Reliable Data Auditing and ACO-Based Resource Scheduling for Cloud Services

2020 ◽  
pp. 107-125
Author(s):  
Soumitra Sasmal ◽  
Indrajit Pan
2021 ◽  
Vol 11 (12) ◽  
pp. 3054-3061
Author(s):  
S. Sureshu ◽  
R. Vijayabhasker

Real-time physiological data may be gathered using wearable medical sensors based on a network of body sensors. We do not however have an effective, trustworthy and secure body sensor network platform (BSN) that can satisfy growing e-health requirements. Many of these applications require BSN to provide the dependable and energy efficient data transfer of many data speeds. Cloud computing is giving assets to patient dependent on application request at SLA (service level agreement) rules. The service providers are focusing on giving the necessity based asset to satisfy the QoS (quality of service) prerequisites. Therefore, it has become an assessment to adapt service-oriented assets because of vulnerability and active interest for cloud services. The task scheduling is an option in contrast to appropriating asset by evaluating the inconsistent outstanding task at hand. the allocation of tasks given by the microprocessor Subsequently, a productive asset scheduling method needs to disseminate proper VMs (Virtual Machines). The swarm intelligence is appropriate to deal with such vulnerability issues carefully. In this paper, an effective resource scheduling strategy Utilizing Modified Particle Swarm Optimization approach (MPSO) is presented, with a target to limit execution cost that gives an approach for the microprocessor to deal with the multiple number of tasks gives to the controllers in order to perform the multiple tasks that gets logged in the cloud via Internet of things technology (Iot), energy consumed, bandwidth consumption, speed and execution cost. The near investigation of results has been exhibited that the presented scheduling scheme performed better when contrasted with existing evaluation. In this manner, the presented resource scheduling approach might be utilized to enhance the viability of cloud resources.


2019 ◽  
Vol 9 (1) ◽  
pp. 166 ◽  
Author(s):  
Farhan Amin ◽  
Awais Ahmad ◽  
Gyu Sang Choi

The Internet of Things (IoT) is an interconnected network of heterogeneous entities, such as sensors and embedded devices. During the current era, a new field of research has emerged, referred to as the social IoT, which mainly includes social networking features. The social IoT refers to devices that are capable of creating interactions with each other to independently achieve a common goal. Based on the structure, the support of numerous applications, and networking services, the social IoT is preferred over the traditional IoT. However, aspects like the roles of users and network navigability are major challenges that provoke users’ fears of data disclosure and privacy violations. Thus, it is important to provide reliable data analyses by using trust- and friendliness-based properties. This study was designed because of the limited availability of information in this area. It is a classified catalog of trust- and friendliness-based approaches in the social IoT with important highlights of important constraints, such as scalability, adaptability, and suitable network structures (for instance, human-to-human and human-to-object). In addition, typical concerns like communities of interest and social contacts are discussed in detail, with particular emphasis on friendliness- and trust-based properties, such as service composition, social similarity, and integrated cloud services.


2021 ◽  
Vol 9 (2) ◽  
pp. 968-977
Author(s):  
B.SivaRama Krishna, Et. al.

Application level resource scheduling in distributed cloud computing is a significant research objective that grabbed the attention of many researchers in recent literature. Minimal resource scheduling failures, robust task completion and fair resource usage are the critical factors of the resource scheduling strategies. Hence, this manuscript proposed a scalable resource-scheduling model for distributed cloud computing environments that aimed to achieve the scheduling metrics. The proposed model called " Modified Resource Scheduling with Schedule Interval Filling " schedules the resource to respective task such that the optimal utilization of resource idle time achieved. The proposed model performs the scheduling in hierarchical order and they are optimal idle resource allocation, if no individual resource is found to allocate then it allocates optimal multiple idle resources with considerable schedule intervals filling. The experimental results evincing that the proposed model is scalable and robust under the adapted metrics.


2018 ◽  
Vol 4 (8) ◽  
pp. 8
Author(s):  
Saloni Atre ◽  
Mayank Namdev

Cloud computing is an enormous area which shares huge amount of data over cloud services and it has been increasing with its on-demand technology. Since, with these versatile cloud services, when the delicate data stored within the cloud storage servers, there are some difficulties which has to be managed like its Security Issues, Data Privacy, Data Confidentiality, Data Sharing and its integrity over the cloud servers dynamically. Also, the authenticity and data access control should be maintained in this wide environment. Thus, Attribute based Encryption (ABE) is a significant version of cryptographic technique in the cloud computing environment. Data integrity, one of the most burning challenges in secure cloud storage. Data auditing protocols enable a verifier to efficiently check the integrity of the files without downloading the entire file from the cloud. In this paper cloud data integrity checking is performed by introducing attribute-based cloud data auditing where users can upload files to cloud through some set of attributes and specify auditor to check the integrity of data files. Existing protocols are mostly based on public key infrastructure or an exact identity, which lacks ?exibility of key management. In this research work Cloud data integrity checking is performed by introducing attribute-based cloud data auditing where users can upload files to cloud through some set of attributes and specify auditor to check the integrity of data files. Variable attributes are used to generate the private key and their performance is evaluated under variable attribute list.


Author(s):  
Kuang Yuejuan ◽  
Luo Zhuojun ◽  
Ouyang Weihao

Background: In order to obtain reliable cloud resources, reduce the impact of resource node faults in cloud computing environment and reduce the fault time perceived by the application layer, a task scheduling model based on reliability perception is proposed. Methods: The model combines the two-parameter weibull distribution and analyzes various interaction relations between parallel tasks to describe the local characteristics of the failure rules of resource nodes and communication links in different periods.The model is added into the particle swarm optimization (pso) algorithm, and an adaptive inertial weighted pso resource scheduling algorithm based on reliability perception is obtained. Results: Simulation results show that when A increases to 0.3, the average scheduling length of the task increases rapidly.When it is 0.4-0.6, the growth rate is relatively slow.When greater than 0.8, the average scheduling length increases sharply.It can be seen that the r-pso algorithm proposed in this paper can accurately estimate the relevant parameters of cloud resource failure rule, and the generated resource scheduling scheme has better fitness, and the optimization effect is more significant with the increase of the number of tasks. Conclusion: With only a small amount of time added, the reliability of cloud services is greatly improved.


2020 ◽  
Vol 13 (36) ◽  
pp. 3725-3737
Author(s):  
Junaid Ahmed Uqaili ◽  

Background/Objectives: The major problems in WSN are the short-range of RF signals and the short life of batteries of each node. We develop a platform that uses the MAC protocols to avoid collisions between packets and decrease the data collection time. To overcome the energy challenges, the sleep modes, idle consumption, and others solutions provided to extend the node’s life period Methods/Statistical analysis: Based on the IoT applications, we configured different hardware (HW) to collect data from temperature,relative humidity (RH), and carbon dioxide (CO2), and access to this data, and these devices remotely through the internet. For this, the nodes, transceivers, batteries, and the gateway (GW) are analyzed. Additionally, it is configured with the frequency band or the radio frequency (RF) sensitivity to improve the performance of the system developed. Findings: Sensors, repeaters, and the GW were configured to work with each other and be accessed through the internet. The energy consumed on the experiment carried out has been reduced by more than 80% choosing LP modes and enable sleep algorithms over the Node’s OS where the time was also reduced around 80% in comparison with the available options. By set MQTT and SSH services, this application is scalable to be integrated with cloud services and be accessed by remote computers. Novelty/Applications: Finally, the lifelong period of nodes augmented drastically, more range between nodes is achieved and highly reliable data collected with low power consumption. Keywords: WSN; sensors; IoT; CO 2; temperature; relative humidity (RH)


Author(s):  
R. J. Lee ◽  
A. J. Schwoeble ◽  
Yuan Jie

Water/Cement (W/C) ratio is a very important parameter affecting the strength and durability of concrete. At the present time, there are no ASTM methods for determining W/C ratio of concrete structures after the production period. Existing techniques involving thin section standard density comparative associations using light optical microscopy and rely on visual comparisons using standards and require highly trained personnel to produce reliable data. This has led to the exploration of other methods utilizing automated procedures which can offer a precise and rapid measurement of W/C ratio. This paper discusses methods of determining W/C ratio using a scanning electron microscope (SEM) backscattered electron image (BEI) intensity signal and x-ray computer tomography.


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