A survey on the scheduling mechanisms in serverless computing: a taxonomy, challenges, and trends

This paper introduces Golgi, a novel scheduling system designed for serverless functions, with the goal of minimizing resource provisioning costs while meeting the function latency requirements. To achieve this, Golgi judiciously over-commits functions based on their past resource usage. To ensure overcommitment does not cause significant performance degradation, Golgi identifies nine low-level metrics to capture the runtime performance of functions, encompassing factors like request load, resource allocation, and contention on shared resources. These metrics enable accurate prediction of function performance using the Mondrian Forest, a classification model that is continuously updated in real-time for optimal accuracy without extensive offline training. Golgi employs a conservative exploration-exploitation strategy for request routing. By default, it routes requests to non-overcommitted instances to ensure satisfactory performance. However, it actively explores opportunities for using more resource-efficient overcommitted instances, while maintaining the specified latency SLOs. Golgi also performs vertical scaling to dynamically adjust the concurrency of overcommitted instances, maximizing request throughput and enhancing system robustness to prediction errors. We have prototyped Golgi and evaluated it in both EC2 cluster and a small production cluster. The results show that Golgi can meet the SLOs while reducing the resource provisioning cost by 42% (30%) in EC2 cluster (our production cluster).

Golgi: Performance-Aware, Resource-Efficient Function Scheduling for Serverless Computing

The main aim of the proposed work is to design a secure cloud storage and data distribution platform for the open cloud (public cloud). This platform offers the secure communication among client and server during the data transmission from the client device. In addition of that it also provides the secure technique to share and transfer the file from one user to another. Therefore to secure the entire communication and storage of cloud server a cryptographic cloud is proposed for implementation and design. To provide security using the cryptographic technique a number of traditional and modern cryptographic techniques are studied. In most of the cryptographic techniques either the time and space complexity is much higher or they are much frequently used and utilized from the classical security point of view. Thus in this presented work the DNA based cryptographic algorithm for security is used. The DNA based cryptographic technique is basically developed using the substitution and other basic operator's implementation. Thus this technique is less computational cost effective and efficient. On the other hand the only four symbols are used for transforming entire massage to the cipher. Due to this security is also enhanced in terms of their recovery process. The proposed SaaS (software as a service) demonstrate the security using the upload, download and sharing of files using the proposed platform. The implementation of the proposed security platform for data exchange and sharing is provided using the JAVA technology. Additionally for the deployment the OpenShift cloud (public cloud) is used. The experimental performance in terms of time and space complexity demonstrates the effective and low resource consuming technique for the cloud data security.

A secure cryptographic cloud communication using DNA cryptographic technique

Abstract CERN (Centre Europeen pour la Recherce Nucleaire) is the largest research centre for high energy physics (HEP). It offers unique computational challenges as a result of the large amount of data generated by the large hadron collider. CERN has developed and supports a software called ROOT , which is the de facto standard for HEP data analysis. This framework offers a high-level and easy-to-use interface called RDataFrame , which allows managing and processing large data sets. In recent years, its functionality has been extended to take advantage of distributed computing capabilities. Thanks to its declarative programming model, the user-facing API can be decoupled from the actual execution backend . This decoupling allows physical analysis to scale automatically to thousands of computational cores over various types of distributed resources. In fact, the distributed RDataFrame module already supports the use of established general industry engines such as Apache Spark or Dask. Notwithstanding the foregoing, these current solutions will not be sufficient to meet future requirements in terms of the amount of data that the new projected accelerators will generate. It is of interest, for this reason, to investigate a different approach, the one offered by serverless computing. Based on a first prototype using AWS Lambda , this work presents the creation of a new backend for RDataFrame distributed over the OSCAR tool, an open source framework that supports serverless computing. The implementation introduces new ways, relative to the AWS Lambda -based prototype, to synchronize the work of functions. 

https://link.springer.com/content/pdf/10.1007/s11227-022-05016-y.pdf

Leveraging an open source serverless framework for high energy physics computing

Cloud computing is a new computing paradigm in the field of it that provides hosted services to a large number of user on demand basis over the internet. They are internet based network that has large numbers of servers. It allows to use the services only when you want and pay only for the amount what you have used. Since cloud computing share distributed resources over an open environment, so security becomes a major concern here. To improve the work performance different services are distributed on different servers but the security and safety aspects are remaining insufficient. Security is the one of major issues that hampers the growth of cloud. So, in this paper we first try to give an idea about cloud computing and then concentrate on the major security aspects of cloud computing paradigm.

/pdf/cloud-computing-and-its-security-aspects-whvad1aj0q.pdf

Cloud computing and its security aspects

Consider an analogy where personal computer users are not required to run, install or store their applications on their personal computers. Consider a situation where every piece of your information and data may be stored on the cloud (Internet). As an allegory for the Internet, cloud is a very popular word but when integrated with the word “computing,” it becomes more important and uncertain. Cloud computing comes into focus only when users think about what they always need, which leads to the concept of an updated version of utility computing. The advancement of cloud computing came about because of the quickly developing utilization of the web among the general population. Cloud computing is anything but an absolutely new innovation; it's actually a voyage through distributed, cluster, grid and presently cloud computing. Before the increasing utilization of the web everywhere throughout the globe, cloud computing had just been used in the IT business. Cloud computing is transforming the computing landscape. The cloud concept and its computing process is an emerging topic in internet-centric and IT-market-oriented businesses. The goal required for the IT industry should be a direct conversation about how this new computing worldview will put an effect the associations, how it can be utilized with the current advancements. Cloud computing needs a third-party vendor through which a client or an end user or a customer may use the cloud provided by a cloud service provider (CSP) on demand. 

Basics of Cloud Computing

Source: CloudSim is developed in the CLOUDS Laboratory, at the Computer Science and Software Engineering Department of the University of Melbourne. CloudSim Toolkit 3.0 was released in Jan 13, 2012. Software License: The CloudSim Toolkit software is released as open source under Lesser General Public License (LGPL) license. Copyright: The CLOUDS Lab, The University of Melbourne, 2009 to date. Downloaded Information: http://www.cloudbus.org/cloudsim https://code.google.com/p/cloudsim 

Cloudsim: A Simulator for Cloud Computing Environment

Plant diseases need the maximum amount of attention currently as ever to ensure that food systems are in situ within the next season. There are serious implications for biological science and also the atmosphere more generally. Deep learning technologies produce opportunities for revamping operations, employment management, production, and forestry management. This paper focuses on the utilization of MobileNetV2 in the image process on mobile devices. This advanced version of MobileNet is specifically curated to make it useful and compatible with mobile applications, and it also permits efficient inference along with the utilization of operations existing in all neural frameworks. The given approach resulted in close to 100% accuracy on the given dataset with minimum number of iterations. It is also inferred that a good accuracy score can be achieved in real-time mobile devices since the model uses less computations to make accurate predictions. This approach hence focuses on “Next-Gen” revolutionary on-device computer vision network. 

Plant Disease Identification Based on Leaf Images Using Deep Learning

Cloud computing is an emerging field in the era of the internet where information and physical resources can be provided to cloud users according to their needs on a pay-as-yougo basis. Security and privacy are major concerns in the cloud computing environment. To address these issues all physical resources, such as computing resources, sensitive user data, and processes, are managed by a third-party service provider. Auditing in a cloud computing environment paves the way for the cloud service provider to make performance and security data readily available to the cloud user. Hence, to maintain data confidentiality, privacy, integrity, and availability, auditing is introduced within third-party service providers. This chapter studies various issues in auditing that have been encountered in practice and also proposes a framework that helps the designer to incorporate auditing aspects in a cloud computing environment. 

Auditing Concept in Cloud Computing

In today's enterprise environments, virtual machine migration is a cloud infrastructure capability that is increasingly being used. It is the key feature of virtualized technologies. Virtual machine live migration is basically transferring instances that include the operating system, runtime memory pages, and active CPU states from a source host to the destination host. Moreover, live migration reduces service downtime, which facilitates proactive maintenance, fault management and load balancing for the virtual machine (VM). 

An Approach to Live Migration of Virtual Machines in Cloud Computing Environment

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