Data Hiding Scheme with Overflow Handling” in the Eleventh International Conference on Computing, Communication and Networking Technologies (11th ICCCNT), held at IIT Kharagpur, India in association with IEEE Kharagpur Section, during July 1 – 3, 2020.

Data hiding is a process of embedding a secret message into a cover medium for secure message transmission. The reversible data hiding techniques are recently explored in the domain of data hiding in which the cover image can be recovered while extracting the hidden secret message. The overview of a reversible data hiding scheme is shown in Figure. 1.

Figure 1. Overview of reversible data hiding

In this research paper, Sree Rama Murthy introduced a new reversible data hiding algorithm based on the histogram of the blocks of the cover images with an efficient overflow management technique to achieve a better embedding rate without compromising the visual quality of the stego image.

Design and development of reversible data hiding schemes are widely studied topic due to its wide scope in cloud computing and medical image transmission. This paper introduces a new reversible data hiding algorithm based on the histogram of the blocks of the cover images with an efficient overflow management technique. In the new scheme, the peak intensity value from each block is used for data hiding, and to make sure the correct recovery of the original image, the grayscale value used for data hiding from each block is embedded in the same block itself by replacing the least significant bits of eight selected pixels. The lossless recovery is ensured by embedding those least significant bits in the same block itself along with the secret message. Detailed theoretical analysis and experimental study of the scheme are carried out and discussed in this paper. The images from the standard image dataset of the University of Southern California (USC-SIPI) are used in their study.

“To be able to publish a research paper at such an early stage in a reputed conference like ICCCNT-2020 is an achievement that has acted as a cornerstone for my research aspirations. I feel highly encouraged, motivated and inspired to contribute more in the fields of research. I express my sincere gratitude to my professors, especially to Dr Manikandan V. M for providing me with the opportunity to collaborate. He put his trust on me, encouraged to do research with him and guided me with his knowledge and experience throughout the journey. I feel this is only the beginning for me, and I will try my best to accomplish more and retain more knowledge,” said Sree Rama Murthy.

Sree Rama Murthy plans to acquire a master’s degree in computer science and aspires to be a researcher who can make significant contributions in the domain of Computer Science and Engineering.