Cost has become the crucial feature for explaining any type of technology efficiently. It is an important aspect for designing any technology. Cloud computing has become the main stage factor of technology by its behavior. Due to its incredible applications and services, figure of choices are growing with time. Therefore, task scheduling algorithms are needed for better execution of any activity. Scheduling is done by appointment of the activities to the machine to run in a better manner. Nowadays users become greedier by changing their demands frequently with enhancement of the technologies provided through the cloud service provider by fruity organization. There are lots of scheduling algorithms based on some priority/nonpriority mechanism to perform a task. To apply filtering in the selection for best scheduling algorithm, a new technique is proposed based on the nature of grey wolf. Comparative study is also considered in this paper with this new optimizing technique. Evaluation is done based on cost factor. Quality of goodness is calculated by the experiments through CloudSim simulator.

https://link.springer.com/content/pdf/10.1007%2F978-981-32-9186-7_16.pdf

Grey Wolf Optimized Task Scheduling Algorithm in Cloud Computing

Trust is just a feeling to make the things reliable. Higher probability of successful execution of scheduling builds the trust greater. Consequently, probability of failure of task of particular scheduling makes one understand that the scheduling is not good for profit in the market, and one does not trust that. Trust can be generated through many factors or reasons. The fruit congenial concept explores these factors to make the things understandable in actual way. In this review, we will categorize all these factors through flowchart and suitable diagrams and help to think the reality to make/do the things correct toward technology. Trust remains same in real life as well as in technology.

Trust for Task Scheduling in Cloud Computing Unfolds It Through Fruit Congenial

Cost is becoming the fruity factor to show the performance for any kind of experiment. Task scheduling algorithms are the valuable term in these days because of its performance in distributed computing environment. Market wants to pay minimum cost for every aspect. Task scheduling is performing the lead role in distributed computing with reducing cost. Various optimized task scheduling has been developed for execute the task efficiently. This paper proves that optimized task scheduling algorithms are better than traditional one’s ever.

/pdf/optimized-task-scheduling-algorithms-in-distributed-4vvzkzauyc.pdf

Optimized Task Scheduling Algorithms in Distributed Computing: A Review

Cloud computing is becoming one of the next industry buzz words. In the current cloud computing scenario, the need for establishing an SLA is highly essential, since it expresses the commitment of provider to create an affordable balance between hosting costs and high levels of service availability during the service offerings. It is also highly necessary to monitor dynamically whether the QoS mentioned in the SLA, is met by the service provider. Moreover, a reliable trust model is required to give a quantitative measure of the trust to the requester before choosing a service provider. In this paper, we portray a dynamic trust establishment framework, wherein the Third-party SLA monitor provides an on-demand QoS assessment module, on a real time basis. Based on the computed trust value, the service provider is chosen. Then, the concept of Adaptive window-based state monitoring is introduced, negating the drawbacks associated with the existing techniques, by reducing the amount of data sent over the network. The proposed approach is implemented and it proves to be efficacious than the existing techniques in most cases.

Dynamic Trust Establishment and Amended Window Based Monitoring in Cloud

IoT-based intrusions and network attacks are becoming ever more concerning. As a mitigatory measure, the IETF standardized Manufacturer Usage Description (MUD) which allows IoT device vendors to specify the legitimate communication patterns (as a MUD profile) of an IoT device. A MUD profile allows the validation of the actual communication pattern of an IoT device with the intended behavior at runtime. However, as the number of IoT devices increases, validation at runtime has scalability challenges in terms of the number of switch resources (e.g., TCAM) required to maintain MUD profiles.In this work, we propose a scalable data plane primitive and a system on top of the primitive, which together enforce MUD profiles of thousands of IoT devices in a P4 programmable switch data plane. Our main idea is to avoid inefficiencies because of the repetition of header values while representing MUD profile-based ACL rules. Further, we exploit the characteristics of header values in ACL rules of real IoT devices and carefully partition the rules across multiple hash-based exact match-action tables in the switch data plane. Since hash-based data structures can be implemented using SRAM which is cheap and abundantly available (order of MBs) in commodity programmable switches, our approach scales well for a large IoT network.

Swathy Harish

Papers

Dynamic Trust Establishment and Amended Window Based Monitoring in Cloud

Scaling IoT MUD Enforcement using Programmable Data Planes