Strict Timed Causal Consistency as a Hybrid Consistency Model in the Cloud Environment

2020 ◽  
Vol 105 ◽  
pp. 259-274
Author(s):  
Hesam Nejati Sharif Aldin ◽  
Hossein Deldari ◽  
Mohammad Hossein Moattar ◽  
Mostafa Razavi Ghods
Keyword(s):  
Cloud Environment ◽  
Consistency Model ◽  
Causal Consistency

scholarly journals Convergence Through a Weak Consistency Model

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Francisco J. Torres-Rojas ◽  
Esteban Meneses
Keyword(s):  
Real Time ◽  
Distributed System ◽  
Weak Consistency ◽  
Consistency Model ◽  
Causal Consistency ◽  
Shared Objects

Given a distributed system with several shared objects and many processes concurrently updating and reading them, it is convenient that the system achieves convergence on the value of these objects. Such property can be guaranteed depending on the consistency model being employed. Causal Consistency is a weak consistency model that is easy and cheap to implement. However, due to the lack of real-time considerations, this model cannot offer convergence. A solution for overcoming that problem is to include time aspects within the framework of the model. This is the aim of Timed Causal Consistency.

scholarly journals Checking Robustness Between Weak Transactional Consistency Models

2021 ◽  
pp. 87-117
Author(s):  
Sidi Mohamed Beillahi ◽  
Ahmed Bouajjani ◽  
Constantin Enea
Keyword(s):  
Distributed Systems ◽  
Polynomial Time ◽  
Reduction Theory ◽  
Proof Technique ◽  
Reachability Problem ◽  
Snapshot Isolation ◽  
Trade Offs ◽  
Consistency Model ◽  
Causal Consistency ◽  
Consistency Models

AbstractConcurrent accesses to databases are typically encapsulated in transactions in order to enable isolation from other concurrent computations and resilience to failures. Modern databases provide transactions with various semantics corresponding to different trade-offs between consistency and availability. Since a weaker consistency model provides better performance, an important issue is investigating the weakest level of consistency needed by a given program (to satisfy its specification). As a way of dealing with this issue, we investigate the problem of checking whether a given program has the same set of behaviors when replacing a consistency model with a weaker one. This property known as robustness generally implies that any specification of the program is preserved when weakening the consistency. We focus on the robustness problem for consistency models which are weaker than standard serializability, namely, causal consistency, prefix consistency, and snapshot isolation. We show that checking robustness between these models is polynomial time reducible to a state reachability problem under serializability. We use this reduction to also derive a pragmatic proof technique based on Lipton’s reduction theory that allows to prove programs robust. We have applied our techniques to several challenging applications drawn from the literature of distributed systems and databases.

A Longitudinal Study of Mental Health in Emerging Adults

2014 ◽  
Vol 73 (3) ◽  
pp. 135-141 ◽  
Author(s):  
Monica S. Bachmann ◽  
Hansjörg Znoj ◽  
Katja Haemmerli
Keyword(s):  
Mental Health ◽  
Longitudinal Study ◽  
Emerging Adults ◽  
Poor Mental Health ◽  
Need Satisfaction ◽  
Computer Assisted ◽  
Consistency Model ◽  
Negative Effect ◽  
The Cross ◽  
Health Model

Emerging adulthood is a time of instability. This longitudinal study investigated the relationship between mental health and need satisfaction among emerging adults over a period of five years and focused on gender-specific differences. Two possible causal models were examined: (1) the mental health model, which predicts that incongruence is due to the presence of impaired mental health at an earlier point in time; (2) the consistency model, which predicts that impaired mental health is due to a higher level of incongruence reported at an earlier point in time. Emerging adults (N = 1,017) aged 18–24 completed computer-assisted telephone interviews in 2003 (T1), 2005 (T2), and 2008 (T3). The results indicate that better mental health at T1 predicts a lower level of incongruence two years later (T2), when prior level of incongruence is controlled for. The same cross-lagged effect is shown for T3. However, the cross-lagged paths from incongruence to mental health are marginally associated when prior mental health is controlled for. No gender differences were found in the cross-lagged model. The results support the mental health model and show that incongruence does not have a long-lasting negative effect on mental health. The results highlight the importance of identifying emerging adults with poor mental health early to provide support regarding need satisfaction.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Enhanced Data Security from Single Clouds to Multiclouds

2018 ◽  
Vol 6 (9) ◽  
pp. 66
Author(s):  
Umesh Banodha ◽  
Praveen Kumar Kataria
Keyword(s):  
Data Storage ◽  
Network Connectivity ◽  
Data Replication ◽  
Recovery Process ◽  
Cloud Environment ◽  
Storage Security ◽  
Cloud Data ◽  
Replication Strategy ◽  
Cloud Data Storage ◽  
Data Files

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.

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