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Currently, digital news portals have been one of the most important news sources for Internet users. However, the way it is written depends on the direction of the content. One approach to news reporting is through manipulative writing. Such method of writing has created a number of adverse outcomes such as political unrest, slander and negative perception towards the particular organization, personnel, and country. It is important for readers to choose and select news portal that is reporting positively and to neglect portals which practices manipulative writing approach for their own gains or causing negative impact towards the community. The aim of this study is to structure and analyzed the literature related to data veracity research that can be used to the profile of digital news portal. The method that has been used in this paper is to classify and define data veracity; a systematic literature review is a conduct. It includes journal and conference proceedings. The results come out with objectives in data veracity, the structure of research topics, research trends with publications and framework veracity model validated. This paper provides a complete review of literature related to profiling digital news portal in data veracity.

Controlling access to the cloud computing services involves new scalability and security challenges that cannot be directly addressed by traditional access control solutions. In other words, cloud computing access control requires establishing a trust between users, service provider and provided services in a scalable manner. Moreover, several access control issues have not been considered in cloud computing such as providing users with a temporal and delegable access. This paper proposed the design of a trusted and decentralized cloud computing access control model for better security and scalability. To address the scalability issue, the components of the proposed model are separated in such a way that they can be decentralized and executed in different extensible machines. The proposed model includes a Trusted XML-based Cloud Computing Policy Language (TXCCPL) that specifies access control policies for authenticating and authorizing both the user and his platform based on the Decentralized Trust Management (DTM) and Trusted Computing (TC) concepts. An Identity Based Encryption (IBE) is used for providing users with temporal and delegable access. Our analysis shows that the proposed model is cost-effectively distributed while avoiding the possible bottlenecks and, as a result, effectively scales with increased workloads. Also, using the DTM and TC concepts help on addressing several security challenges found in cloud computing.

Problem statement: Impatient jobs are the jobs that have strict constraints in starting and completion time and need a fast response and attention in mapping to resources. The negotiation process in cloud computing needs a customer-provider agreement that leads to loss of a significant amount of time for impatient jobs. The huge increasing in cloud service providers makes selecting the best provider an exhaustive task. Approach: We considered the problem of Service Level Agreement (SLA) negotiation and commitment process for immediate mode scheduling under intercloud paradigm. This study explored an alternative model dedicated for impatient jobs under intercloud paradigm. We developed a model of negotiation where the cloud-broker had the ability to nominate the best cloud provider, commit the agreement and submit the jobs for execution. Cloudsim simulators with synthetic datasets had been used to evaluate the proposed system. Results: The results showed an improvement in SLA waiting time and the number of jobs failure. Conclusion: This study proved the importance of rapid mapping for impatient jobs in increasing system throughput.

Problem statement: Task scheduling is the main factor that determines the performance of any distributed system. Cloud computing comes with a paradigm of distributed datacenters. Each datacenter consists of physical machines that host virtual machines to execute customers' tasks. Resources allocation on the cloud is different from other paradigms and the mapping algorithms need to be adapted to the new characteristics. This study takes the problem of immediate task scheduling under an intercloud infrastructure using a genetic algorithm. An impatient task needs to be scheduled as soon as it enters the system taking into account the input and output files location and its QoS requirements. Approach: This study proposes an algorithm that can find a fast mapping using genetic algorithms with "exist if satisfy" condition to speed up the mapping process and ensures the respecting of all task deadlines. Cloudsim simulator was used to test the proposed algorithm with real datasets collected as a cloud benchmark. Mapping time and makespan are the performance metrics that are used to evaluate the proposed system. Results: The results show an improvement in the proposed system compared to MCT algorithm as illustrated throughout the study. Conclusion: Batch mapping via genetic algorithms with throughput as a fitness function can be used to map jobs to cloud resources.

Problem statement: Cooperative caching, which allows sharing and coordination of cached data among clients, is a potential technique to improve the data access performance and availability in mobile ad hoc networks. However, variable data sizes, frequent data updates, limited client resources, insufficient wireless bandwidth and client’s mobility make cache management faces many challenges. Approach: In this study, we propose a Cluster Cache Collaborative (CCC) to reduce the average delay and increase the local cache hit ratio. Our architecture considers several factors that affect cache performance, namely: access probability, query status, distance between the requester and data source/cache, and data size. A collaborative cache management strategy, intra/inter cluster, is developed that employs Last Recently Used (LRU) and Time-To-Live (TTL) as the replacement data policy. Results: Our proposed architecture is being evaluated and compared to previous study’ architectures, and result shows that our architecture is different from other approaches by including query status model into a collaborative caching architecture to reduce the number of hopes between the requested node and the source node. Conclusion/Discussion: Due to the limitations of previous study’ architectures, this study attempts to enhance the performance of the continuous query (collaborative cache management) with respect to the local cache hit ratio and the average delay.